文章基本信息

标题：NON INVASIVE TECHNIQUE BASED EVALUATION OF ELECTROMYOGRAM SIGNALS USING STATISTICAL ALGORITHM
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作者：Tanu Sharma ; Karan Veer ; Ravinder Agarwal 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2014
卷号：3
期号：5
页码：1987-1991
出版社：Shri Pannalal Research Institute of Technolgy
摘要：It is well known that Surface Electromyography is the activity that is being generated when voluntary contraction took place, so in this investigation, the study of Surface Electromyogram (SEMG) signals at different above-elbow muscles were carried out. These signals were easily acquired from surface of skin of the body using non-invasively house design of hardware system and various techniques for the interpretation of these recorded signals using one way repeated factorial analysis of variance were presented. Acquired data from selected locations of above elbow was interpreted for various features using LABVIEW soft scope and finally the computations of parameters were done. Result shows characteristics change in extracted feature values for different movements with respect to each position and movement.
关键词：Electromyogram signal; data acquisition; ; electrode; statistical technique