Human upper limb muscle state monitoring system based on surface electromyogram signals and judging method thereof

Abstract

The invention discloses a human upper limb muscle state monitoring system based on surface electromyogram signals and a judging method thereof. The monitoring system comprises a signal collection module, a signal processing module and a mode classifying module, wherein the signal collection module is used for collecting human upper limb surface electromyogram signals and converting the human upper limb surface electromyogram signals into digital signals; the signal processing module is used for preprocessing the digital signals and extracting features; the mode classifying module is used for identifying input feature vectors, outputting types of the feature vectors and judging the upper limb muscle state. The judging method comprises the following steps: collecting human surface electromyogram signals via the signal collection module; processing the human surface electromyogram signals via the signal processing module; and identifying modes of the human surface electromyogram signals via the mode classifying module. Through the adoption of the scheme, effective electromyogram signals are efficiently extracted and are accurately analyzed and processed; the cost is reduced; the calculation quantity is greatly reduced; the real-time performance of the system is improved; the system has a high application value in the market.

Description

technical field [0001] The invention relates to the field of medical detection, in particular to a monitoring system and judging method for human upper limb muscle state based on surface electromyography signals. Background technique [0002] Surface electromyography (sEMG) is the electrical potential measured at the skin surface of the muscle. Through the processing of amplification, filtering and sampling, the sEMG can be adjusted to a suitable data segment, and then feature extraction can be performed using data processing technology. Using the classifier to perform pattern recognition on the extracted features can determine the state of human muscles, including what kind of action the muscles are performing and whether the muscles are in a state of fatigue. To determine what kind of action the muscles are performing, the exoskeleton device can be controlled through sEMG. It is also possible to use virtual reality technology to control the equipment in the virtual scene...

AI Technical Summary

Problems solved by technology

However, the invention collects EMG signals and EEG signals at the same time, which not only increases the cost, but also increases the amount of calculation, which affects the real-time performance of the system's online recognition.

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