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Correlating motor unit morphology with bioelectrical activity - A simulation study

delete2018-01-01
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E
Ewa Zalewska *
I
I Hausmanowa-Pétrusewicz
DOI:10.1016/j.clinph.2017.11.003delete
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摘要

摘要

En 中文
Objectives: The aim was to determine motor unit morphology underpinning the various MUP waveforms using MUP analysis. Method: The simulation method is based on the decomposition of MUP into single fiber potentials. Number of fibers, fiber diameters and fiber to electrode distances were determined. The impact of each muscle fiber on the MUP waveform was determined and quantified by its percentage contribution. Results: The origin of the four examined MUPs of distinct waveforms have been explained by showing the histograms of fiber diameters and their distance to the electrode. In the case of a low amplitude MUP it was found that it originated from fibers of smaller than normal diameters with no dominant fiber. In another case of a MUP of short duration its shape was due to a single fiber close to the electrode which contributed to about 80% of the MUP. In case of polyphasic MUP, muscle fiber diameters variability was responsible for MUP characteristic. MUP from normal muscle originated from few fibers of similar diameters. Correlation between MUP's characteristic and morphological features has been indicated. Our findings are consistent with the neurophysiological knowledge about the origins of MUP. The approximation method enables MUP analysis that provides quantitative description of motor unit morphology. Conclusion: MUP analysis using an approximation method enables to get an insight into motor unit morphology and therefore increases understanding of the way the motor unit structure correlates with MUP waveform. (C) 2017 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Keyword:
EMG
Motor unit potentials
Simulation study
Neuromuscular disorders
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期刊

Clinical Neurophysiology 封面图
Clinical Neurophysiology
IF:
3.6
论文数:
9.3K
被引数:
2.1W

机构

P
Polish Academy of Sciences
学者数:
3.0W
论文数: 3.1W
被引数: 3.1W
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