Ma Heather T, Zhang Y T
Jockey Club Centre for Osteoporosis Care and Control, School of Public Health, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China.
J Neuroeng Rehabil. 2007 Aug 8;4:29. doi: 10.1186/1743-0003-4-29.
An important measure of the performance of a myoelectric (ME) control system for powered artificial limbs is the signal-to-noise ratio (SNR) at the output of ME channel. However, few studies illustrated the neuron-muscular interactive effects on the SNR at ME control channel output. In order to obtain a comprehensive understanding on the relationship between the physiology of individual motor unit and the ME control performance, this study investigates the effects of physiological factors on the SNR of single ME channel by an analytical and simulation approach, where the SNR is defined as the ratio of the mean squared value estimation at the channel output and the variance of the estimation.
Mathematical models are formulated based on three fundamental elements: a motoneuron firing mechanism, motor unit action potential (MUAP) module, and signal processor. Myoelectric signals of a motor unit are synthesized with different physiological parameters, and the corresponding SNR of single ME channel is numerically calculated. Effects of physiological multi factors on the SNR are investigated, including properties of the motoneuron, MUAP waveform, recruitment order, and firing pattern, etc.
The results of the mathematical model, supported by simulation, indicate that the SNR of a single ME channel is associated with the voluntary contraction level. We showed that a model-based approach can provide insight into the key factors and bioprocess in ME control. The results of this modelling work can be potentially used in the improvement of ME control performance and for the training of amputees with powered prostheses.
The SNR of single ME channel is a force, neuronal and muscular property dependent parameter. The theoretical model provides possible guidance to enhance the SNR of ME channel by controlling physiological variables or conscious contraction level.
用于动力假肢的肌电（ME）控制系统性能的一个重要指标是ME通道输出端的信噪比（SNR）。然而，很少有研究阐明神经元 - 肌肉相互作用对ME控制通道输出端信噪比的影响。为了全面了解单个运动单位的生理学与ME控制性能之间的关系，本研究通过分析和模拟方法研究生理因素对单个ME通道信噪比的影响，其中信噪比定义为通道输出端的均方值估计与估计方差之比。
基于三个基本要素建立数学模型：运动神经元放电机制、运动单位动作电位（MUAP）模块和信号处理器。用不同的生理参数合成运动单位的肌电信号，并数值计算单个ME通道的相应信噪比。研究了生理多因素对信噪比的影响，包括运动神经元的特性、MUAP波形、募集顺序和放电模式等。
数学模型的结果得到模拟的支持，表明单个ME通道的信噪比与自主收缩水平相关。我们表明基于模型的方法可以深入了解ME控制中的关键因素和生物过程。这项建模工作的结果可能用于改善ME控制性能以及训练使用动力假肢的截肢者。
单个ME通道的信噪比是一个与力、神经元和肌肉特性相关的参数。该理论模型为通过控制生理变量或有意识收缩水平来提高ME通道的信噪比提供了可能的指导。
