Projects - User contributions [en]

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-06-18T09:05:40Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-05-27T17:31:17Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-14T14:50:50Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:19:54Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:18:50Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:11:14Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:09:00Z

A1670240:

== Abstract ==
The aim of this project is to develop a brain-computer interface (BCI) for rehabilitation of stroke patients with impaired limb movement. A BCI is a device which is capable of directly measuring neural oscillations of the brain (aka brainwaves) and interpreting these to perform various functions.<ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref><ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref> In our project we will interpret the brainwaves associated with muscle movement and use this to control a bio-mechanical limb. Not only will this enable motion of a previously paralysed limb, it will also assist in the brain's ability to rewire itself (a concept known as neuroplasticity), since the limb will respond and send feedback to the brain. After a successful rehabilitation the patient will regain control of their limb, and new area of the brain will take on this function.
{{Infobox programming language
| name = C++
| logo = File:ISO C++ Logo.svg
| logo_size = 140px
| paradigm = [[Multi-paradigm programming language|Multi-paradigm]]: [[procedural programming|procedural]], [[functional programming|functional]], [[object-oriented programming|object-oriented]], [[generic programming|generic]]<ref name="stroustruptcpppl">{{Cite book |last=Stroustrup |first=Bjarne |authorlink=Bjarne Stroustrup |title=The C++ Programming Language |year=1997 |edition=Third |chapter=1 |isbn=0-201-88954-4 |oclc=59193992 }}</ref>
| year = {{Start date and age|df=yes|1985}}
| designer = [[Bjarne Stroustrup]]
| latest release version = ISO/IEC 14882:2017
| latest release date = {{Start date and age|2017|12|01|df=yes}}
| typing = [[Static type|Static]], [[Nominal type system|nominative]], [[Type inference|partially inferred]]
| implementations = {{nowraplinks|[[Clang|LLVM Clang]], [[GNU Compiler Collection|GCC]], [[Microsoft Visual C++]], [[C++Builder|Embarcadero C++Builder]], [[Intel C++ Compiler]], [[IBM XL C++]], [[Edison Design Group|EDG]]}}
| influenced by = [[Ada (programming language)|Ada]], [[ALGOL 68]], [[C (programming language)|C]], [[CLU (programming language)|CLU]], [[ML (programming language)|ML]], [[Simula]]
| influenced = [[Ada (programming language)|Ada 95]], [[C Sharp (programming language)|C#]],<ref name="influenceSharp">{{cite journal |last=Naugler |first=David |date=May 2007 |title=C# 2.0 for C++ and Java programmer: conference workshop |journal=Journal of Computing Sciences in Colleges |volume=22 |issue=5 |quote=Although C# has been strongly influenced by Java it has also been strongly influenced by C++ and is best viewed as a descendant of both C++ and Java.}}</ref> [[C99]], [[Chapel (programming language)|Chapel]],<ref name="chplspec">{{cite web|title=Chapel spec (Acknowledgements)|url=http://chapel.cray.com/spec/spec-0.98.pdf|date=1 October 2015|accessdate=14 January 2016|publisher=Cray Inc}}</ref> [[D (programming language)|D]], [[Java (programming language)|Java]],<ref>{{cite web | url=https://books.google.com/books?id=0rUtBAAAQBAJ&lpg=PA133&pg=PA133#v=onepage&q&f=true|title=Cracking The Java Programming Interview :: 2000+ Java Interview Que/Ans |author=Harry. H. Chaudhary |accessdate=29 May 2016 |date=28 July 2014}}</ref> [[Lua (programming language)|Lua]], [[Perl]], [[PHP]], [[Python (programming language)|Python]],<ref>{{Cite web|url=https://docs.python.org/tutorial/classes.html|title=9. Classes — Python 3.6.4 documentation|website=docs.python.org|access-date=2018-01-09}}</ref> [[Rust (programming language)|Rust]], [[Nim (programming language)|Nim]]{{citation needed|date=April 2017}}
| programming_language = C++ or C
| license =
| file_ext = .C .cc .cpp .cxx {{nowrap|.c++}} .h .hh .hpp .hxx {{nowrap|.h++}}
| website = {{URL|http://isocpp.org/}}
| wikibooks = C++ Programming
| caption =
}}
__TOC__

