首页> 外文期刊>Journal of electromyography and kinesiology: Official journal of the International Society of Electrophysiological Kinesiology >Variability of estimates of muscle fiber conduction velocity and surface EMG amplitude across subjects and processing intervals
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Variability of estimates of muscle fiber conduction velocity and surface EMG amplitude across subjects and processing intervals

机译:跨对象和处理间隔的肌肉传导速度和表面EMG幅度的估计变异性

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摘要

The force developed by the human neuromuscular system can change very rapidly (15-50 ms). When processing EMG signals for inferring neural control strategies, it is therefore necessary to extract estimates from short time intervals. In this study, we investigate the relation between joint torque and estimates of average muscle fibre conduction velocity (MFCV) and amplitude (RMS) from surface EMG signals, when varying the duration of the processing interval. Moreover, we assessed the inter-subject variability in RMS and MFCV estimates. Ten healthy subjects performed isometric linearly increasing ankle dorsiflexion contractions up to 70% MVC at a rate of 5% MVCs-1. High-density EMG signals were recorded from the tibialis anterior muscle and MFCV and RMS were estimated in eight time-intervals ranging from 15 to 2000 ms. MFCV and RMS were significantly correlated with force in all subjects and when using all time-intervals (MFCV = 0.77 +/- 0.07, RMS = 0.79 +/- 0.06 (R-2), Pearson-P 0.01). The variability around the regression line for both MFCV and RMS estimates significantly increased when using intervals 100 ms (P 0.001). However, the slope of the regression between EMG variables and force did not change with the duration of the interval (P 0.001). Moreover, MFCV showed a substantially smaller variability across subjects in its relation to force than RMS [average coefficient of variation of regression slopes across all time intervals, 24.48 +/- 1.51 (%), whilst for the RMS it was 56.65 +/- 0.69 (%)]. These results indicate that estimates of MFCV and RMS as a function of joint torque are unbiased with respect to processing interval duration. Moreover, they reveal that estimates of MFCV are more consistent across subjects than EMG amplitude.
机译:由人类神经肌肉系统开发的力可以很快地变化(15-50毫秒)。在处理EMG信号时,用于推断神经控制策略,因此有必要从短时间间隔中提取估计。在这项研究中,在改变处理间隔的持续时间的情况下,我们研究了与表面EMG信号之间的关节扭矩与平均肌纤维传导速度(MFCV)和幅度(RMS)之间的关系。此外,我们评估了RMS和MFCV估计中的对象间变异性。十个健康的受试者以5%MVCS-1的速率进行等距线性增加脚踝背屈收缩至70%MVC。从胫骨前肌肌记录高密度EMG信号,MFCV和RMS以15至2000ms的8个时间间隔估计。 MFCV和RMS与所有受试者的力显着相关,并且当使用所有时间间隔时(MFCV = 0.77 +/- 0.07,RMS = 0.79 +/- 0.06(R-2),Pearson-P <0.01)。使用间隔时,MFCV和RMS估计的回归线周围的变化显着增加。 100 ms(P <0.001)。然而,EMG变量与力之间的回归的斜率在间隔的持续时间(P <0.001)之间没有变化。此外,MFCV在其关系中显示了与力的关系的显着较小的变异性,而不是RMS的[回归斜率的平均变化系数,在所有时间间隔,24.48 +/- 1.51(%),而RMS为56.65 +/- 0.69 (%)]。这些结果表明,作为关节扭矩的函数的MFCV和RMS的估计是关于处理间隔持续时间的偏差。此外,他们揭示了对受试者的MFCV的估计比EMG幅度更一致。

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