METHOD FOR CLASSIFICATION OF MUSCULAR FATIGUE BASED ON ANALYSIS OF WAVELET TRANSFORMATION OF SEGMENTS OF MOTOR ACTIVITY OF ELECTROMYOSIGNAL Russian patent published in 2025 - IPC A61B5/00 

FIELD: medicine.

SUBSTANCE: present technical solution relates to the field of medical rehabilitation devices and robotics, in particular to methods and systems for controlling an exoskeleton in the rehabilitation of people with diseases leading to disorders of the musculoskeletal system and musculoskeletal system, as well as for use as human-machine interfaces of industrial exoskeletons. In a known method for assessing muscle fatigue, which consists in obtaining a sEMG signal from a muscle participating in a test functional test or a technological operation, its segmentation according to a certain rule, which enables to form a time sequence of segments, determination of the obtained segments for subsequent study of their energy evolution and constructing descriptors for a muscle fatigue classifier, for muscle fatigue stratification in the current period of the functional test, the wavelet plane of the sEMG segment corresponding to the motor activity interval in the current period of the functional test, and based on its analysis, two vectors of descriptors are formed, the first of which is determined by calculating the global entropy of wavelets in rows (scales) of the wavelet plane, and the second is determined by calculating the global entropy of wavelets in columns of the wavelet plane, wherein the second vector of descriptors includes only components that exceed a threshold value, which is set so that it takes the maximum value of the threshold, which does not lead to omission of indices within the remaining sequence of vector components.

EFFECT: reduction of error in classification of muscular fatigue levels by using machine learning models as classifiers.

3 cl, 10 dwg