== Project Team ==
=== Students ===
Alex Woodcock 
Artem Vasilyev 

=== Supervisors ===
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Introduction ==
[[File:BCI_user_1.jpg|300px|thumb|A BCI user with an EEG headset viewing his brainwaves]]
To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

=== Motivation ===
A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

=== Current Technology ===
Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

=== Work by previous UoA Students ===
This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

=== Objectives ===
The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== Background ==
=== Neurons ===
=== The Human Brain ===
=== Neural Frequency Bands ===
=== Control Signals ===
=== Neuroplasticity ===

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

== System Overview ==
=== Hardware ===
==== Electrodes ====
==== Data Aquisition ====
=== Software ===
==== Spatial Filters ====
==== Temporal Filters ====
==== Visulisations ====
=== Bio-Mechanical Limb ===

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== Glossary ==

== Further Reading ==

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:05:47Z

A1670240:

== Abstract ==
The aim of this project is to develop a brain-computer interface (BCI) for rehabilitation of stroke patients with impaired limb movement. A BCI is a device which is capable of directly measuring neural oscillations of the brain (aka brainwaves) and interpreting these to perform various functions.<ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref><ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref> In our project we will interpret the brainwaves associated with muscle movement and use this to control a bio-mechanical limb. Not only will this enable motion of a previously paralysed limb, it will also assist in the brain's ability to rewire itself (a concept known as neuroplasticity), since the limb will respond and send feedback to the brain. After a successful rehabilitation the patient will regain control of their limb, and new area of the brain will take on this function.

__TOC__

== Project Team ==
=== Students ===
Alex Woodcock 
Artem Vasilyev 

=== Supervisors ===
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Introduction ==
[[File:BCI_user_1.jpg|300px|thumb|A BCI user with an EEG headset viewing his brainwaves]]
To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

=== Motivation ===
A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

=== Current Technology ===
Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

=== Work by previous UoA Students ===
This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

=== Objectives ===
The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== Background ==
=== Neurons ===
=== The Human Brain ===
=== Neural Frequency Bands ===
=== Control Signals ===
=== Neuroplasticity ===

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

== System Overview ==
=== Hardware ===
==== Electrodes ====
==== Data Aquisition ====
=== Software ===
==== Spatial Filters ====
==== Temporal Filters ====
==== Visulisations ====
=== Bio-Mechanical Limb ===

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

<source lang="java">
/** @file paex_saw.c
@ingroup examples_src
@brief Play a simple (aliasing) sawtooth wave.
@author Phil Burk http://www.softsynth.com
*/

#include <cstdio>
#include <iostream>
#include <cmath>
#include "portaudio.h"

#define NUM_SECONDS (12)
#define SAMPLE_RATE (44100)

typedef struct
{
float left_phase;
float right_phase;
}
paTestData;

/* This routine will be called by the PortAudio engine when audio is needed.
** It may called at interrupt level on some machines so don't do anything
** that could mess up the system like calling malloc() or free().
*/
static int patestCallback(const void* inputBuffer, void* outputBuffer,
unsigned long framesPerBuffer,
const PaStreamCallbackTimeInfo* timeInfo,
PaStreamCallbackFlags statusFlags,
void *userData)
{
static int n = 0;
float* out = (float*)outputBuffer;

for (int i = 0; i < framesPerBuffer*2; i+=2)
{
static float decay = 1;
static float decay2 = 1.4;

