Projects:2019s1-155 Brain Computer Interface Control for Biomedical Applications

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Project Team

Students

Zhiying Lin

Kayla Wahlstrom


Supervisors

Associate Professor Mathias Baumert

Mr David Bowler


Introduction

Motivation


Previous UofA student Work

Work completed by previous students included designing a flexible headset using an elastic strap to hold the electrodes. BCI software was also developed, but due to time constraints, some features such as classifiers and the function of Data Tab on the BCI framework were not fully implemented. Also developed was a new mechanical 3D glove, and testing of the system was completed using third-party software platform OpenViBE.


Objective

Background

What is a BCI

The brain-computer interface (BCI) is a collaboration between the brain and a device that allows signals from the brain to direct some external activity, such as controlling a cursor or a prosthetic limb. This interface enables direct communication between the brain and the controlled object.

Types of BCI

There are many different techniques to measure brain signals. These can divided into non-invasive, semi-invasive and invasive. [1]

The Brain and Neural Oscillations



Neuroimaging approaches in BCI[2]

1. Electroencephalography (EEG) measures the difference in potential on the scalp due to neural activity, which is the sum of thousands or millions of cortical neurons' postsynaptic excitatory potential and inhibitory potential.

2. Magnetoencephalography (MEG) measures magnetic field differences related to neuron activity.

3. Functional Magnetic Resonance Imaging (fMRI) was used to detect changes in local cerebral blood volume, cerebral blood flow and oxygenation level during neuron activation.

4. Near Infrared Spectroscopy (NIRS) USES the characteristics of light in the near infrared spectrum to penetrate the skull to a considerable depth for the study of brain metabolism. It can detect the change of hemoglobin concentration in the process of local nerve activity in different wavelengths of weak light intensity.

References

1. http://learn.neurotechedu.com/introtobci/

2. Byoung-Kyong Min, Matthew J. Marzelli and Seung-Schik Yoo (2010) Neuroimaging-based approaches in the brain–computer interface, Available at: https://www.researchgate.net/publication/46109898 (Accessed: 12/4/2019).

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