Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition
نویسندگان
چکیده
منابع مشابه
REVIEW Motor Unit Firing Behavior in Man
Studies on motor unit firing behavior in man by the decomposition technique are described. The decomposition technique identifies motor unit firing with 100% accuracy at force levels of greater than 80% maximal voluntary contraction (MVC). In all muscles examined, the higher the recruitment threshold of the motor unit, the lower the rate at which it fired at the target level. Smaller muscles, s...
متن کاملHigh-density Surface EMG: Techniques and Applications at a Motor Unit Level
* Correspondence to: Dick F. Stegeman, 920 Department of Neurology / Clinical Neurophysiology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Medical Centre Nijmegen, P.O. Box 9101, 6500HB Nijmegen, The Netherlands, e-mail: [email protected] Received 20 March 2012; accepted 24 April 2012 High-density Surface EMG: Techniques and Applications at a Motor ...
متن کاملHand dominance and motor unit firing behavior.
Daily preferential use was shown to alter physiological and mechanical properties of skeletal muscle. This study was aimed at revealing differences in the control strategy of muscle pairs in humans who show a clear preference for one hand. We compared the motor unit (MU) recruitment and firing behavior in the first dorsal interosseous (FDI) muscle of both hands in eight male volunteers whose ha...
متن کاملLateral dominance and motor unit firing behavior.
Twelve subjects were classified as left-handed (LH) or right-handed (RH) using Annett's hand dominance classification. Motor unit recordings were obtained from the first dorsal interosseous (FDI) muscle of each hand using a quadrifilar needle electrode. Firing occurrences of individual motor units were then identified and the firing rates of all motor units recorded during the contraction were ...
متن کاملHigh-yield decomposition of surface EMG signals.
OBJECTIVE Automatic decomposition of surface electromyographic (sEMG) signals into their constituent motor unit action potential trains (MUAPTs). METHODS A small five-pin sensor provides four channels of sEMG signals that are in turn processed by an enhanced artificial intelligence algorithm evolved from a previous proof-of-principle. We tested the technology on sEMG signals from five muscles...
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ژورنال
عنوان ژورنال: IEEE Transactions on Biomedical Engineering
سال: 2015
ISSN: 0018-9294,1558-2531
DOI: 10.1109/tbme.2014.2368514