decay *= 0.999995;
decay2 *= 0.99996;
float mag = (6.0 + sin(2 * n * 2 * 3.1415 / 176400.0)) / 80.0;
out[i] = decay * mag * sin(0.04 * n);
out[i + 1] = decay * mag * sin(0.04 * n + 2*n*2*3.1415/176400.0);

out[i] += decay * 0.07 * sin(1.334839854 * 0.04 * n);
out[i + 1] += decay * 0.07 * sin(1.334839854 * 0.04 * n + 1.334839854 * 2 * n * 2 * 3.1415 / 176400.0);

out[i] += decay2 * 0.07 * sin(1.334839854 * 0.02 * n);
out[i + 1] += decay2 * 0.07 * sin(1.334839854 * 0.02 * n + 1.334839854 * n * 2 * 3.1415 / 176400.0);

if (n > 88200*3)
{
out[i] += decay * 0.05 * sin(1.681792831 * 0.04 * n);
out[i + 1] += decay * 0.05 * sin(1.681792831 * 0.04 * n + 1.681792831 * 2 * n * 2 * 3.1415 / 176400.0);
out[i] += decay * 0.02 * sin(2 * 0.04 * n);
out[i + 1] += decay * 0.02 * sin(2 * 0.04 * n + 2 * 2 * n * 2 * 3.1415 / 176400.0);
}
else
{
if (n == 88200 * 3)
{
decay = 1;
decay2 = 0.5;
}

out[i] += decay * 0.04 * sin(1.781797436 * 0.04 * n);
out[i + 1] += decay * 0.04 * sin(1.781797436 * 0.04 * n + 1.781797436 * 2 * n * 2 * 3.1415 / 176400.0);

}
++n;
}

return 0;
}

/*******************************************************************/
static paTestData data;

int main(void)
{
PaStream *stream;
PaError err;

printf("PortAudio Test: output sawtooth wave.\n");
/* Initialize our data for use by callback. */
data.left_phase = data.right_phase = 0.0;
/* Initialize library before making any other calls. */
err = Pa_Initialize();
if (err != paNoError) goto error;

/* Open an audio I/O stream. */
err = Pa_OpenDefaultStream(&stream,
0, /* no input channels */
2, /* stereo output */
paFloat32, /* 32 bit floating point output */
SAMPLE_RATE,
1024, /* frames per buffer */
patestCallback,
&data);
if (err != paNoError) goto error;

err = Pa_StartStream(stream);
if (err != paNoError) goto error;

/* Sleep for several seconds. */
Pa_Sleep(NUM_SECONDS * 1000);

err = Pa_StopStream(stream);
if (err != paNoError) goto error;
err = Pa_CloseStream(stream);
if (err != paNoError) goto error;
Pa_Terminate();
printf("Test finished.\n");

std::cin.clear(); // reset any error flags
std::cin.ignore(32767, '\n'); // ignore any characters in the input buffer until we find an enter character
std::cin.get(); // get one more char from the user

return err;

error:
Pa_Terminate();
fprintf(stderr, "An error occured while using the portaudio stream\n");
fprintf(stderr, "Error number: %d\n", err);
fprintf(stderr, "Error message: %s\n", Pa_GetErrorText(err));
return err;
}

</source>

== Glossary ==

== Further Reading ==

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T15:04:39Z

A1670240:

== Abstract ==
The aim of this project is to develop a brain-computer interface (BCI) for rehabilitation of stroke patients with impaired limb movement. A BCI is a device which is capable of directly measuring neural oscillations of the brain (aka brainwaves) and interpreting these to perform various functions.<ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref><ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref> In our project we will interpret the brainwaves associated with muscle movement and use this to control a bio-mechanical limb. Not only will this enable motion of a previously paralysed limb, it will also assist in the brain's ability to rewire itself (a concept known as neuroplasticity), since the limb will respond and send feedback to the brain. After a successful rehabilitation the patient will regain control of their limb, and new area of the brain will take on this function.

