Lowery M, Nolan P, O'Malley M
Department of Electronic and Electrical Engineering, University College Dublin, 4, Dublin, Ireland.
J Electromyogr Kinesiol. 2002 Apr;12(2):111-8. doi: 10.1016/s1050-6411(02)00004-4.
Changes in the median frequency of the power spectrum of the surface electromyogram (EMG) are commonly used to detect muscle fatigue. Previous research has indicated that changes in the median frequency are related to decreases in muscle fibre conduction velocity (MFCV) during sustained fatiguing contractions. However, in experimental studies the median frequency has been consistently observed to decrease by a relatively greater amount than MFCV. In this paper, a new estimate of EMG frequency compression, the Spectral Compression Estimate (SCE), is compared with the median frequency of the EMG power spectrum, the median frequency of the EMG amplitude spectrum and MFCV measured during sustained, isometric, fatiguing contractions of the brachioradialis muscle at 30, 50 and 80% maximum voluntary contraction (MVC). The SCE is found to provide a better estimate of the observed changes in MFCV than the median frequency of either the EMG power spectrum or EMG amplitude spectrum.
表面肌电图(EMG)功率谱的中位数频率变化通常用于检测肌肉疲劳。先前的研究表明,在持续的疲劳收缩过程中,中位数频率的变化与肌纤维传导速度(MFCV)的降低有关。然而,在实验研究中,一直观察到中位数频率的下降幅度比MFCV相对更大。在本文中,将肌电图频率压缩的一种新估计方法,即频谱压缩估计(SCE),与在肱桡肌进行30%、50%和80%最大自主收缩(MVC)的持续等长疲劳收缩过程中测量的肌电图功率谱中位数频率、肌电图幅度谱中位数频率以及MFCV进行了比较。结果发现,与肌电图功率谱或肌电图幅度谱的中位数频率相比,SCE能更好地估计观察到的MFCV变化。