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Patterns of motor recruitment can be determined using surface EMG

机译:可以使用表面肌电图确定运动恢复的模式

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Previous studies have reported how different populations of motor units (MUs) can be recruited during dynamic and locomotor tasks. It was hypothesised that the higher-threshold units would contribute higher-frequency components to the sEMG spectra due to their faster conduction velocities, and thus recruitment patterns that increase the proportion of high-threshold units active would lead to higher-frequency elements in the sEMG spectra. This idea was tested by using a model of varying recruitment coupled to a three-layer volume conductor model to generate a series of sEMG signals. The recruitment varied from (A) orderly recruitment where the lowest-threshold MUs were initially activated and higher-threshold MUs were sequentially recruited as the contraction progressed, (B) a recurrent inhibition model that started with orderly recruitment, but as the higher-threshold units were activated they inhibited the lower-threshold MUs (C) nine models with intermediate properties that were graded between these two extremes. The sEMG was processed using wavelet analysis and the spectral properties quantified by their mean frequency, and an angle 0 that was determined from the principal components of the spectra. Recruitment strategies that resulted in a greater proportion of faster MUs being active had a significantly lower theta and higher mean frequency.
机译:先前的研究报告了在动态和运动任务期间如何招募不同数量的运动单位(MU)。假设较高的阈值单元由于其更快的传导速度而将对sEMG频谱贡献较高的频率分量,因此增加活动的高阈值单元比例的募集模式将导致sEMG中的高频元素光谱。通过使用变动募集模型与三层体导体模型耦合以生成一系列sEMG信号,对该想法进行了测试。募集的方式有所不同(A)有序募集,其中最低阈值的MUs最初被激活,而更高阈值的MUs随着收缩的进展而被依次募集,(B)从有序募集开始但以更高阈值开始的复发抑制模型单位被激活,它们抑制了具有中间属性的较低阈值MU(C)九个模型,这些模型的等级介于这两个极端之间。使用小波分析对sEMG进行处理,并通过其平均频率和从光谱的主要成分确定的角​​度0来量化光谱特性。导致较大比例的更快MU处于活动状态的招聘策略的theta值明显较低,而平均频率较高。

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