Department of Applied Sciences, Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada.
Laboratoire de Recherche Biomécanique et Neurophysiologique en Réadaptation Neuro-Musculo-Squelettique (Lab BioNR), Université du Québec à Chicoutimi (UQAC), Chicoutimi, QC G7H 2B1, Canada.
Int J Environ Res Public Health. 2021 Feb 19;18(4):2001. doi: 10.3390/ijerph18042001.
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.
我们旨在确定与生物力学限制引起的肌肉骨骼疼痛发展相关的神经生理模式。12 名（12 名）年轻健康志愿者（2 名女性）分别进行了两项实验性实际手动任务，每项任务持续 30 分钟：（1）具有肌肉骨骼疼痛发展高风险，（2）具有低风险。在任务期间，同步采集了脑电图（EEG）和肌电图（EMG）信号数据以及疼痛评分。随后，从神经生理信号中计算出两个主要变量：（1）皮质抑制作为任务相关功率增加（TRPI）在β脑电频率带（β.TRPI），（2）肌肉变异性作为肌电图信号的变异系数（CoV）。在任务执行的最后 5 分钟内，高风险条件下的疼痛测量值表现出很强的效应大小；由于肌肉疲劳，CoV 下降到 18%以下。在两种实验条件下，在任务的第 5 分钟后观察到皮质抑制增加（β.TRPI >50%）。这些结果表明，β.TRPI≥50%和 CoV≤18%的神经生理模式可能是监测重复性和长时间暴露于手动任务引起的肩部肌肉骨骼疼痛发展的指标。
