CN-121987225-A - Analog display method and system for electromyographic signals

CN121987225ACN 121987225 ACN121987225 ACN 121987225ACN-121987225-A

Abstract

The invention relates to the technical field of biomedical engineering and discloses a simulation display method and a simulation display system of an electromyographic signal, wherein the method comprises the steps of constructing a branching signal with retained time sequence association by carrying out channel analysis and synchronous verification on a mixed signal sequence; extracting envelope features from the signals, performing trend fitting correction to generate initial intensity distribution, constructing an interference distribution map based on cross-correlation analysis, determining an intensity correction value by using self-adaptive filtering and residual analysis, reversely reconstructing the signals by combining a tissue impedance model to restore real muscle activity distribution, mapping distribution data to a visual model, and generating a muscle activity image through interpolation and sharpening. The method can solve the problem of low accuracy of the visual image in the prior art.

Inventors

LUO YUANLONG
Zheng Tailong
YE MINGJIE
ZHU KANGXIANG
CHEN WEI
SHAO WANYING

Assignees

广州市施瑞医疗科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260127

Claims (9)

1. A simulation display method of electromyographic signals is characterized by comprising the steps of obtaining a mixed signal sequence, carrying out channel data analysis and time sequence synchronous verification on the mixed signal sequence, determining time sequence-related shunt electromyographic signals, carrying out full-wave rectification and moving average processing on the shunt electromyographic signals, carrying out linear interpolation after abnormal fluctuation points are identified by utilizing first-order difference, obtaining envelope characteristics of each channel, carrying out sliding window root mean square on the envelope characteristics, extracting unlabeled sections, carrying out least square fitting to obtain initial variation trend, carrying out numerical correction according to the initial variation trend, determining initial intensity distribution, carrying out cross-channel cross-correlation function operation on the initial intensity distribution, obtaining cross-correlation coefficient, identifying asynchronous interference components exceeding a synchronous fluctuation range, constructing an interference distribution map, identifying high-frequency noise areas in the interference distribution map, updating adaptive filter coefficients, outputting the interference noise components, constructing a dynamic superposition model based on the interference noise components, carrying out residual energy analysis, constructing a spatial mapping matrix according to the intensity combination electrode physical layout, carrying out inverse mapping on the preset tissue impedance, carrying out inverse mapping on the spatial mapping, carrying out inverse transformation on the spatial mapping, carrying out actual transformation, carrying out inverse transformation, and carrying out two-dimensional motion equalization, and carrying out dynamic transformation, and carrying out inverse transformation on the spatial transformation, and carrying out dynamic transformation.
2. The electromyographic signal simulation display method according to claim 1, wherein the method comprises the steps of obtaining a mixed signal sequence, carrying out channel data analysis and time sequence synchronous verification on the mixed signal sequence, determining a shunt electromyographic signal with retained time sequence association, obtaining the mixed signal sequence, writing the original amplitude into an independent channel buffer area corresponding to the channel identifier to obtain independent channel data, calculating a time sequence label deviation value of the independent channel data, generating synchronous verification bits based on the time sequence label deviation value, constructing independent signal streams subjected to time sequence verification, distributing physical storage addresses for the independent signal streams, generating independent data stream files, and carrying out aggregation on the independent data stream files to determine the shunt electromyographic signals.
3. The electromyographic signal simulation display method according to claim 1, wherein the step of performing full-wave rectification and moving average processing on the shunt electromyographic signal, and performing linear interpolation after identifying abnormal fluctuation points by utilizing first-order difference to obtain envelope characteristics of each channel comprises the steps of performing absolute value operation on the shunt electromyographic signal to generate full-wave rectification signals, performing moving window average calculation on the full-wave rectification signals to generate a preliminary envelope curve, calculating first-order difference of the preliminary envelope curve, positioning based on the first-order difference to obtain abnormal fluctuation points, replacing amplitude values at the abnormal fluctuation points by utilizing linear interpolation to generate smooth envelope sequences, analyzing the smooth envelope sequences, extracting local maxima and integral areas, and obtaining the envelope characteristics of each channel.
4. The electromyographic signal simulation display method according to claim 1, wherein the method comprises the steps of executing sliding window root mean square on the envelope feature, extracting unlabeled sections, performing least square fitting to obtain an initial variation trend, performing numerical correction according to the initial variation trend, determining initial intensity distribution, performing sliding window root mean square operation on the envelope feature to obtain a time-varying effective value, calculating an intensity variation gradient of the time-varying effective value, identifying continuous sections with amplitude and duration exceeding a preset interference threshold in the intensity variation gradient, determining an interference accumulation section, extracting unlabeled sections in the time-varying effective value, performing least square fitting to obtain an initial variation trend, performing numerical correction on the interference accumulation section by using the initial variation trend, generating corrected signal intensity, performing two-dimensional spatial mapping and smoothing on the corrected signal intensity, and determining the initial intensity distribution.
