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MYOELECTRIC SIGNAL ESTIMATION DEVICE, MYOELECTRIC SIGNAL ESTIMATION METHOD, AND PROGRAM

机译:肌电信号估计装置,肌电信号估计方法和程序

摘要

To provide a myoelectric signal estimation device, a myoelectric signal estimation method and a program in which other muscle activities can be estimated from myoelectric signals of muscles becoming measurement targets where multiple myoelectric signals are mixed, without increasing the number of electrodes to adhere to the muscle surface.SOLUTION: Regression equations (M1, M2) are derived from feature values R(Ac, Lc, Lc) measured by a myoelectric signal measuring device 20 filtered for every parameter, and myoelectric estimated signals (Sv, Sv) are calculated by using the regression equations (M1, M2) and the feature values R(Av). The highest correlation coefficients (r, r) are calculated from the calculated signals Sv (Sv, Sv) and the feature values R(Lv, Lv), and the parameters and the regression equations (M1, M2) capable of obtaining the correlation coefficients (r, r) are selected and stored in the parameter DB13d and the myoelectric signal regression model DB13f.SELECTED DRAWING: Figure 3
机译:为了提供一种肌电信号估计装置,一种肌电信号估计方法和程序,其中可以从成为混合多个肌电信号的测量目标的肌肉的肌电信号中估计其他肌肉活动,而无需增加粘附到肌肉上的电极的数量。解决方案:回归方程(M1,M2)从针对每个参数过滤的肌电信号测量设备20测量的特征值R(Ac,Lc,Lc)得出,肌电估计信号(Sv,Sv)通过使用回归方程(M1,M2)和特征值R(Av)。根据计算出的信号Sv(Sv,Sv)和特征值R(Lv,Lv)以及能够获得相关系数的参数和回归方程(M1,M2)计算出最高相关系数(r,r)选择(r,r)并将其存储在参数DB13d和肌电信号回归模型DB13f中.SELECTED DRAWING:图3

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