VARIATION OF INSTANTANEOUS SPECTRAL CENTROID ACROSS BANDS OF SURFACE ELECTROMYOGRAPHIC SIGNALS

Divya Bharathi Krishnamani, Non-Invasive Imaging, P. Karthick, R. Swaminathan
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Abstract

Surface electromyography (sEMG) is a technique which noninvasively acquires the electrical activity of muscles and is widely used for muscle fatigue assessment. This study attempts to characterize the dynamic muscle fatiguing contractions with frequency bands of sEMG signals and a geometric feature namely the instantaneous spectral centroid (ISC). The sEMG signals are acquired from biceps brachii muscle of fifty-eight healthy volunteers. The frequency components of the signals are divided into low frequency band (10-45Hz), medium frequency band (55-95Hz) and high frequency band (95-400Hz). The signals associated with these bands are subjected to a Hilbert transform and analytical shape representation is obtained in the complex plane. The ISC feature is extracted from the resultant shape of the three frequency bands. The results show that this feature can differentiate the muscle nonfatigue and fatigue conditions (p<0.05). It is found the values of ISC is lower in fatigue conditions irrespective of frequency bands. It is also observed that the coefficient of variation of ISC in the low frequency band is less and it demonstrates the ability of handling inter-subject variations. Therefore, the proposed geometric feature from the low frequency band of sEMG signals could be considered for detecting muscle fatigue in various neuromuscular conditions.
表面肌电信号波段瞬时谱质心的变化
表面肌电图(sEMG)是一种无创获取肌肉电活动的技术,被广泛用于肌肉疲劳评估。本研究试图用表面肌电信号的频带和瞬时谱质心(ISC)的几何特征来表征动态肌肉疲劳收缩。从58名健康志愿者的肱二头肌获取表面肌电信号。信号的频率成分分为低频(10-45Hz)、中频(55-95Hz)和高频(95-400Hz)。对与这些波段相关的信号进行希尔伯特变换,得到复平面上的解析形状表示。ISC特征是从三个频带的合成形状中提取的。结果表明,该特征可以区分肌肉非疲劳状态和疲劳状态(p<0.05)。结果表明,在不同频带的疲劳状态下,ISC值均较低。ISC在低频段的变异系数较小,显示了处理学科间变异的能力。因此,可以考虑从表面肌电信号的低频波段提取几何特征来检测各种神经肌肉状态下的肌肉疲劳。
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