Classify EMG data for upper limb muscle based on different movement of arm rehabilitation device

'Iffah Masturah , Ibrahim (2014) Classify EMG data for upper limb muscle based on different movement of arm rehabilitation device. Project Report. UTeM. (Submitted)

Text CLASSIFY EMG DATA FOR UPPER LIMB MUSCLE BASED ON DIFFERENT MOVEMENT OF ARM REHABILITATION DEVICE 24pages.pdf Download (731kB)

Abstract

Rehabilitation device is used as an exoskeleton for people who experiencelimb failure. Arm rehabilitation device may easethe rehabilitation programme for those who suffer arm dysfunctional. The device used to facilitate the tasks of the program should improve the electrical activity in the motor unit by minimising the mental effort of the user. Electromyography (EMG) is the techniques to analyse the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person are failed to contract the muscle for movements. To prevent the muscles from paralysis becomes spasticity or flaccid the force of movements has to minimise the mental efforts. To minimise the used of cerebral strength, analysis on EMG signalsfrom normal people are conducted beforeit can be implement in the device. The signalsare collect according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The implementation of EMG signals is to set the movements’ pattern of the arm rehabilitation device. The filtered signal further the process by extracting the features as follows;Standard Deviation(STD), Mean Absolute Value(MAV), Root Mean Square(RMS), Zero Crossing(ZCS) and Variance(VAR). The extraction of EMG data is to have the reduced vector in the signal features for minimising the signals error than can be implement in classifier.The classification of time-domain features only can be applied for three types of time-domain features are Mean Absolute Value(MAV), Root Mean Square(RMS) and Standard Deviation(STD).Thearm movements of 60˚, 90˚ and 120˚ are classified into their own class of degrees movements by using SOM-Toolbox for MATLAB are visualized in U- Matrix form.

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