Difference between revisions of "Projects:2014S1-21 Design And Development of a New Respiratory Monitor for Detection of Sleep Apnoea"
(→Deliverable) |
(→Deliverable) |
||
Line 94: | Line 94: | ||
* Progress report | * Progress report | ||
** Mr Dang's :[https://myuni.adelaide.edu.au/courses/1/3410_ELEC_ENG_COMBINED_0001/groups/_292684_1//_2786549_1/Progress%20report%20-%20Tuong%20Huy%20Dang.pdf] | ** Mr Dang's :[https://myuni.adelaide.edu.au/courses/1/3410_ELEC_ENG_COMBINED_0001/groups/_292684_1//_2786549_1/Progress%20report%20-%20Tuong%20Huy%20Dang.pdf] | ||
− | ** Ms. Chen's: [https://myuni.adelaide.edu.au/courses/1/3410_ELEC_ENG_COMBINED_0001/groups/_292684_1//_2786574_1/Final%20Progress%20Report.pdf]* Final seminar | + | ** Ms. Chen's: [https://myuni.adelaide.edu.au/courses/1/3410_ELEC_ENG_COMBINED_0001/groups/_292684_1//_2786574_1/Final%20Progress%20Report.pdf] |
+ | * Final seminar | ||
* Final Report | * Final Report | ||
* Poster Display | * Poster Display |
Revision as of 11:37, 10 October 2014
This project is to build an improved version of apnea monitor. In this project, the new monitor to be developed should have the ability to recognize different types of apneas, should be non-invasive and easy to use and understand and be less expensive.
The SIDS (Sudden Infant Death Syndrome) monitoring device prototype to be constructed in the duration of 9 months and will be done using acoustic signal acquisition for sensing respiratory signal. It will be a team approach towards the research and development of the project. The project is to be divided in three phases, phase 1: signal acquisition unit, phase 2: signal processing unit and phase 3: a RF unit. Finally, a working prototype of the SIDS monitoring device will be constructed
Contents
Project Information
Background
Sleep Apnoea describes the situation that the breathing stops for a certain amount of time during sleep [1]. It often goes undiagnosed that usually cannot be detected by doctor, and also no blood test can help to diagnose the situation [2]. There are two types of Sleep Apnoea, Obstructive Sleep Apnoea (OSA) and Central Sleep Apnoea (CSA). Obstructive Sleep Apnoea (OSA) describes the most common condition that due to the patient’s pharyngeal narrowing, the airway collapses or becomes blocked during sleep [1]. Central Sleep Apnoea (CSA) is a less common type. It happened when the area of patient’s brain that control the breathing not sending the correct signals to the breathing muscles, the breath will stop for brief periods. In some case, Central Sleep Apnoea can occur with Obstructive Sleep Apnoea [2].
SIDS (Sudden Infant Death Syndrome) is a sudden and unexpected death of a healthy infant less than 1 year old, whose death remains unexplained after medical investigation. Most of SIDS cases occur at night when infant is asleep. According to the report from NSW Commission for Children and Young People, many cases happened when an infant sleeping face down, which may lead to periods of apnoea that my cause death of an infant [6].
Some research show there are some technique exist to detect the sleep apnoea. These methods included use impedance pneumography detect the changes in electrical impedance during the airflow through the lungs [3]; an automated classification algorithm that detects Sleep Apnoea based on the electrocardiogram (ECG) data features [4]; thermistors monitor to detect temperature of the air from the mouth or nostrils [5]; etc.
In this project, the acoustic acquisition technique will be used. Based on the research done by J. Mazumdar et al. on 1996, the acoustic signals have a large potential to identify the sleep apnoea. However, a critical issue in this technique is the signal that receives by the microphone also contained the surrounding sources of sound that interfering with the respiratory signal [5]. Therefore, the signal acquisition unit should be able filtered the noise signal as much as possible and result a clear and accurate respiratory signal. The signal processing unit should be able to identify the classes of the signal and recognize patient’s breathing status.
Significances
According to the Sleep Health Foundation, sleep disorders cost hospitals system $96.2millions in 2010, which 73.1 % of it are spend on the sleep apnoea [7]. Even though, there still have a large number of population had been diagnosed with sleep apnoea. The research show there were an approx. 1.5 million Australians (8.9 % of the population) with sleep disorders [7].
Furthermore, according to the research done by the SIDS and Kids organization, up to 2011, over last 10 years, an average of 0.3 per 1000 SIDS cases happened [3]. This number is shocking. Also, from the research done by NSW Commission for Children and Young People, sleep apnoea is one reasons of sudden infant death, especially face-down position has been prove to be strongly associated with SIDS [6]. Follow figure shows the relationship between infant face-down sleep position and the SIDS rate.
On the other side, the cause of the SIDS still is a mystery. The feature of the sleep apnoea monitor, which able to recognize the sleep apnoea type, can be provide some evidence in order to help with the investigation of the SIDS cause.
Therefore, this project is important because the new apnoea monitor may help research towards further of SIDS. As the feature of this monitor, it will suitable for all classes of people
Aims
The aims of the project are:
- Ability to detect and recognize the sleep apnoea and send a warning to the caregivers
- The device have to be simple enough to be set-up (clear Instruction and easy to understand)
- Portable so the device has to be small enough to carry for users
- Non-invasive
- Power efficient
- Low-cost device
Technical and Software Requirement
Hardware Requirement
- Personal computers, which are compatible and have ability to operate MatLab and Altium Designer without any constraints, are required.