__TOC__

== Project Team ==
=== Students ===
Alex Woodcock 
Artem Vasilyev 

=== Supervisors ===
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Introduction ==
[[File:BCI_user_1.jpg|300px|thumb|A BCI user with an EEG headset viewing his brainwaves]]
To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

=== Motivation ===
A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

=== Current Technology ===
Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

=== Work by previous UoA Students ===
This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

=== Objectives ===
The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== Background ==
=== Neurons ===
=== The Human Brain ===
=== Neural Frequency Bands ===
=== Control Signals ===
=== Neuroplasticity ===

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

== System Overview ==
=== Hardware ===
==== Electrodes ====
==== Data Aquisition ====
=== Software ===
==== Spatial Filters ====
==== Temporal Filters ====
==== Visulisations ====
=== Bio-Mechanical Limb ===

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

<source lang="c++">
/** @file paex_saw.c
@ingroup examples_src
@brief Play a simple (aliasing) sawtooth wave.
@author Phil Burk http://www.softsynth.com
*/

#include <cstdio>
#include <iostream>
#include <cmath>
#include "portaudio.h"

#define NUM_SECONDS (12)
#define SAMPLE_RATE (44100)

typedef struct
{
float left_phase;
float right_phase;
}
paTestData;

/* This routine will be called by the PortAudio engine when audio is needed.
** It may called at interrupt level on some machines so don't do anything
** that could mess up the system like calling malloc() or free().
*/
static int patestCallback(const void* inputBuffer, void* outputBuffer,
unsigned long framesPerBuffer,
const PaStreamCallbackTimeInfo* timeInfo,
PaStreamCallbackFlags statusFlags,
void *userData)
{
static int n = 0;
float* out = (float*)outputBuffer;

for (int i = 0; i < framesPerBuffer*2; i+=2)
{
static float decay = 1;
static float decay2 = 1.4;

decay *= 0.999995;
decay2 *= 0.99996;
float mag = (6.0 + sin(2 * n * 2 * 3.1415 / 176400.0)) / 80.0;
out[i] = decay * mag * sin(0.04 * n);
out[i + 1] = decay * mag * sin(0.04 * n + 2*n*2*3.1415/176400.0);

out[i] += decay * 0.07 * sin(1.334839854 * 0.04 * n);
out[i + 1] += decay * 0.07 * sin(1.334839854 * 0.04 * n + 1.334839854 * 2 * n * 2 * 3.1415 / 176400.0);

out[i] += decay2 * 0.07 * sin(1.334839854 * 0.02 * n);
out[i + 1] += decay2 * 0.07 * sin(1.334839854 * 0.02 * n + 1.334839854 * n * 2 * 3.1415 / 176400.0);

if (n > 88200*3)
{
out[i] += decay * 0.05 * sin(1.681792831 * 0.04 * n);
out[i + 1] += decay * 0.05 * sin(1.681792831 * 0.04 * n + 1.681792831 * 2 * n * 2 * 3.1415 / 176400.0);
out[i] += decay * 0.02 * sin(2 * 0.04 * n);
out[i + 1] += decay * 0.02 * sin(2 * 0.04 * n + 2 * 2 * n * 2 * 3.1415 / 176400.0);
}
else
{
if (n == 88200 * 3)
{
decay = 1;
decay2 = 0.5;
}

out[i] += decay * 0.04 * sin(1.781797436 * 0.04 * n);
out[i + 1] += decay * 0.04 * sin(1.781797436 * 0.04 * n + 1.781797436 * 2 * n * 2 * 3.1415 / 176400.0);

}
++n;
}

return 0;
}

/*******************************************************************/
static paTestData data;

int main(void)
{
PaStream *stream;
PaError err;

printf("PortAudio Test: output sawtooth wave.\n");
/* Initialize our data for use by callback. */
data.left_phase = data.right_phase = 0.0;
/* Initialize library before making any other calls. */
err = Pa_Initialize();
if (err != paNoError) goto error;

