Surface Electromyography Signal Collecting Strategy for Artificial Hand Controlling Purposes

Abdul-Sahib N. Kadhim, Mohammed M. Abdul-Sattar and Hasan S. Falah
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Abdul-Sahib N. Kadhim: Mechanical Engineering Department, College of Engineering, Al Nahrain University, Iraq.
Mohammed M. Abdul-Sattar: Mechanical Engineering Department, College of Engineering, Al Nahrain University, Iraq.
Hasan S. Falah: Mechanical Engineering Department, College of Engineering, Al Nahrain University, Iraq.

European Journal of Engineering and Technology Research, 2018, vol. 2, issue 10, 21-25

Abstract: Surface electromyography technique is presented for muscle activation detection and intuitive control of prostheses or robot arm. This research aims to develop a strategy for collecting EMG signal in order to be used as input control for an artificial hand. Methodology of this research composed of, collecting EMG signal using clinical device to choose the best position. Collect the signal using myoware muscle sensor depending on these positions locating above with determining the threshold value for each position. The test was done on a healthy female person and an amputee person, a number of three position were used by the clinical myotrace 400 each positon composed of four channels i, four channel location were chosen from the three position that were used by the myoware sensor on the forearm in addition to two locations on the ulna, while the amputee included only two locations on the ulna. The locations obtained from the myotrace targeting muscles ( extensor carpi ulnaris, flexor digitorium sublimis, brachioradialis, flexor carpi ulnaris). The threshold values obtained were on a range of 150-320 that consider a non-sensitive. For the amputee the threshold values were the from 150-220 for both the healthy arm and the amputee arm which consider a weaker values.

Keywords: Surface Electromyography; Threshold Value; Electrodes Positions; Artificial Hand (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:2:y:2018:i:10:id:60467

DOI: 10.24018/ejeng.2017.2.10.467

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