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目的:提出一种基于表面肌电信号时频分析的预测膝关节力矩的新方法。方法:受试者完成递增负重蹲起实验,采集股直肌的表面肌电信号进行时频分析,获得基于Wigner-Ville分布的表面肌电信号在时间和频率的二维平面上的能量密度,并由此估算出能够反映肌肉瞬时做功能力的敏感指标——瞬时平均频率功率。结果:以股直肌的瞬时平均频率功率和膝角为自变量,获得的二元线性回归方程可以有效预测膝关节瞬时力矩的大小。结论:表面肌电信号瞬时平均频率功率能实时反映肌肉的做功能力,可作为预测膝关节力矩和预防膝关节损伤的一个基础指标。
OBJECTIVE: To propose a new method for predicting knee joint torque based on time-frequency analysis of surface EMG signals. Methods: The subjects completed progressive weight squatting experiments, the surface rectus muscle EMG signals were collected for time-frequency analysis to obtain the Wigner-Ville distribution of surface EMG signal in two-dimensional time and frequency energy density, And estimate the instantaneous average frequency power that can reflect the muscular instantaneous power function. Results: The binary linear regression equation obtained by using the instantaneous mean frequency power of the rectus femoris muscle and the knee angle as an independent variable can effectively predict the instantaneous moment of knee joint. CONCLUSION: The instantaneous average frequency power of surface EMG can reflect the work ability of muscle in real time, which can be used as a basic index to predict knee joint torque and prevent knee joint injury.