5. The electromyographic signal simulation display method according to claim 1, wherein the step of performing cross-channel cross-correlation function operation on the initial intensity distribution to obtain a cross-correlation coefficient, and identifying asynchronous interference components exceeding a synchronous fluctuation range by detecting a time lag offset of the cross-correlation coefficient to construct an interference distribution map comprises the steps of extracting each channel intensity sequence in the initial intensity distribution, aligning each channel intensity sequence with a time axis as a reference to construct a multi-channel time sequence signal, performing cross-correlation function operation on the multi-channel time sequence signal to generate the cross-correlation coefficient, detecting the time lag offset of the cross-correlation coefficient, intercepting corresponding signal features as asynchronous interference components if the time lag offset exceeds a preset synchronous fluctuation range, calculating interference weights according to the offset and duration of the asynchronous interference components, generating interference feature vectors according to the interference weights, and performing mapping projection and meshing processing on the interference feature vectors to obtain the interference distribution map.
6. The method for simulating and displaying the electromyographic signals according to claim 1, wherein the method for simulating and displaying the electromyographic signals is characterized by identifying a high-frequency noise region in the interference distribution diagram and updating a self-adaptive filter coefficient, outputting an interference noise component, constructing a dynamic superposition model based on the interference noise component and carrying out residual energy analysis, determining an intensity correction value, and comprises the steps of carrying out frequency domain transformation on the interference distribution diagram, detecting an aggregation region with frequency distribution exceeding a preset high-frequency threshold value, determining the high-frequency noise region, calculating an amplitude mean value and a duration of the high-frequency noise region, carrying out filtering coefficient updating operation on a preset self-adaptive filter according to the amplitude mean value and the duration, outputting an interference noise component, carrying out time sequence analysis on the interference noise component, extracting a periodic covering characteristic, constructing a dynamic superposition model, carrying out residual energy analysis on the dynamic superposition model, calculating the difference between a superposed signal and an expected signal, obtaining an intensity deviation value, and carrying out reverse compensation on the mixed signal sequence based on the intensity deviation value, thus obtaining the intensity correction value.
7. The simulation display method of the electromyographic signals according to claim 1 is characterized by comprising the steps of constructing a space mapping matrix according to the intensity correction value in combination with an electrode physical layout, performing inverse weighting compensation on an intensity mutation area in the space mapping matrix according to a preset tissue impedance model, reconstructing real activity distribution, wherein the method comprises the steps of obtaining a channel physical layout of an electrode array, constructing the space mapping matrix according to the intensity correction value and the channel physical layout, detecting the intensity mutation area in the space mapping matrix, calculating to obtain the conduction attenuation of the intensity mutation area according to the preset tissue impedance model, performing inverse weighting compensation on the space mapping matrix by using the conduction attenuation, analyzing an original point source intensity sequence, mapping the original point source intensity sequence to a predefined topological grid, generating a local activation area distribution map, and performing global aggregation on the local activation area distribution map to obtain real activity distribution.
8. The method for simulating and displaying electromyographic signals according to claim 1, wherein the steps of converting the real activity distribution into a two-dimensional numerical matrix, performing normalization mapping and downward rounding processing to generate an initial gray texture, performing spatial interpolation, equalization contrast adjustment and sharpening processing on the initial gray texture to generate a muscle activity image, comprise converting the real activity distribution into a two-dimensional numerical matrix, performing gray mapping on the two-dimensional numerical matrix to generate an initial gray texture map, performing interpolation processing on the initial gray texture map to construct a continuous gray surface model, performing equalization processing on the continuous gray surface model to adjust contrast to generate a pseudo-color rendering map, and performing sharpening processing on the pseudo-color rendering map to enhance edge definition to generate a muscle activity image.
9. The analog display system of the electromyographic signals is characterized by comprising a shunt processing module, a channel analysis module and a time sequence synchronization verification module, wherein the shunt processing module is used for acquiring a mixed signal sequence, carrying out channel data analysis and time sequence synchronization verification on the mixed signal sequence, and determining a shunt electromyographic signal associated with a reserved time sequence; the system comprises an envelope extraction module for performing full-wave rectification and moving average processing on the shunt electromyographic signals, performing linear interpolation after abnormal fluctuation points are identified by utilizing first-order difference to obtain envelope characteristics of each channel, an intensity distribution calculation module for performing sliding window root mean square, extracting unmarked sections and performing least square fitting on the envelope characteristics to obtain initial variation trend, performing numerical correction according to the initial variation trend to determine initial intensity distribution, an interference detection module for performing cross-channel cross-correlation function operation on the initial intensity distribution to obtain cross-correlation coefficients, identifying asynchronous interference components exceeding a synchronous fluctuation range by detecting time-lag offset of the cross-correlation coefficients to construct an interference distribution map, a filtering correction module for identifying high-frequency noise regions in the interference distribution map and updating adaptive filter coefficients, outputting interference noise components, constructing a dynamic superposition model based on the interference noise components and performing residual energy analysis, determining intensity correction values, a spatial mapping matrix according to the intensity correction values, performing inverse weighting compensation on the preset intensity mutation regions in the spatial mapping matrix according to a tissue impedance model, a real-normalized activity distribution can be used for performing inverse weighting and mapping to the real two-dimensional activity distribution, and generating an initial gray texture, performing spatial interpolation, balanced contrast adjustment and sharpening on the initial gray texture, and generating a muscle active image.

