Kiryu T, De Luca C J, Saitoh Y
Department of Information Engineering, Faculty of Engineering, Niigata University, Japan.
IEEE Trans Biomed Eng. 1994 Nov;41(11):1031-8. doi: 10.1109/10.335841.
We investigated the time-varying behaviour of the autoregressive (AR) parameters in a myoelectric (ME) signal detected during a linear force increasing contraction. The AR parameters of interest were the reflection coefficients, the AR model spectrum, and the prediction errors. We used well-conditioned ME signals for which the complete time record of the motor units firings was available. In addition, the influence of the recruitment of a new motor unit, the conduction velocity of action potentials, and additive broad-band noise were investigated using simulated ME signals. The simulated ME signals were constructed from a selected group of the available motor unit action potential trains. The results revealed that, as the contraction progressed, the AR parameters displayed a time-varying behavior which coincided with the recruitment of newly recruited motor units whose spectrum of the waveform differed from that of the rest of the ME signal. This property of the AR parameters was obscured by the presence of broad-band noise and low-amplitude motor unit action potentials, both of which are more pronounced during low-level force contractions.
我们研究了在肌肉等长收缩力逐渐增加过程中检测到的肌电（ME）信号中自回归（AR）参数的时变行为。感兴趣的AR参数包括反射系数、AR模型频谱和预测误差。我们使用了条件良好的ME信号，其运动单元放电的完整时间记录是可用的。此外，还使用模拟ME信号研究了新运动单元募集、动作电位传导速度和加性宽带噪声的影响。模拟ME信号由一组选定的可用运动单元动作电位序列构建而成。结果表明，随着收缩的进行，AR参数呈现出时变行为，这与新募集的运动单元的募集情况一致，这些新募集运动单元的波形频谱与ME信号的其余部分不同。AR参数的这一特性被宽带噪声和低幅度运动单元动作电位的存在所掩盖，这两者在低水平力收缩期间更为明显。