/* Open an audio I/O stream. */
err = Pa_OpenDefaultStream(&stream,
0, /* no input channels */
2, /* stereo output */
paFloat32, /* 32 bit floating point output */
SAMPLE_RATE,
1024, /* frames per buffer */
patestCallback,
&data);
if (err != paNoError) goto error;

err = Pa_StartStream(stream);
if (err != paNoError) goto error;

/* Sleep for several seconds. */
Pa_Sleep(NUM_SECONDS * 1000);

err = Pa_StopStream(stream);
if (err != paNoError) goto error;
err = Pa_CloseStream(stream);
if (err != paNoError) goto error;
Pa_Terminate();
printf("Test finished.\n");

std::cin.clear(); // reset any error flags
std::cin.ignore(32767, '\n'); // ignore any characters in the input buffer until we find an enter character
std::cin.get(); // get one more char from the user

return err;

error:
Pa_Terminate();
fprintf(stderr, "An error occured while using the portaudio stream\n");
fprintf(stderr, "Error number: %d\n", err);
fprintf(stderr, "Error message: %s\n", Pa_GetErrorText(err));
return err;
}

</source>

== Glossary ==

== Further Reading ==

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T14:20:53Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T14:10:04Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:58:51Z

A1670240:

File:BCI user 1.jpg

2018-04-13T13:57:38Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:56:18Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:29:20Z

A1670240:

Projects talk:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:16:18Z

A1670240: Created page with "discuss here"

discuss here

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:14:23Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T13:03:44Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:56:53Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:55:40Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:55:02Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:52:06Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:50:34Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:31:25Z

A1670240:

== Project Team ==
=== Students ===
Alex Woodcock 
Artem Vasilyev 

=== Supervisors ===
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Abstract ==

== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
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| row 1, cell 2
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|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:30:49Z

A1670240:

== Project Team ==
=== Students === 
Alex Woodcock 
Artem Vasilyev 

=== Supervisors === 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Abstract ==

== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
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! Header 2
! Header 3
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| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:29:35Z

A1670240:

==Project Team==
'''Students''' 
Alex Woodcock 
Artem Vasilyev 

===Supervisors=== 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

==Abstract==

==Introduction==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
|+ Table 1
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! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:27:35Z

A1670240:

== 1. Project Team ==
'''1.1 Students''' 
Alex Woodcock 
Artem Vasilyev 

'''1.2 Supervisors''' 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== 2. Abstract ==

== 3. Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:24:07Z

A1670240:

#== Project Team ==
##'''Students''' 
Alex Woodcock 
Artem Vasilyev 

##'''Supervisors''' 
#[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
#[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Abstract ==

== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T12:23:24Z

A1670240:

== #Project Team ==
'''##Students''' 
Alex Woodcock 
Artem Vasilyev 

'''##Supervisors''' 
#[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
#[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Abstract ==

== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:33:04Z

A1670240:

== Project Team ==
'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

== Abstract ==
== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

[[File:Example.jpg]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:28:05Z

A1670240:

== Project Team ==
'''Students''' 
Alex Woodcock 
Artem Vasilyev 
'''Supervisors''' 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[http://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 
== Abstract ==
== Introduction ==

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Nicolas-Alonso, LF & Gomez-Gil, J, 'Brain Computer Interfaces, a Review', Sensors; 2012, vol. 12, pp. 1211-1279.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

[[File:Example.jpg]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

{| class="wikitable"
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|}

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:24:33Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
[http://www.adelaide.edu.au/directory/mathias.baumert Assoc.Professor Mathias Baumert] 
[https://www.adelaide.edu.au/directory/david.bowler Mr David Bowler] 

{| class="wikitable"
|+ Table 1
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! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
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|-
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|}

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

[[File:Example.jpg]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:18:55Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London.]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

[[File:Durdle Door Overview.jpg|thumb|[[Durdle Door]], a [[natural arch]] near [[Lulworth Cove]]]]