Description

Analog display method and system for electromyographic signals Technical Field The invention relates to the technical field of biomedical engineering, in particular to a simulation display method and system of electromyographic signals. Background At present, the electromyographic signal processing technology is a key link in the biomedical engineering field, and is characterized in that the movement intention of a human body is analyzed by capturing an electric signal generated by muscle activity. In practical applications such as rehabilitation and exercise analysis, the intensity distribution of multichannel electromyographic signals needs to be acquired in real time and presented with high fidelity so as to accurately reflect the physiological state and the stress mode of muscles and ensure accurate assessment of muscle functions. In one prior art, multiple original myoelectric signals are typically acquired using an intelligent sensor-integrated acquisition device and processed using conventional time domain analysis methods. Such schemes typically directly full-wave rectify and low-pass filter the original signal to extract an envelope, and then calculate an effective value based on the envelope to generate a signal waveform or intensity thermodynamic diagram. For example, in a continuous motion capture scenario, the system usually performs independent smoothing on each channel data according to fixed filtering parameters, and directly maps the calculated amplitude to a visual image on the assumption that the noise is a constant additive component, without performing depth verification and dynamic separation on the time sequence correlation between channels. The prior art lacks self-adaptive adjustment capability for signal dynamic characteristics, and ignores the dynamic superposition relation existing between external noise and the electromyographic signals, so that obvious defects exist in the processing process. When the collection or action continuously changes for a long time, the simple filtering can not eliminate the interference components accumulated along with the time, so that the calculation result of the effective value is deviated, and the correlation distribution among channels is distorted. Therefore, the prior art has the problem of low accuracy of the visualized image. Disclosure of Invention The invention provides an electromyographic signal simulation display method and system, which are used for solving the problem of low accuracy of a visual image in the prior art. In order to solve the technical problems, the invention provides an analog display method of electromyographic signals, which comprises the steps of obtaining a mixed signal sequence, carrying out channel data analysis and time sequence synchronous verification on the mixed signal sequence, and determining shunt electromyographic signals associated with reserved time sequences; performing full-wave rectification and moving average processing on the shunt electromyographic signals, performing linear interpolation after abnormal fluctuation points are identified by utilizing first-order difference to obtain envelope characteristics of each channel, performing sliding window root mean square on the envelope characteristics, extracting unmarked sections, performing least square fitting to obtain initial variation trend, performing numerical correction according to the initial variation trend to determine initial intensity distribution, performing cross-channel cross-correlation function operation on the initial intensity distribution to obtain cross-correlation coefficients, identifying asynchronous interference components beyond a synchronous fluctuation range by detecting the time lag offset of the cross-correlation coefficients, constructing an interference distribution map, identifying high-frequency noise areas in the interference distribution map, updating adaptive filter coefficients, outputting interference noise components, constructing a dynamic superposition model based on the interference noise components, performing residual energy analysis, determining intensity correction values, combining the intensity correction values with electrode physical layout, performing inverse weighting compensation on the intensity mutation areas in the spatial mapping matrix according to a preset tissue impedance model, reconstructing real activity distribution, converting the real activity distribution into a two-dimensional texture numerical matrix, performing normalization mapping and initial texture rounding, performing grey-scale adjustment, performing spatial contrast adjustment and grey-scale equalization, a muscle activity image is generated. The method comprises the steps of obtaining a mixed signal sequence, writing the original amplitude into an independent channel buffer area corresponding to a channel identifier to obtain independent channel data, calculating a time sequence label deviation value of the independent