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Mapping of the Upper Limb Movements and Onset Detection

[+] Author Affiliations
Alejandra Avila Vasquez, Jen-Yuan (James) Chang

National Tsing Hua University, Hsinchu, Taiwan

Paper No. ISPS2013-2811, pp. V001T07A001; 3 pages
doi:10.1115/ISPS2013-2811
From:
  • ASME 2013 Conference on Information Storage and Processing Systems
  • ASME 2013 Conference on Information Storage and Processing Systems
  • Santa Clara, California, USA, June 24–25, 2013
  • Conference Sponsors: Information Storage and Processing Systems Division
  • ISBN: 978-0-7918-5553-9
  • Copyright © 2013 by ASME

abstract

Electromyogram (EMG) consists on the recording and measurement of the electrical potential generated by the activation of muscle fibers [1]. Electromyographic signals (EMGs) are directly linked to the movement performed by a person. Thus, the study of EMGs for the control prosthesis and exoskeletons has become increasingly popular in the past years. To provide a real time control of a prosthesis or exoskeleton (assistive device) to the user, the time between the movement performed by a healthy arm and the movement of the exoskeleton should be small as possible. The main objective of this paper is to map different movements of the upper limb. Moreover, detect the onset of the EMGs to determine which muscle is producing movement. Surface electrodes were used to perform the experiments in order to insure the comfort of the subjects. The analysis of the signal to detect the onset was done using Matlab. After mapping eight movements, results show that the EMGs recorded from the Trapezius muscle can be used as a discriminative to differentiate between movements performed by the arm and movements performed by the forearm and hand. This will reduce the time and number of EMG channels needed to correctly identify the movement performed by the upper limb of a subject.

Copyright © 2013 by ASME

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