A method of Gait phase prediction using linear interpolation in the process of Gait phase recognition by the user adaptive classification based on sEMG signal

摘要

The present invention relates to a walking step prediction method using a linear interpolation in a walking step recognition process that recognizes a walking step using an EMG signal-based classifier using adaptive features and channel selection for improving accuracy. (A5) Calculating an average time required for each walking step using training data; (d1) calculating a correction value using a difference between a required time required for walking from the previous walking to the current walking to the current walking and the actual required time; (d2) calculating a predictive correction time of the current walking step using the correction value; And (d3) estimating the time required for the next walking step using the correction value, the average time taken by the walking step, and the average time from the previous walking to the current walking, As shown in Fig. By correcting the time of the walking step more accurately by the correction by the linear interpolation method, the recognition rate of the walking step can be improved, the walking step can be more accurately recognized, and the power will is more accurately controlled .