A gait recognition model building method based on myoelectric signals, a recognition method and a device

Abstract

The embodiment of the invention provides a gait recognition model building method based on myoelectric signals, a recognition method and a device. The model building method comprises the following steps of collecting the myoelectric signals; reducing the noise; adding a class tag and extract the following EMG signal characteristics: slope change rate, Willison amplitude, logarithm of variance, waveform length, and characteristics DB7-MAV; calculating the DBI index and SCAT index and obtaining the comprehensive evaluation results. The comprehensive evaluation result are randomly divided into atraining sample group and a test sample group according to a predetermined proportion, and input them into the LightGBM model for training and testing. The parameters in LightGBM model are adjusted according to the error of training set and test set, and grouped, trained, tested and adjusted repeatedly until the error of model test results accords with the data model of predetermined standard, andthe corresponding relationship between human gait type and comprehensive evaluation results is stored in the data model. The embodiment of the invention can efficiently and accurately establish a data model, and the gait recognition rate is high and the recognition result is more reliable.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of gait recognition, in particular to a method for establishing a gait recognition model based on electromyographic signals, a recognition method and a device. Background technique [0002] As an emerging application technology, biometric technology has been widely used in many aspects. The effective identification of human walking gait can better analyze and study human walking gait, which in turn can provide more reliable data support for competitive sports, fitness sports, bionic medical device research and other aspects. [0003] At present, the technology of walking gait recognition is mainly to identify and analyze the lower limb gait. The lower limb gait is the posture and state of the legs during the walking process of the human body, which has periodicity, continuity and repetition. features. In the process of human body movement, the time from one side of the heel to the gro...

AI Technical Summary

Problems solved by technology

At present, more recognition signals mainly include physical signals and electromyography signals (EMG). Physical signals generally use pressure signals and image signals. Gait, low cost, simple structure, but because the acquisition process of the physical signal occurs after the movement occurs, there is a certain hysteresis, so it has limitations

The electromyographic signal (EMG) occurs about 30ms to 80ms before the occurrence of muscle activity, which is very advanced and can predict the human muscle activity. However, the technical solution disclosed in the Chinese invention patent application No. 201510014792.2 Only the absolute mean and variance of the EMG signal are used as the eigenvalues, and the reliability of the obtained results is relatively low.

Images