EMG-Based Spasticity Robotic Arm Forupper Arm Fatigue Identification

  • Authors

    • Abdul Malik Mohd Ali
    • Syed Faiz Ahmed
    • Athar Ali
    • M Kamran Joyo
    • Kushairy A. Kadir
    • Radzi Ambar
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.34.13917
  • Electromyogram (EMG), Rehabilitation, Robotic and Sensor.

  • Abstract

    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.

     

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  • How to Cite

    Malik Mohd Ali, A., Faiz Ahmed, S., Ali, A., Kamran Joyo, M., A. Kadir, K., & Ambar, R. (2018). EMG-Based Spasticity Robotic Arm Forupper Arm Fatigue Identification. International Journal of Engineering & Technology, 7(2.34), 79-83. https://doi.org/10.14419/ijet.v7i2.34.13917

    Received date: 2018-06-08

    Accepted date: 2018-06-08

    Published date: 2018-06-08