Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment

Patients suffering from diseases like motor neuron diseases (MND), or trauma such as spinal cord injury (SCI), and amputation are not able to move. Presented is a work on combining the power wheelchair designed to aid the movement of disabled patient and a Brain Computer Interface (BCI) can be used...

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Format:	Thesis
Language:	English
Subjects:	Electroencephalography Amyotrophic lateral sclerosis Wheelchair Power wheelchair > Design and construction
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/3/Jackie%20Teh.pdf
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id	my-unimap-78027
record_format	uketd_dc
spelling	my-unimap-780272023-03-07T01:12:16Z Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment Paulraj, M. P., Prof. Dr. Patients suffering from diseases like motor neuron diseases (MND), or trauma such as spinal cord injury (SCI), and amputation are not able to move. Presented is a work on combining the power wheelchair designed to aid the movement of disabled patient and a Brain Computer Interface (BCI) can be used to replace conventional joystick so that it can be controlled without using hands. By using the BCI, the brain signal emanated during Motor Imagery (MI) tasks can be converted into control signal for power wheelchair maneuvering. In this research, five subjects are requested to perform six Kinesthetic Motor Imagery tasks plus one relax task and the Electroencephalography (EEG) signals are recorded. Elliptic filter was used to remove power line noise. The proposed feature, combined feature of Fractal Dimension with Mel-frequency Cepstral Coefficients has outperformed the others. It was able to improve the classification performance to a satisfactory level especially for the subject 3 which yielded relatively poor result by using four other feature extraction methods. The classifiers network parameters were experimentally selected and the Levenberg-Marquardt training algorithm was used to train the networks. The Multilayer Perceptron Neural Network (MLPNN) outperformed Elman Recurrent Neural Network and Nonlinear Autoregressive Exogenous model (NARX) with average accuracy of 91.7%. The developed network models was further tested and evaluated with two simulated virtual environment created by using MATLAB graphical user interface (GUI). The simulation results suggested that step by step control is better than continuous control of wheelchair, and also the proposed feature, combined feature of FD with MFCCs and MLPNN can be used to classify Motor Imagery signal for directional control of powered wheelchair. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/78027 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/4/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/1/Page%201-24.pdf 784ce3421281c42f4339e7067c36d326 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/2/Full%20text.pdf d5f227a401b694b0f1d05f18e9c5eab3 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/3/Jackie%20Teh.pdf 5c051083266c29de0d594bfab1f835df Universiti Malaysia Perlis (UniMAP) Electroencephalography Amyotrophic lateral sclerosis Wheelchair Power wheelchair -- Design and construction School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Paulraj, M. P., Prof. Dr.
topic	Electroencephalography Amyotrophic lateral sclerosis Wheelchair Power wheelchair -- Design and construction
spellingShingle	Electroencephalography Amyotrophic lateral sclerosis Wheelchair Power wheelchair -- Design and construction Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
description	Patients suffering from diseases like motor neuron diseases (MND), or trauma such as spinal cord injury (SCI), and amputation are not able to move. Presented is a work on combining the power wheelchair designed to aid the movement of disabled patient and a Brain Computer Interface (BCI) can be used to replace conventional joystick so that it can be controlled without using hands. By using the BCI, the brain signal emanated during Motor Imagery (MI) tasks can be converted into control signal for power wheelchair maneuvering. In this research, five subjects are requested to perform six Kinesthetic Motor Imagery tasks plus one relax task and the Electroencephalography (EEG) signals are recorded. Elliptic filter was used to remove power line noise. The proposed feature, combined feature of Fractal Dimension with Mel-frequency Cepstral Coefficients has outperformed the others. It was able to improve the classification performance to a satisfactory level especially for the subject 3 which yielded relatively poor result by using four other feature extraction methods. The classifiers network parameters were experimentally selected and the Levenberg-Marquardt training algorithm was used to train the networks. The Multilayer Perceptron Neural Network (MLPNN) outperformed Elman Recurrent Neural Network and Nonlinear Autoregressive Exogenous model (NARX) with average accuracy of 91.7%. The developed network models was further tested and evaluated with two simulated virtual environment created by using MATLAB graphical user interface (GUI). The simulation results suggested that step by step control is better than continuous control of wheelchair, and also the proposed feature, combined feature of FD with MFCCs and MLPNN can be used to classify Motor Imagery signal for directional control of powered wheelchair.
format	Thesis
title	Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
title_short	Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
title_full	Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
title_fullStr	Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
title_full_unstemmed	Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
title_sort	design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78027/3/Jackie%20Teh.pdf
_version_	1776104281080856576

Design and development of a motor imagery based interfaces of wheelchair in a simulated virtual environment

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