CN104224169A - Surface electromyogram signal linear analyzing method for judging human body muscle fatigue - Google Patents
Surface electromyogram signal linear analyzing method for judging human body muscle fatigue Download PDFInfo
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- CN104224169A CN104224169A CN201410542102.6A CN201410542102A CN104224169A CN 104224169 A CN104224169 A CN 104224169A CN 201410542102 A CN201410542102 A CN 201410542102A CN 104224169 A CN104224169 A CN 104224169A
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Abstract
The invention relates to the field of interdiscipline of signal processing, medicine and biomechanics, in particular to a surface electromyogram signal linear analyzing method for judging the human body muscle fatigue. The method comprises the steps of measuring surface electromyogram signals of different test points of the same muscle, filtering the signals to remove artifacts, using empirical mode decomposition (EMD) to carry out noise reduction on the surface electromyogram signals, carrying out signal reconstruction according to the frequency spectrums of the electromyogram signals and carrying out linear analysis on the reconstructed surface electromyogram signals (SEMG) to respectively extract integral electromyogram signals (IEMG), root-mean-square values (IEMG), the mean amplitude (MA), the zero-crossing rate, the mid-value frequency and the mean frequency (MNF). The change tendency of a linear index in a continuous increasing process of the muscle fatigue degree can be checked to provide theoretical basis for evaluating the muscle fatigue.
Description
Technical field
The present invention relates to a kind of linearly analytical method, particularly a kind of surface electromyogram signal linear analysis method for judging human muscle's fatigue.The invention belongs to signal processing, medical science, biomechanics interdisciplinary field.
Background technology
Surface myoelectric (surface electromyography, SEMG) signal is the complicated small-signal of one obtained at skin surface, motor unit action potential (the motor unit action potential formed when can regard that motor unit activates as, MUAP) result that superposes with various noise synthesis of sequence, it can obtain the relevant information of neuromuscular control system by the mode of Non-invasive detection.Current use surface electromyogram signal carries out part muscle vveariness research and has been applied to multiple industry and sphere of life, as the treatment of athletic training, ergonomic design, rehabilitation engineering, neural patient.
Summary of the invention
The present invention mainly for the chronic musculoskeletal illness relevant with occupation, as neck, shoulder, waist, backache and complication of wrist etc.A kind of surface electromyogram signal linear analysis method for judging human muscle's fatigue is proposed, this invention is by the linear process to muscle diverse location surface electromyogram signal, analyze muscle fatigue situation, prevention and corntrol muscle fatigue in advance, the deficiency of subjective assessment can be overcome, the generation of effective prevention and corntrol chronic musculoskeletal illness.
For achieving the above object, the present invention takes following technical scheme: initial data DC method gathers, 7 are adopted to lead Ag/AgCl electrode record SEMG data, with Scan4.3 software to initial surface myoelectricity data analysis, remove artefact, empirical mode decomposition is utilized to carry out noise reduction process to filtered primary signal, obvious for part low frequency IMF interference components and redundant components are removed, then corresponding IMF component is reconstructed to the SEMG signal that just can obtain after noise reduction process, extract the linear index of surface electromyogram signal, linear (the IEMG of analytical calculation, RMS, MA, ZCR, MF, MNF) index.Investigating the eigenvalue of the different test point surface electromyogram signals of same muscle and contrast, analyzing and determine that linear index constantly increases the weight of the variation tendency in process in muscle fatigue degree, evaluating muscle fatigue degree for judging.
Accompanying drawing explanation
Fig. 1 surface electromyogram signal liner fraction implementing procedure figure.
embodiment
By being example to chronic neck pain modal in occupational musculoskeletal disorder, researcher has investigated 632 staff of less than 36 years old and student, and find that there is 258 examples ill, prevalence is 41%, and musculi colli fatigue is one of major reason causing cervical spondylosis.
Experiment is chosen subjects's cervical region Superior trapezius surface electromyogram signal and is analyzed and researched, DC method is adopted to gather, 7 are adopted to lead Ag/AgCl electrode record SEMG data, sample frequency 1000Hz, bandpass filtering is 0.1-500Hz, with Scan4.3 software to initial surface myoelectricity data analysis, remove artefact, empirical mode decomposition is utilized to carry out noise reduction process to filtered primary signal, obvious for part low frequency IMF interference components and redundant components are removed, then corresponding IMF component is reconstructed to the SEMG signal that just can obtain after noise reduction process, extract the linear character index (IEMG of surface electromyogram signal, RMS, MA, ZCR, MF, MNF), analytical calculation linear index, investigate the eigenvalue of the different test point surface electromyogram signals of same muscle and contrast, determine that linear index constantly increases the weight of the variation tendency in process in cervical region Superior trapezius muscle fatigue degree by analysis, musculi colli degree of fatigue is evaluated for judging, in conjunction with cervical region biomechanics and Medical Imaging, explain that the pathogenesis of the collar dish pathological changes of low sections often occurs people who bends over one's desk working for a long time.
Claims (2)
1. one kind for judging the surface electromyogram signal linear analysis method of human muscle's fatigue, it is characterized in that: by analyzing the linear index of muscle surface electromyographic signal, integration myoelectricity value (IEMG), root-mean-square value (RMS), mean amplitude of tide (MA), zero-crossing rate (ZCR), median frequency (MF), average frequency (MNF), investigation linear index constantly increases the weight of the variation tendency in process in muscle fatigue degree, for the evaluation of muscle fatigue provides theoretical foundation.
2. the surface electromyogram signal linear analysis method according to claims 1, it is characterized in that: directly gather the initial data that muscle surface electromyographic signal obtains, by the impact of the factors such as muscle physiological characteristic, checkout equipment, spatial environments, precision is not high, need carry out noise reduction process by empirical mode decomposition (EMD) effects on surface electromyographic signal, the electromyographic signal after process carries out signal reconstruction, attenuating noise information, obtain by the original electromyographic signal of sound pollution, improve the fidelity of signal.
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| CN105147251B (en) * | 2015-08-19 | 2017-12-22 | 宁波工程学院 | Muscular fatigue dynamic prediction method based on multichannel sEMG |
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