Detection method for high-density-or-multichannel-electromyographic-signal muscle activation onsets

Abstract

The invention relates to a detection method for high-density-or-multichannel-electromyographic-signal muscle activation onsets. The method includes the steps that based on statistical information, activation threshold values of all channel electromyographic signals are determined; then an onset of firstly activating a channel serves as a standard, and muscle activation onsets of other channels areassigned in two following time windows; all the channel onsets are divided into three classes with the clustering algorithm; influences of local muscle malfunctions and external disturbance are eliminated, and whether muscles are activated or not and corresponding activation onsets are determined. According to the detection method for the high-density-or-multichannel-electromyographic-signal muscle activation onsets, through correlations between all the channels in high-density or multichannel electromyographic signals, whether the muscles are activated or not and corresponding activation onsets are accurately judged from the high-density or multichannel electromyographic signals in real time.

Description

technical field [0001] The invention relates to the field of physiological electrical signal detection, in particular to a method for detecting the starting point of muscle activation of high-density or multi-channel electromyographic signals. Background technique [0002] The joints of the human body rely on muscle contraction to ensure limb behavior. The brain issues instructions, and the muscles respond through nerve conduction, changing from a resting state to an active state, and electromyographic signals can be detected through electrodes. EMG signals are derived from the action potentials of the nerves that control muscle contraction, which reflect the subjective movement intention of the human body as well as the activation and contraction characteristics of the muscles, and are widely used in the fields of intelligent rehabilitation training equipment and rehabilitation assessment. [0003] Human joint activities are completed by the cooperation of multiple muscles....

AI Technical Summary

Problems solved by technology

These two high-density or multi-channel muscle activation detection methods are easy to make misjudgments on local muscle malfunctions and external interference, with low accuracy and poor real-time performance.

However, there is a correlation between the channels of the high-density or multi-channel EMG signal, and these two methods do not consider the correlation between the channels in the EMG signal.

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