Method for predicting lower limb joint angles on basis of electromyography wavelet correlation dimensions

Abstract

The invention relates to a method for predicting lower limb joint angles on the basis of electromyography wavelet correlation dimensions. The method includes acquiring surface electromyography signalsfrom related muscle groups of the lower limbs of human bodies and determining action signal sections of the surface electromyography signals by the aid of energy thresholds; carrying out wavelet denoising on the surface electromyography signals of the action signal sections to obtain effective surface electromyography signals; carrying out wavelet multi-scale decomposition on the effective surface electromyography signals, extracting low-frequency coefficients of each layer, and further computing correlation dimensions of the low-frequency coefficients of each layer; combining the low-frequency coefficients and correlation dimension numbers with one another, computing wavelet correlation dimension coefficient features of the effective surface electromyography signals, and inputting the features into prediction networks; dividing extracted electromyography signals into training sets and test sets and extracting features according to processes; training networks by the training sets, and then verifying the prediction accuracy by the test sets. The method has the advantages that as shown by experimental results, the method is high in human body lower limb movement knee joint angle prediction rate, and prediction results of the method are superior to prediction results of other prediction methods.

Description

technical field [0001] The invention belongs to the field of pattern recognition, and relates to a pattern recognition method based on electromyographic signals, in particular to a method for predicting joint angles of human lower limbs based on wavelet correlation dimension features of electromyographic signals. Background technique [0002] Patients with spinal cord injury (spinal cord injury SCI) refer to those who have lost their motor function due to nerve damage, and their postoperative rehabilitation treatment has a long way to go. Rehabilitation training using passive methods such as treadmills and knee extension and flexion is a traditional treatment method, but the therapeutic effect of this method is limited. Practice has proved that active training can improve the reorganization of the cerebral cortex, which is conducive to the recovery of neurons in patients. The traditional human-computer interaction system based on program control restricts the development of...

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Problems solved by technology

However, the model has a complex structure and contains many physiological parameters that cannot be directly measured

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