EMG Controlled Wheelchair Movement based on Masseter and Buccinators Muscles

EMG Controlled Wheelchair Movement based on Masseter and Buccinators Muscles

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2016 by IJETT Journal
Volume-37 Number-3
Year of Publication : 2016
Authors : Hayder A. Azeez, Norasmadi Abdul Rahim, Muhammad Juhairi Aziz bin safar
DOI :  10.14445/22315381/IJETT-V37P221

Citation 

Hayder A. Azeez, Norasmadi Abdul Rahim, Muhammad Juhairi Aziz bin safar"EMG Controlled Wheelchair Movement based on Masseter and Buccinators Muscles", International Journal of Engineering Trends and Technology (IJETT), V37(3),133-139 July 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
There are many elderly people who lack the control of movement of their upper or lower limbs. There are also many people affected and who are paralyzed. For this reason, the wheelchair is very important for these people to help them daily. The aim of this work is to present a control method of wheelchair movement in five directions: (forward, reverse direction, turn left, turn right, and stop condition) based on the signals of electromyography (EMG), where the EMG signals are collected from the masseter and buccinators muscles, and then extracted features of the autoregressive model (AR model) 4-order, and classify it by using the Knearest neighbor classifier (KNN) and use it as a control signal for the wheelchair’s movement. The rate of classification was a maximum when the value of K=1 and K=2, where the accuracy of the proposed method was as the following: double blowing 98.1, double clenching 97.3, single blowing 96.5, and single clenching 98.1.

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Keywords
Intelligent Wheelchair, EMG, AR model, K-nearest neighbour classifier.