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Detection of EMG onset in ERP research
Author(s) -
BOXTEL G. J. M.,
GERAATS L. H. D.,
BERGLENSSEN M. M. C.,
BRUNIA C. H. M.
Publication year - 1993
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/j.1469-8986.1993.tb02062.x
Subject(s) - thumb , electromyography , psychology , dorsum , task (project management) , index finger , artificial intelligence , audiology , speech recognition , physical medicine and rehabilitation , pattern recognition (psychology) , computer science , neuroscience , medicine , engineering , anatomy , systems engineering
Many researchers have used off‐line techniques for the automatic detection of electromyogram (EMG) onset. However, very little is known about the accuracy of these methods. In the present study, five such methods are evaluated and their accuracy is reported. Five subjects were asked to produce fast (ballistic) and slow (ramp) contractions with thumb and index finger of the right hand in a simple reaction time task. EMG was recorded from the first dorsal interosseus muscle, and onsets were visually determined in the raw EMG. These onsets were compared with the onsets produced by the automated methods on the rectified and low‐pass filtered EMG. Four of the automated methods produced very reliable estimates of the visually determined onsets, at least when additional constraints upon the initial estimates were made. Studies using automated methods for EMG onset detection should report findings about their accuracy.