Fig. 5: Prediction of gait dynamics using the GenENet device.
a, Experimental set-up involving walking across three force plates (FPs) with simultaneous video capture. Fz denotes the vertical ground reaction force. The post-training network is used to predict the GRF, while vertical knee force and moment are calculated through inverse dynamics based on the video data, which are incorporated into the kinetic post-training dataset. b, Schematic of the six-channel EMG device attached to the calf. c, GRF prediction during the gait cycle, showing five distinct phases where predicted values closely match the true values obtained from the video data. d, Snapshots of the real-time prediction of GRF on musculoskeletal model. The green arrow indicates the GRF and the device is attached to the right leg as shown in the red region. e, R2 coefficient of 0.975 for GRF prediction. f, Adaptation to different individuals, showing a consistent R2 coefficient across them. g, Illustration of GRF and KAM vector directions. h, Predicted y-axis knee joint force and KAM over specific time intervals. Muscle contributions were not included in the inverse dynamics calculation of joint forces.
