予測誤差の幾何学的関係による表面筋電図解析
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概要
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It has been reported that the mode of muscle activity is concerned with the power spectrum pattern of surface electromyogram (EMG), in so far as the signal is steadily ergodic in the stochastic process. In this paper, a new deterministic method is proposed for characterization of the non-stationary EMG which varies dynamically in time. An AR (auto-regressive) model is suitable to explain the almost periodical EMG. When the parameters of this model are calculated by the least square estimate (LSE), it is important that the (i+1) th order of forward and the (i) th order of backward prediction error vectors be orthogonal to each other. Therefore, the non-stationariness of EMG is characterized from the looseness of the orthogonality, if these vectors at any interval are obtained as the outputs from the standard filter (SDF), which is defined in a stationary interval by the LSE. Practically, {JFBEO(i)}, which resembles the similarity function, is used for characterization. When an SDF was prepared with the masticatory EMG during the maximum clenching, decrease in the order of AR model appeared for 50%, 25% clenching. At the onset and the ending phase of EMG during the tapping movement, the order also decreased gradually toward the silent phase. The physiological meaning of the order has not yet been clarified, but this method may be useful to understanding the transition period of EMG, which is concerned with excitation and inhibition.
- 日本ME学会の論文
- 1986-04-00
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