考虑动态平衡的起立意图预测OA北大核心CSTPCD

Aiming at the problem that the sit-to-stand intention is difficult to predict and the black box model is lack of biomechanical explanation,a sit-to-stand intention prediction method considering dynamic equilibrium was proposed.According to the law of dynamic equilibrium followed by the human body's sit-to-stand movement,a nonlinear processing method of the centroid trajectory considering the speed of the sit-to-stand movement was proposed,i.e.,extrapolated center of mass(CoM),transforming the Cartesian coordinate plane of the CoM to the dynamic equilibrium reference plane,reducing the dependence of feature data on the human body's motion speed,and improving the accuracy of the judgment of the sit-to-stand intention.Support vector machines(SVM)and neural networks(NN)were used to validate the proposed method,and the proposed method was compared with traditional data processing methods.Results show that the accuracy of model prediction is improved.The prediction accuracy of SVM is improved from 73.3%～74.1%to 79.9%,and the time deviation between stand up time and assist time is reduced from 96～101 ms to 70 ms.The prediction accuracy of the NN increases from 81.2%to 86.2%,and the time deviation decreases from 87 ms to 59 ms.