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Can Surface EMG Be Adequately Described by Digital Sampling?

机译：数字采样能否充分描述表面肌电图？

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摘要

Surface electromyography (SEMG) is a common tool to evaluate muscle function in kinesiological studies, musculoskeletal rehabilitation, prosthetics, clinical research and neurological disease diagnosis. The acquisition of SEMG is a crucially basic issue to gain an insight into musculoskeletal system function. The aim of this study is to investigate if the sampled surface EMG signals can reflect adequately the neural activity of the underlying musculature. The surface EMG signals of four muscles (abductor pollicis muscles and abductor digiti minimi muscles of right hand and left hand) are studied on the amplitude, frequency and nonlinear measure based on symplectic geometry. There are obvious differences in nonlinear measures of the different sampled signals, although there are little significant changes in their amplitude and frequency measures. Meanwhile, surface EMG signals obviously differ from their surrogate data at higher sampling frequencies. The results indicate that surface EMG signals contain nonlinear components. To gather the sufficient information of surface EMG signal, the data acquisition should be required at the higher sampling frequency. Furthermore, the nonlinear measure based on symplectic geometry can be used as a sensitive index for evaluation of the activity of the human muscles.
机译：表面肌电图（SEMG）是在运动学，肌肉骨骼康复，修复，临床研究和神经系统疾病诊断中评估肌肉功能的常用工具。 SEMG的收购是了解肌肉骨骼系统功能的至关重要的基本问题。这项研究的目的是调查所采样的表面肌电信号是否可以充分反映潜在肌肉组织的神经活动。研究了四种肌肉（右手和左手的外展肌和小指外展肌）的表面肌电信号，在振幅，频率和基于辛几何的非线性测量中进行了研究。尽管它们的幅度和频率测量几乎没有显着变化，但不同采样信号的非线性测量存在明显差异。同时，在较高的采样频率下，表面肌电信号明显不同于其替代数据。结果表明表面肌电信号包含非线性成分。为了收集表面肌电信号的足够信息，应该在较高的采样频率下进行数据采集。此外，基于辛几何的非线性测量可以用作评估人体肌肉活动的敏感指标。

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