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基于脑电图的频谱分析显示,在长时间间歇性运动任务中,脑电波变化与调节渐进性疲劳有关。

EEG-Based Spectral Analysis Showing Brainwave Changes Related to Modulating Progressive Fatigue During a Prolonged Intermittent Motor Task.

作者信息

Suviseshamuthu Easter S, Shenoy Handiru Vikram, Allexandre Didier, Hoxha Armand, Saleh Soha, Yue Guang H

机构信息

Center for Mobility and Rehabilitation Engineering Research, Kessler Foundation, West Orange, NJ, United States.

Department of Physical Medicine and Rehabilitation, Rutgers Biomedical Health Sciences, Newark, NJ, United States.

出版信息

Front Hum Neurosci. 2022 Mar 11;16:770053. doi: 10.3389/fnhum.2022.770053. eCollection 2022.

Abstract

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue comprising a central and peripheral component, which demands a gradually increasing effort. However, the brain contribution to the enhancement of effort to cope with progressing fatigue lacks a complete understanding. The intermittent motor tasks (IMTs) closely resemble many activities of daily living (ADL), thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects performing IMT until self-perceived exhaustion. Fourteen participants (median age 51.5 years; age range 26-72 years; 6 males) repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted ≈5 s with a 2-s rest between trials. The force, EEG, and surface EMG (from elbow joint muscles) data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency (TF) characteristics across the conditions. The outcome of channel- and source-level TF analyses reveals that the theta, alpha, and beta power spectral densities vary in proportion to fatigue levels in cortical motor areas. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post-contraction EEG data. The findings would enhance our understanding on the etiology and physiology of voluntary motor-action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks, evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies, and develop therapeutic strategies for restoring the patients' ability to participate in ADL by mitigating the central and muscle fatigue.

摘要

长时间反复进行次最大强度的运动任务会导致肌肉疲劳,这包括中枢和外周成分,需要逐渐增加努力程度。然而,大脑在增强努力以应对逐渐加重的疲劳方面所起的作用仍缺乏全面的了解。间歇性运动任务(IMT)与许多日常生活活动(ADL)非常相似,因此在研究疲劳方面仍具有生理相关性。因此,本研究的范围是调查健康受试者在进行IMT直至自我感觉精疲力竭时基于脑电图的大脑激活模式。14名参与者(年龄中位数51.5岁;年龄范围26 - 72岁;6名男性)按照示波器屏幕上显示的视觉提示,以最大自主收缩的40%重复进行肘部屈曲收缩,直至主观疲劳。每次收缩持续约5秒,两次试验之间休息2秒。同时收集力量、脑电图和表面肌电图(来自肘关节肌肉)数据。预处理后,我们在研究时段的开始、中间和结束时分别选择了一组试验,分别代表与轻度、中度和重度疲劳状况相关的大脑活动,以比较和对比不同状况下脑电图时频(TF)特征的变化。通道级和源级TF分析的结果表明,θ、α和β功率谱密度与皮质运动区域的疲劳程度成比例变化。我们从稳定期和收缩后脑电图数据中观察到,与分级疲劳相关的频段特异性频谱功率有统计学上的显著变化。这些发现将增进我们对与自愿运动动作相关疲劳的病因和生理学的理解,并为抵消与ADL相关的肌肉无力和运动耐力不足的感觉提供指导。该研究结果将有助于解释为什么某些患者在执行日常任务时会出现加剧的疲劳,评估诸如神经疾病和癌症治疗等临床状况在未来研究中如何改变疲劳背后的神经机制,并通过减轻中枢和肌肉疲劳来制定恢复患者参与ADL能力的治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/831e/8962200/09631b3e7b66/fnhum-16-770053-g0001.jpg

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