Miao T, Sakamoto K
Department of Communications and Systems, University of Electro-Communications, Tokyo, Japan.
Appl Human Sci. 1995 Jan;14(1):7-13. doi: 10.2114/ahs.14.7.
The propriety of the autoregressive (AR) method as a means of processing the signals of physiological tremor of human finger (finger tremor) was investigated. Application of the Akaike's criterion demonstrated that the 15-th order AR model was required to describe the recordings of finger tremor. According to Burg's algorithm, both AR spectrum and AR parameters were estimated to study the effects of various weight loads on finger tremor. It was found that, (1) the amplitude of AR spectrum was apparently enhanced by adding the load; (2) the first prediction coefficient (a1) and the first reflection coefficient (rho 1) significantly declined by increasing the weight loads. The results were compared with the calculations from FFT (Fast Fourier Transform) and autocorrelation function. Simple physical interpretation of the AR parameters (i.e. a1 and rho 1) was discussed in relation with system's resonant modes.
研究了自回归（AR）方法作为处理人类手指生理震颤信号（手指震颤）的一种手段的适用性。应用赤池准则表明，需要15阶AR模型来描述手指震颤的记录。根据伯格算法，估计了AR谱和AR参数，以研究各种重量负荷对手指震颤的影响。结果发现，（1）通过增加负荷，AR谱的幅度明显增强；（2）随着重量负荷的增加，第一预测系数（a1）和第一反射系数（rho 1）显著下降。将结果与快速傅里叶变换（FFT）和自相关函数的计算结果进行了比较。结合系统的共振模式，对手指震颤的AR参数（即a1和rho 1）进行了简单的物理解释。