[[File:Example.jpg]]

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:12:44Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

{| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:12:03Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

{
| class="wikitable"
|+ Table 1
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T11:08:43Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

{| class="wikitable"
|-
! Header 1
! Header 2
! Header 3
|-
| row 1, cell 1
| row 1, cell 2
| row 1, cell 3
|-
| row 2, cell 1
| row 2, cell 2
| row 2, cell 3
|}

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:59:41Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 Schalk, G & Mellinger, J 2010, A Practical Guide to Brain-Computer Interfacing with BCI2000, Springer, London]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:58:15Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 BCI2000 Book]</ref>

text 2 <ref name="r1" /> <ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:56:29Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

text 1 <ref name="r1">[https://www.amazon.com/Practical-Guide-Brain-Computer-Interfacing-BCI2000/dp/1849960917 BCI2000 Book]</ref>

text 2 <ref name="r2" /><ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:51:39Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert {{cn}} 
David Bowler 

Hello<ref name="LoC">[https://www.loc.gov/about/ Library of Congress]</ref> World!<ref>http://www.w3.org/</ref>

Hello again!<ref name="LoC" /><ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

== References ==
{{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:46:42Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert{{cn}} 
David Bowler 

Hello<ref name="LoC">[https://www.loc.gov/about/ Library of Congress]</ref> World!<ref>http://www.w3.org/</ref>

Hello again!<ref name="LoC" /><ref>Perry's Handbook, Sixth Edition, McGraw-Hill Co., 1984.</ref>

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

References: {{reflist}}

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:09:02Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

===Introduction to the Brain Computer Interface Control for Biomedical Applications Project===

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T10:07:11Z

A1670240: Redirected page to Https://en.wikipedia.org/wiki/Help:Cheatsheet

#REDIRECT [[https://en.wikipedia.org/wiki/Help:Cheatsheet]]

== Project Team ==

<nowiki><img src="https://upload.wikimedia.org/wikipedia/commons/8/8d/SimulationNeuralOscillations.png"></nowiki>

----

== Headline text ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:56:36Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:55:22Z

A1670240:

== Project Team ==

<nowiki><img src="https://upload.wikimedia.org/wikipedia/commons/8/8d/SimulationNeuralOscillations.png"></nowiki>

----

== Headline text ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

A '''brain–computer interface''' ('''BCI'''), sometimes called a '''neural-control interface''' ('''NCI'''), '''mind-machine interface''' ('''MMI'''), '''direct neural interface''' ('''DNI'''), or '''brain–machine interface''' ('''BMI'''), is a direct communication pathway between an enhanced or wired [[brain]] and an external device. BCI differs from [[Neuromodulation (medicine)|neuromodulation]] in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.<ref name="Krucoff 584">{{Cite journal|last=Krucoff|first=Max O.|last2=Rahimpour|first2=Shervin|last3=Slutzky|first3=Marc W.|last4=Edgerton|first4=V. Reggie|last5=Turner|first5=Dennis A.|date=2016-01-01|title=Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation|url=http://journal.frontiersin.org/article/10.3389/fnins.2016.00584/full|journal=Neuroprosthetics|pages=584|doi=10.3389/fnins.2016.00584|pmc=5186786|pmid=28082858|volume=10}}</ref>

Research on BCIs began in the 1970s at the [[University of California, Los Angeles]] (UCLA) under a grant from the [[National Science Foundation]], followed by a contract from [[DARPA]].<ref name="Vidal1">{{cite journal|pmid=4583653|doi=10.1146/annurev.bb.02.060173.001105|year=1973|last1=Vidal|first1=JJ|title=Toward direct brain-computer communication|volume=2|pages=157–80|journal=Annual Review of Biophysics and Bioengineering|issue=1}}</ref><ref name="Vidal2">{{cite journal|author=J. Vidal|title=Real-Time Detection of Brain Events in EEG|journal=IEEE Proceedings|year=1977|url=http://www.cs.ucla.edu/~vidal/Real_Time_Detection.pdf|volume=65|pages=633–641|doi=10.1109/PROC.1977.10542|issue=5}}</ref> The papers published after this research also mark the first appearance of the expression ''brain–computer interface'' in scientific literature.

