Laboratory of Biomechanics & Biocalorimetry, University of Basel, c/o Biozentrum/Pharmazentrum, Klingelbergstrasse 50-70, CH-4056 Basel, Switzerland.
J Neurosci Methods. 2011 Sep 30;201(1):27-34. doi: 10.1016/j.jneumeth.2011.07.008. Epub 2011 Jul 18.
The dynamic interplay between muscles surrounding the knee joint, the central nervous system and external factors require a control strategy to generate and stabilise the preferred gait pattern. The electromyographic (EMG) signal is a common measure reflecting the neuromuscular control strategies during dynamic tasks. Neuromuscular control mechanisms, found in processed EMG signals, showed a precise pacing with a pacing rhythm and a tight control of muscle activity in running and maximally contracted muscles. The purpose of this study was to provide an insight how muscles get activated during walking. The EMG power, extracted by the wavelet transform (92-395Hz), over a time period encompassing 250ms before and 250ms after heel strike was analysed. The study showed that the wavelet-based analysis of EMG signals was sufficiently sensitive to detect a synchronisation of the activation of thigh muscles while walking. The results within each single subject and within the group consisting of 10 healthy females showed that, although there was a lot of jitter in the locations of the intensity peaks, the muscle activation is controlled, on average, by a neuromuscular activity paced at about 40ms, however with variable amplitudes. Albeit the jitter of the signal, the results resolved the temporal dependency of intensity peaks within muscles surrounding the knee and provided an insight into neural control of locomotion. The methodology to assess the stabilising muscle activation pattern may provide a way to discriminate subjects with normal gait pattern form those with a deteriorated neuromuscular control strategy.
膝关节周围的肌肉、中枢神经系统和外部因素之间的动态相互作用需要一种控制策略来产生和稳定首选的步态模式。肌电图（EMG）信号是反映动态任务中神经肌肉控制策略的常用指标。在跑步和最大收缩肌肉中，处理后的 EMG 信号中发现的神经肌肉控制机制表现出精确的起搏、起搏节律和肌肉活动的紧密控制。本研究的目的是提供对肌肉在行走过程中如何被激活的深入了解。在足跟着地前 250ms 和后 250ms 期间，通过小波变换（92-395Hz）提取的 EMG 功率进行了分析。研究表明，基于小波的 EMG 信号分析足以检测到行走时大腿肌肉激活的同步。在每个个体内和由 10 名健康女性组成的组内的结果表明，尽管强度峰值的位置存在很多抖动，但肌肉激活平均受到大约 40ms 神经肌肉活动的控制，尽管幅度不同。尽管信号存在抖动，但结果解决了膝关节周围肌肉中强度峰值的时间依赖性，并深入了解了运动的神经控制。评估稳定肌肉激活模式的方法可能为区分具有正常步态模式和神经肌肉控制策略恶化的受试者提供一种途径。
