【摘要】 智能膝关节假肢是截肢患者恢复日常运动的重要辅具。对人体下肢运动意图的识别是实现下肢假肢控制的关键。该文针对此问题，提出了一种通过表面肌电信号预测膝关节角度的方法。对表面肌电提取时域特征，通过BP神经网络模型建立平地行走过程中表面肌电信号和膝关节角度的映射关系，预测膝关节角度。更多还原

【Abstract】 Robotic knee prosthesis plays an important role to assist amputation subjects while recovering in daily living activities and human lower limb motion intention mapping based on surface electromyography(sEMG) is the key step towards the control of robotic knee prosthesis. In this paper, we propose a method for predicting knee joint angles base on sEMG. Predict the knee joint angle by extraction of the time domain features of sEMG and building the mapping relationship between sEMG and knee joint angle during flat walking through BP neural network model.更多还原