Open AccessEMG-Based Spasticity Robotic Arm Forupper Arm Fatigue Identification
Author(s) -
Abdul Malik Mohd Ali,
Syed Faiz Ahmed,
Athar Ali,
M. Kamran Joyo,
Kushsairy Kadir,
Radzi Ambar
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.34.13917
Subject(s) - physical medicine and rehabilitation , electromyography , spasticity , signal (programming language) , motor unit , muscle fatigue , computer science , medicine , anatomy , programming language
Electromyogram (EMG) signal reflect the electrical activity of human muscle and contains information about the structure of muscle. Furthermore, motor unit action potential (MUAP) is the results from spatial and temporal summation of difference muscle fibers of a single motor. The EMG signal results, in turn is from the summation of different MUAPs which are sufficiently near the recording electrode. EMG signal can identify the differences between signals from bicep, triceps and forearms during exercise. Raw data from the experiment is vital to assist physiotherapy to understand when the subject fatigue of noise high pick signal during rehabilitation. Several normal subjects were selected to perform experiments to understand the pattern of fatigue in early state, middle stage and last stage of exercises.