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A Neurophysiological Pattern as a Precursor of Work-Related Musculoskeletal Disorders Using EEG Combined with EMG

机译:作为使用EEG联合EG的工作相关的肌肉骨骼疾病的前兆作为与EMG相结合的神经生理学模式

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摘要

We aimed to determine the neurophysiological pattern that is associated with the development of musculoskeletal pain that is induced by biomechanical constraints. Twelve (12) young healthy volunteers (two females) performed two experimental realistic manual tasks for 30 min each: (1) with the high risk of musculoskeletal pain development and (2) with low risk for pain development. During the tasks, synchronized electroencephalographic (EEG) and electromyography (EMG) signals data were collected, as well as pain scores. Subsequently, two main variables were computed from neurophysiological signals: (1) cortical inhibition as Task-Related Power Increase (TRPI) in beta EEG frequency band (β.TRPI) and (2) muscle variability as Coefficient of Variation (CoV) from EMG signals. A strong effect size was observed for pain measurement under the high risk condition during the last 5 min of the task execution; with muscle fatigue, because the CoV has decreased below 18%. An increase in cortical inhibition (β.TRPI >50%) was observed after the 5th min of the task in both experimental conditions. These results suggest the following neurophysiological pattern—β.TRPI ≥ 50% and CoV ≤ 18%—as a possible indicator to monitor the development of musculoskeletal pain in the shoulder in the context of repeated and prolonged exposure to manual tasks.
机译:我们旨在确定与生物力学限制诱导的肌肉骨骼疼痛的发展有关的神经生理学模式。十二(12)年轻健康志愿者(两名女性)每次进行两次实验现实手工任务30分钟:(1)肌肉骨骼疼痛发展的高风险和(2)疼痛发展风险低。在任务期间,收集同步脑电图(EEG)和肌电图(EMG)信号数据以及疼痛分数。随后,从神经生理信号计算两个主要变量:(1)作为任务相关的功率增加(TRPI)在β脑电图频带(β.TRPI)和(2)肌变异系数(COV)的肌肉变异性(COV)的肌肉变异性信号。在任务执行的最后5分钟期间,在高风险条件下观察到强烈的效果大小;有肌肉疲劳,因为COV减少了低于18%。在两种实验条件下任务的第5分钟后观察到皮质抑制(β.TRPI> 50%)的增加。这些结果表明以下神经生理学模式-β.TRPI≥50%和COV≤18% - 在重复和长时间接触手动任务的情况下监测肩膀中肌肉骨骼疼痛的发育的可能指标。

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