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A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair

Master of Science in Biomedical Electronic Engineering

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Bibliographic Details
Main Author: Hayder Abdulazeez Yousif, Al-Yasari
Other Authors: Norasmadi, Abdul Rahim, Dr.
Format: Dissertation
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2016
Subjects:
Electromyography
Motion control devices
Wheelchairs
Masseter muscle
Quadriplegia
Electromyogram (EMG)
EMG signals
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72463
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spelling my.unimap-724632021-10-15T07:12:38Z A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair Hayder Abdulazeez Yousif, Al-Yasari Norasmadi, Abdul Rahim, Dr. Electromyography Motion control devices Wheelchairs Masseter muscle Quadriplegia Electromyogram (EMG) EMG signals Master of Science in Biomedical Electronic Engineering There are many people who cannot control the movement of their upper or lower limbs. Also, there are many people affected with some form of paralysis, suffering from a spinal cord injury, and many elderly people are unable to control their upper and lower limbs. Therefore, it is necessary to provide them with an alternative control device that can help them to achieve some mobility independence, where the wheelchair is very important for these people to help them in their daily lives for moving from one place to another in a comfortable manner. The main objective of this research work is to control the movements of the wheelchair in five directions (forward, reverse, stop, left and right), using signals from the masseter and buccinators muscles as control signals. Then extracted the features of the autoregressive model, waveform length, mean absolute value and root mean square, and then classify them by using a K-nearest neighbor classifier and linear discriminant analysis to choose the better result of the classification and utilize it as a control signals for the wheelchair movement in offline method. The result of classification shows that the accuracy of the K-nearest neighbor classifier is very higher compared with the linear discriminant analysis classifier, where the highest rate of accuracy was 98.88% when using the KNN classifier with the AR model 4-order. 2016 2021-10-15T07:10:57Z 2021-10-15T07:10:57Z Dissertation http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72463 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Electromyography
Motion control devices
Wheelchairs
Masseter muscle
Quadriplegia
Electromyogram (EMG)
EMG signals
spellingShingle Electromyography
Motion control devices
Wheelchairs
Masseter muscle
Quadriplegia
Electromyogram (EMG)
EMG signals
Hayder Abdulazeez Yousif, Al-Yasari
A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
description Master of Science in Biomedical Electronic Engineering
author2 Norasmadi, Abdul Rahim, Dr.
author_facet Norasmadi, Abdul Rahim, Dr.
Hayder Abdulazeez Yousif, Al-Yasari
format Dissertation
author Hayder Abdulazeez Yousif, Al-Yasari
author_sort Hayder Abdulazeez Yousif, Al-Yasari
title A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
title_short A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
title_full A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
title_fullStr A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
title_full_unstemmed A classification of EMG signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
title_sort classification of emg signal from masseter and buccinators, muscles to control the directional movement of power-assisted wheelchair
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2016
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72463
_version_ 1724609888898777088
score 13.222552

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