Method for continuously estimating angle of human joint on basis of surface electromyographic signal

Abstract

The invention belongs to the field of human-computer interaction and discloses a method for continuously estimating the angle of a human joint on the basis of a surface electromyographic signal. The method comprises the following steps that a, a joint part of an object to be predicted is selected, and the electromyographic signal and a joint angle signal of the joint part are collected; b, the collected electromyographic signal and the joint angle signal are preprocessed separately; c, according to the preprocessed electromyographic signal and joint angle signal, a sparse pseudo-input Gaussianprocess regression algorithm is used for constructing a prediction model of the electromyographic signal and joint angle signal; d, the real-time electromyographic signal of the object to be predicted is put into the prediction model to obtain the desired joint angle signal. By means of the method, the surface electromyographic signal is mapped to the motion of the joint angle continuously, the real-time performance of continuous estimation is ensured, the prediction accuracy is improved, and the computational complexity is reduced.

Description

technical field [0001] The invention belongs to the field of human-computer interaction, and more specifically relates to a method for continuously estimating the joint angle of a human body based on surface electromyographic signals. Background technique [0002] "Human-computer natural interaction" as an important component module has attracted people's attention. Human surface electromyography (sEMG) can be used as a human body because it is easy to collect, contains information about human motion intentions, and its signal generation is ahead of motion. The interface of computer interaction is used to realize the natural interaction between human and computer. Current commercial devices that use surface electromyography signals as human-machine interfaces are usually limited in range of motion, sensory feedback, and limited functions in intuitive control. Although the mechanical structure of the device has multiple degrees of freedom and can complete flexible actions, it...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a method for continuously estimating joint angles based on surface electromyographic signals, by using a sparse pseudo-input Gaussian process regression algorithm to construct a mapping model between electromyographic signals and human joint angles, Realize the movement of the surface electromyographic signal mapped to the joint angle in a continuous manner to ensure the real-time performance of the continuous estimation method, thus solving the technical problems of low prediction accuracy, poor real-time performance and complex calculation of the continuous estimation method

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