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首页> 外文期刊>Muscle and Nerve >Decomposition-based quantitative electromyography: effect of force on motor unit potentials and motor unit number estimates.
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Decomposition-based quantitative electromyography: effect of force on motor unit potentials and motor unit number estimates.

机译：基于分解的定量肌电图：力对运动单位电位和运动单位数量估计的影响。

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摘要

Decomposition-based quantitative electromyography (DQEMG) allows for the collection of motor unit potentials (MUPs) over a broad range of force levels. Given the size principle of motor unit recruitment, it may be necessary to control for force when using DQEMG for the purpose of deriving a motor unit number estimate (MUNE). Therefore, this study was performed to examine the effect of force on the physiological characteristics of concentric needle- and surface-detected MUPs and the subsequent impact on MUNEs obtained from the first dorsal interosseous (FDI) muscle sampled using DQEMG. Maximum M waves were elicited in 10 subjects with supramaximal stimulation of the ulnar nerve at the wrist. Intramuscular and surface-detected EMG signals were collected simultaneously during 30-s voluntary isometric contractions performed at specific percentages of maximal voluntary contraction (MVC). Decomposition algorithms were used to identify needle-detected MUPs and their individual MU firing times. These MU firingtimes were used as triggers to extract their corresponding surface-detected MUPs (S-MUPs) using spike-triggered averaging. A mean S-MUP was then calculated, the size of which was divided into the maximum M-wave size to derive a MUNE. Increased levels of contraction had a significant effect on needle- and surface-detected MUP size, firing rate, and MUNE. These results suggest that force level is an important factor to consider when performing quantitative EMG, including MUNEs with this method.
机译：基于分解的定量肌电图（DQEMG）允许在很大的作用力范围内收集运动单位电位（MUP）。给定电机单元募集的规模原则，使用DQEMG得出电机单元数量估算值（MUNE）时可能需要控制力。因此，进行这项研究以检查力对同心针和表面检测到的MUP的生理特征的影响，以及随后对使用DQEMG采样的第一背骨（FDI）肌肉获得的MUNE的影响。在腕部尺神经受到最大刺激的情况下，在10位受试者中引起最大的M波。在以最大自愿收缩（MVC）的特定百分比执行的30秒钟自愿等距收缩期间，同时收集肌内和表面检测到的EMG信号。分解算法用于识别针头检测到的MUP及其各自的MU触发时间。这些MU触发时间用作触发信号，以使用尖峰触发平均值提取其对应的表面检测MUP（S-MUP）。然后计算平均S-MUP，将其大小分为最大M波大小以得出MUNE。收缩水平的提高对在针头和表面检测到的MUP大小，射速和MUNE有重大影响。这些结果表明，在执行定量肌电图（包括使用此方法的MUNE）时，力量水平是要考虑的重要因素。

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