Estimation of Ground Reaction Force and Center of Pressure During Walking Based on Neural Network Model
10.16156/j.1004-7220.2025.01.019
- VernacularTitle:基于神经网络模型估算步行中的地面反作用力和压力中心
- Author:
Ru FENG
1
;
Chen YANG
;
Hui LIU
Author Information
1. 南京体育学院运动健康学院,南京 210014
- Publication Type:Journal Article
- Keywords:
ground reaction force;
center of pressure;
neural network;
gait analysis
- From:
Journal of Medical Biomechanics
2025;40(1):140-147
- CountryChina
- Language:Chinese
-
Abstract:
Objective Two neural network algorithm models were constructed to estimate the three-dimensional(3D)ground reaction force(GRF)and center of pressure(COP)during walking,and the estimation results of two algorithm models were compared,so as to provide a solution for the acquisition of gait dynamics data without force plate.Methods A total of 1 384 gait data were selected.Multi-layer perceptron(MLP)and convolutional neural network(CNN)were applid to construct models for estimating GRF and COP components based on the 3D trajectories of whole-body markers.100 samples were randomly selected as the test set,and the estimation performance was evaluated by the correlation coefficient(r),relative root mean square error(rRMSE).Paired-sample t-tests were used to compare the estimation performance of the two neural network models.Results The r values of each components of GRF estimated by MLP were 0.954-0.993,and the rRMSEs were 4.36％-9.83％.The rvalues of each component of GRF estimated by CNN were 0.979-0.994,and the rRMSEs were 3.06％-6.69％.The rvalues of each component of COP estimated by MLP were 0.888-0.992,and the rRMSEs were 4.78％-16.63％.The rvalues of each component of COP estimated by CNN were 0.944-0.995,and rRMSEs were 3.06％-10.85％.The RMSEs of CNN in estimating the medio-lateral component of GRF,the medio-lateral and antero-posterior components of COP during right stance phase,as well as the medio-lateral and antero-posterior components of COP during left stance phase were all lower than those of MLP(P＜0.01).The RMSEs of MLP in estimating the anterior-posterior component of GRF during right stance phase,as well as the anterior-posterior component of COP and the vertical direction of GRF during left stance phase were lower than those of CNN(P＜0.01).Conclusions Both MLP and CNN achieved good estimation accuracy in estimating GRF and COP during walking based on the trajectories of whole-body markers.The estimation accuracy of MLP in estimating the anterior-posterior components and vertical component of GRF was better than that of CNN,while the estimation accuracy of CNN in estimating the medio-lateral component of GRF,the anterior-posterior and medio-lateral components of COP were better than that of MLP.
