股内侧肌疲劳时表面肌电信号特征研究

目的:通过分析双侧股内侧肌疲劳时表面肌电图(SEMG)信号特征,探讨利用SEMG评价肌肉疲劳的新方法,拓展表面肌电图的临床应用。方法:4名健康青年女性采用60%最大负荷能力,伸膝约65°,静态等长收缩3min,同步记录受试者双侧股内侧肌的表面肌电信号,对实验数据进行曲线拟合、非线性回归分析。结果:股内侧肌疲劳时的SEMG各参数与测试时段的最优拟合曲线均为三次项曲线,其通式为Y=b0+b1x+b2x2+b3x3。中位频率(MF)、平均功率频率(MPF)、过零率(ZCR)方程中的b1和b3为负数,b2为正数。平均肌电图(AEMG)方程中b1和b3为正数,b2为负数。结果表明,肌肉疲劳的曲线为三次项曲线,影响肌肉疲劳的主要因素可能有3个,但其确切机制仍有待进一步研究确定。

Research on the Surface Electromyographic Signal Characteristics in Vastus Medialis during Muscular Fatigue

Objective To explore a new method for evaluating muscle fatigue by analyzing the surface electromyographic(SEMG) signal characteristics and to search for the practical use of SEMG.Methods Four healthy young females performed continuous isometric contractions of vastus medialis at 65° knee extension with 60% MVC for 3 minutes. SEMG signals were recorded from bilateral vastus medialis. The data were analyzed through curve fitting and nonlinear regression.Results All the estimative curves for SEMG parameter in relation to the testing phase are of cubic with the equations of Y=b_0+b_1x+b_2x2+b_3x3. The b1 and b3 in the formula are negative and b2 is positive for MF,MPF,ZCR, whereas the b1 and b3 are positive and b2 is negative for AEMG.Conclusion The cubic curve during muscle fatigue suggests that three main factors may involve in muscle fatigue. The factors were discussed briefly and need to be confirmed further.