- A breadboard is required which will be used to construct the prototype and testing the device before print the Demo on the PCB board.
- Solder iron
- Lead
- High quality wireless directional microphone
- Power supply (battery)
- Electrical isolation case
- Buzzer or siren
- LED Display Screen
- Variety of hand tools and some basic circuitry components
The majority of these hardware can be found in University store and others stores.
Software Requirement
The project is required a wide range of signals processing skills, techniques and programs to identify the noise sources and process the received data in order to acquire the required signal from the patients.
- MatLab is a computing software that can perform numeric computation and visualization that integrates numerical analysis, matrix computation, signal processing, graphing, and filtering the signals.
- Other software packages that are required to test the circuits and design a PCB prototype is Altium Designer software. Altium Designer is an software that combines Schematic, ECAD Libraries, Rules and Constrains, BoM, supply chain management, ECO Processes and World class PCB Design Tools in one easy to use, Native 3D enhanced, Unified Environment, increasing team’s productivity, efficiency and reducing overall costs and time. Altium Designer is a very useful tool to build and test the PCB board for the device
Method of Approach
- Phase 1: Signal Acquisition
- Determine the location for the microphone -- Amplitude, Frequency and the bandwidth will be located by analyzing the data which is received from the hospital. The result of the analysis will determine the characteristic of the wireless microphone. The microphone shall be modified to match the characteristic and also to match the body's impedance value. The microphone shall be tested and ready for phase 2.
- Choose an appropriate equipment to acquire the acoustic signal -- The respiratory sounds can be acquired from several positions on the body. According to J. Mazumdar’s research, the site on neck adjacent to the larynx will be the chosen for placement of the microphone stethoscope
- Phase 2: Developing Signal Processing Technique
- The digitized signal from phase 1 will be analyzed using a Samsung Ativ 9 laptop. The advantages of this were that we could display and visualize the collected signal. The signal can be processed by using Fast Fourier Transform and Wavelet functions in MatLab
- Fast Fourier Transform (FFT) -- A technique which has considerable number of applications known for frequency analyses, will be used to analyse the signals. The result of it will used as an indicator of respiration. Once the computer received the signal, a text file of the data will be generated. MatLab will reconstruct the text file and analysis the signal
- Wavelet Analysis -- A technique which represent the input signal by using transient waveform (wavelet) which 'shifted' in time and 'scaled' in frequency. The result of it will indicate the coefficient that corresponding to one scale and one frequency.
- The digitized signal from phase 1 will be analyzed using a Samsung Ativ 9 laptop. The advantages of this were that we could display and visualize the collected signal. The signal can be processed by using Fast Fourier Transform and Wavelet functions in MatLab
- Phase 3: Developing the device
- Design/Construct the PCB
- Communication between the board and software
Challenges
To achieve the aim of this project, there are several challenge that the team facing:
- Identify the microphone that satisfied the requirement
- The noise from the surrounding will cause difficulty during analysis, and it is hard to remove
- Time Constrain
- Complexity of the Codes
- Analyzing and constructing parameters and hypothesis
- PCB circuit design: not familiar with the software will cause trouble during the design
- Power Usage: the device has to have minimum usage of power to be able to operate longer and not creating too much heat for the patients
Future Work
- Phase 3
- Run and test more data to make the hypothesis more dynamic
Deliverable
- Proposal Seminar
- Proposal report
- Progress report
- Final seminar
- Final Report
- Poster Display
- Exhibition
Team
Group Members
- Ms. Ran Chen
- Mr. Tuong Huy Dang
Supervisors
Resources
- $250 is allocated to each member in the group
- Access to Electrical & Electronic Computer Lab
References
- [1] Narcolepsy and Overwhelming Daytime Sleep Society of Australia. Sleep Apnoea. [online]. Available: [6]
- [2] National Heart, Lung and Blood Institute. What is Sleep Apnoea?.[online]. Available: [7]
- [3] World Health Organization, “Core Medical Equipment”, World Health Organization, Geneva, Switzerland, Data Sheets Rep, 2011
- [4] L. Almazaydeh et al., “Detection of Obstructive Sleep Apnoea through ECG Signal Features,” in [Electro/Information Technology (EIT)], [2012] © IEEE International Conference, doi: [10.1109/EIT.2012.6220730], Indianapolis, IN, pp.1-6
- [5] A.Ajmani et al., “Spectral Analysis of an Acoustic Respiratory Signal with a View to Development an Apnoea Monitor, "Australian Physical & Engineering Sciences in Medicine, vol.19, no.2, 1996
- [6] NSW Commission for Children and Young People, “Sudden Unexpected Deaths in Infancy: the New South Wales Experience”, New South Wales Child death Review Team, Surry Hills, NSW, Rep, 2005
- [7] Sleep Health Foundation, “Re-awakening Australia: the economic cost of sleep disorders in Australia, 2010”, Deloitte Access Economics Pty Ltd, UK, Rep, 2011.
Contact
Ms. Ran Chen: a1208747@student.adelaide.edu.au
Mr. Tuong Huy Dang: a1600884@student.adelaide.edu.au
See Also
- Heart Signal Processing Software for Evaluating Pacemaker Effectiveness[8]