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Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction

机译:动态收缩期间基于特征分析的肌电信号激活与时滞之间的关系

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摘要

This study examined the effects of electromyographic (EMG) signals from Biceps Brachii (BB) muscle on the root mean square (RMS)-time relationships during dynamic contraction. Ten healthy and right hand dominated male subjects were volunteered for the experiments. The RMS features were extracted from the corresponding EMG signals (amplitude of the full wave EMG) for 10 seconds in 5 minutes intervals between each trial. Ten seconds (or 10000 ms) were divided into 4 time lags to identify the muscle activity and relationship between EMG and time using different statistical analysing techniques, such as mean, regression analysis, correlation, ANOVA, and coefficient of variation (CoV) for muscle activity variation. The results shows that large positive linear association between EMG and endurance time where the points are close to the linear trend line (R squared = 0.93 and F-ratio = 453.1). Signal steadiness is better during last time lags (1.66% during 7501–10000 ms) compared to initial time duration (10.35% during 0–2500 ms).
机译:这项研究检查了动态收缩过程中肱二头肌(BB)肌电图(EMG)信号对均方根(RMS)-时间关系的影响。十名健康且右手支配的男性受试者被自愿参加实验。在每次试验之间的5分钟间隔内,从相应的EMG信号(全波EMG的幅度)提取RMS特征10秒钟。使用不同的统计分析技术(例如均值,回归分析,相关性,ANOVA和肌肉变异系数(CoV)),将十秒(或10000毫秒)分为4个时滞,以识别肌肉活动以及EMG与时间之间的关系。活动变化。结果表明,EMG与耐力时间之间存在较大的正线性关联,其中点接近线性趋势线(R平方= 0.93,F比​​= 453.1)。与初始持续时间(0-2500 ms期间为10.35%)相比,在最后的时间延迟(7501–10000 ms期间为1.66%)时的信号稳定性更好。

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