SEMG Signal Indicators On Six Characteristics Of The Rectus Femoris Muscle Fatigue Sensitivity

Objectve: Study of ordinary people and regular exercise advantage legs the rectus femorislast isometric contraction of surface electromyography(sEMG) signal, sEMG signals usedtest three linear characteristic indicators the concentric IEMG, AEMG, MPF, and threenon-linear characteristics of indicators C(n),%DET, Entropy for fatigue sensitivity.Methods: The study subjects were divided into control and experimental groups, the controlgroup of eight of Wuhan Institute of Physical Education, Graduate School of HumanMovement Science graduate, the experimental group of eight undergraduate students ofWuhan Institute of Physical Education professional badminton special sports training, finlandproduced MEGA brand assessment laboratory research equipment for the Wuhan Institute ofPhysical Education Kinesiology ME6000-T16telemetry surface electromyography tester HPlaptop, the American BIODEX multi-joint isokinetic testing system, rectus to remain seatedextensor action research model of the dominant leg shares, do30o40%MVC,30o80%MVC,60o40%MVC,60o80%MVC load isometric contraction until fatigue, EMG signal eachexperimental level subjects sEMG signals and record the whole process is divided into11segments, the first seconds of each segment of the calculation interval as calculated above sixcharacteristics of indicators, obtained for each experimental level16(16subjects)×11=176segments, for experimental level704segment calculated interval, observations ofeach calculation interval operator six indicators, so this study were obtained partial correlationanalysis of the4224data to do SPSS simple variabke multivariate analysis of variance, andthe regression analysis.Result: By partial correlation analysis, sEMG signal linear characteristic index fatigue relatedsampling points for the MPF, and only associated with fatigue, nonlinear characteristics ofindicators associated fatigue for C(n); sampling point for the MPF and C(n) observations ahighly significant main effect by single dependent variable multi-factor analysis of variance;by regression analysis, found that MPF the observed values of C(n) with the deepening of thedegree of fatigue showing a very significant downward trend, C(n) of observations cansignificantly distinguish the difference in exercise capacity of subjects.Conclusion:1. The sEMG signal linear characteristic indicators IEMG, AEMG, MPF and non-linear characteristics of indicators C(n),%DET, Entropy, sensitive to fatigue change isMPF and C(n), their observations showed very significant downward trend with thedeepening of the degree of fatigue;2. Division the sEMG signal characteristic index IEMG,AEMG, MPF, C(n),%DET, Entropy, C(n) observations not only reflect the very significantdeepening of the degree of fatigue, also significantly distinguish differences in subjectsathletic ability.