'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:46:57Z

A1670240:

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:45:16Z

A1670240:

[http://www.example.com link title]== Project Team ==
[[File:Example.jpg]]'
<nowiki><img src="https://upload.wikimedia.org/wikipedia/commons/8/8d/SimulationNeuralOscillations.png"></nowiki>
'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:42:53Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

<img src="https://upload.wikimedia.org/wikipedia/commons/8/8d/SimulationNeuralOscillations.png">

'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:42:07Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

<link href="style1.css" rel="stylesheet" type="text/css" />
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'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.

Projects:2018s1-155 Brain Computer Interface Control for Biomedical Applications

2018-04-13T09:36:07Z

A1670240:

== Project Team ==

'''Students''' 
Alex Woodcock 
Artem Vasilyev 

'''Supervisors''' 
Mathias Baumert 
David Bowler 

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'''Introduction to the Brain Computer Interface Control for Biomedical Applications Project'''

Welcome to the Brain-Computer Interface Control for Biomedical applications project presentation by Artem Vasilyev and Alex Woodcock.

''Motivation for the project''

A stroke is a disease that causes damage to the brain, usually due to a blood clot. Often the stroke causes partial or complete loss of motor functions, preventing people from even doing something as simple as independently getting a glass of water. However, through advances in brain research and personalised brain wave monitoring technology, researchers have found ways to restore lost motor functions.

''Brain Computer Interface''

To explain what a BCI, brain computer interface, is, it is a system that measures neural oscillations or brainwaves. The resulting waveform presented to the researchers is influenced by various factors such as the subject’s thoughts, intentions, movements and emotions. The data is collected using various mechanisms which can be electric, magnetic and optical.

''Brain Cortex''

In case you do not know, the human brain consists of many cortex that are responsible for different functions of our bodies, for example the motor cortex is the one responsible for movement.

''Current BCI technology''

Commonly, researchers use specially made caps with predetermined holes for electrodes. This is because the human scalp has been fully mapped. This allows for consistency in readings and in between research initiatives. There is a broad spectrum of BCI uses such as helping people with disability by controlling various devices and gaming.

The technology is not ideal and there are many challenges in using it. For example due to the many neurons in the human brain, there is a very low Signal To Noise ratio and spatial resolution. The electrodes that are placed on the subjects’ scalp are also prone to being affected by artefacts. Artefacts are undesirable potentials that are caused not by brain signals, but by some external origin. This can be something as subtle as blinking, eye movements or facial muscle movements such as the jaw. During data acquisition, subjects are carefully instructed to minimise movements, but digital filters are also used to isolate their effects.

''Previous groups''

This is a quick rundown of what the previous groups did on this project. They have used the official proprietary Emotiv software to test the headset, constructed a robotic limb, connected the Emotiv hardware to the open source BCI2000 software package and redesigned the headset itself. Sadly the latest iteration of the headset is somewhat unusable, therefore we will redesign it once more.

''Goals of the project''

The key goal of this project is to develop a low cost BCI system that uses commercial hardware. It is to be non invasive, meaning no probes will go in someone’s skull, and to interface with Emotiv BCI hardware. We also plan to develop brand new BCI software that will have a modern Graphical User Interface, visualizations, and allow us direct control over the implemented filters. Then, we will analyse our readings, classify relevant features that correspond to hand movements and develop a robotic limb support system that will enable neuroplasticity in stroke patients, allowing them to return to normal lives. Neuroplasticity is a relatively newly discovered phenomenon which is essentially rewiring the neurons in the brain, allowing different areas of the brain control over new functions.