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肌疲劳与恢复对间歇握力疲劳任务后神经肌肉网络的影响:脑电图和肌电图信号的频谱分析。

Effects of Muscle Fatigue and Recovery on the Neuromuscular Network after an Intermittent Handgrip Fatigue Task: Spectral Analysis of Electroencephalography and Electromyography Signals.

机构信息

Department of Physical Therapy and Assistive Technology, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan.

Biomechanics Research Laboratory, Department of Medical Research, MacKay Memorial Hospital, Taipei 25160, Taiwan.

出版信息

Sensors (Basel). 2023 Feb 22;23(5):2440. doi: 10.3390/s23052440.

Abstract

Mechanisms underlying exercise-induced muscle fatigue and recovery are dependent on peripheral changes at the muscle level and improper control of motoneurons by the central nervous system. In this study, we analyzed the effects of muscle fatigue and recovery on the neuromuscular network through the spectral analysis of electroencephalography (EEG) and electromyography (EMG) signals. A total of 20 healthy right-handed volunteers performed an intermittent handgrip fatigue task. In the prefatigue, postfatigue, and postrecovery states, the participants contracted a handgrip dynamometer with sustained 30% maximal voluntary contractions (MVCs); EEG and EMG data were recorded. A considerable decrease was noted in EMG median frequency in the postfatigue state compared with the findings in other states. Furthermore, the EEG power spectral density of the right primary cortex exhibited a prominent increase in the gamma band. Muscle fatigue led to increases in the beta and gamma bands of contralateral and ipsilateral corticomuscular coherence, respectively. Moreover, a decrease was noted in corticocortical coherence between the bilateral primary motor cortices after muscle fatigue. EMG median frequency may serve as an indicator of muscle fatigue and recovery. Coherence analysis revealed that fatigue reduced the functional synchronization among bilateral motor areas but increased that between the cortex and muscle.

摘要

运动引起的肌肉疲劳和恢复的机制取决于肌肉水平的外周变化和中枢神经系统对运动神经元的不当控制。在这项研究中,我们通过脑电图(EEG)和肌电图(EMG)信号的频谱分析来分析肌肉疲劳和恢复对神经肌肉网络的影响。共有 20 名健康的右利手志愿者进行了间歇性握力疲劳任务。在疲劳前、疲劳后和恢复后状态下,参与者用持续 30%最大自主收缩(MVC)收缩握力测力计;记录 EEG 和 EMG 数据。与其他状态相比,疲劳后 EMG 中频明显下降。此外,右侧初级皮层的 EEG 功率谱密度在伽马波段表现出明显增加。肌肉疲劳导致对侧和同侧皮质肌相干性的β和γ频段增加,而双侧初级运动皮层之间的皮质皮质相干性则降低。EMG 中频可作为肌肉疲劳和恢复的指标。相干性分析表明,疲劳降低了双侧运动区之间的功能同步性,但增加了皮层和肌肉之间的同步性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7277/10007140/4a4b870c7a09/sensors-23-02440-g001.jpg

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