Methods Inf Med - Detection algorithm for single motor unit firing in surface EMG of the trapezius muscle.

Tópicos

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Resumo

CKGROUND: Work-related musculoskeletal disorders (MSD) of the neck and the shoulders are a growing problem in society. An interesting pattern of spontaneous muscle activity, the firing of a single motor unit, in the trapezius muscle is observed during a laboratory study in a rest state or a state with a mental load.OBJECTIVE: In this study, we report on the finding of the single motor unit firing and we present a detection algorithm to localize these single motor unit firings.METHODS: A spike train detection algorithm, using a nonlinear energy operator and correlation, is presented to detect burst of highly correlated, high energetic spike-like segments.RESULTS: This single motor unit was visible in 65% of the test subjects on one or both trapezius muscles although there was no change in posture of the test subjects. All the segments in the data that were determined as single motor unit firings were detected by the algorithm.DISCUSSION: The physiological meaning of this firing pattern is a very low and subconscious contraction of the muscle. A long-term contraction could lead to the exhaustion of the muscle fibers, thus resulting in musculoskeletal disorders. The detection algorithm is able to localize this phenomenon in a sEMG measurement. The ability of detecting these firings is helpful in the research of its origin.CONCLUSION: The detection algorithm can be used to gain insight in the physiological origin of this phenomenon. In addition, the algorithm can also be used in a biofeedback system to warn the user for this undesired contraction to prevent MSD.

Resumo Limpo

ckground workrel musculoskelet disord msd neck shoulder grow problem societi interest pattern spontan muscl activ fire singl motor unit trapezius muscl observ laboratori studi rest state state mental loadobject studi report find singl motor unit fire present detect algorithm local singl motor unit firingsmethod spike train detect algorithm use nonlinear energi oper correl present detect burst high correl high energet spikelik segmentsresult singl motor unit visibl test subject one trapezius muscl although chang postur test subject segment data determin singl motor unit fire detect algorithmdiscuss physiolog mean fire pattern low subconsci contract muscl longterm contract lead exhaust muscl fiber thus result musculoskelet disord detect algorithm abl local phenomenon semg measur abil detect fire help research originconclus detect algorithm can use gain insight physiolog origin phenomenon addit algorithm can also use biofeedback system warn user undesir contract prevent msd

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