抄録
This paper proposes the CPG synergy model, which can generate rhythmic signals with nonstationary characteristics, to enable evaluation of rhythmic motions such as human finger tapping movements. The model consists of multiple central pattern generators (CPGs) that generates basic rhythm patterns, and can approximate nonstationary rhythmic signals, in which the waveform in each cycle of the signal drastically changes depending on time, by combining the basic rhythm patterns generated by the CPGs with weight coefficients and time-shift parameters. The validity of the proposed model was verified by numerical experiments for artificially generated rhythmic signals using multiple sinusoidal signals. Comparison experiments were then performed using the model parameters (i.e., basic rhythm patterns, weight coefficients and time-shift parameters) extracted from finger tapping movements performed by individuals in a healthy subject group and a Parkinson's disease patient group. The number of CPGs and the coefficients of variation of maximum weight coefficients showed significant differences between each group at the 0.1% level. These outcomes indicate that the proposed model has the potential to allow evaluation of abnormal movements in patients with motor function impairments.
