## 2 Materials and Methods
### Data Collection and Processing  
The kinetic and kinematic data were collected during the last minute of baseline, the first minute of the third bout of biofeedback adaptation (acquisition), immediately after biofeedback (recall 1), and after a 5 min break (recall 2). GRFs were captured at 1000 Hz using a force platform embedded in the instrumented split-belt treadmill (Motek Medical, Amsterdam, The Netherlands). Three-dimensional kinematic data were captured at 100 Hz using a 10-camera Vicon motion capture analysis system (Oxford Metrics, Oxford, UK). Surface electromyography (EMG) electrodes with wireless preamplifiers (Trigno, Delsys, Inc., Boston, MA, USA) were placed on the right leg's gluteus maximus (GMAX) and vastus lateralis (VL) muscles. EMG signals were sampled at 2000 Hz and visually checked for quality when participants contracted each muscle. Each participant's comfortable and fastest overground walking speed was measured twice along a 10 m walkway before and after the training session to evaluate the effect of VGRF biofeedback on overground walking speed.  
GRFs and marker trajectories were low-pass filtered using a fourth-order Butterworth filter at 20 Hz and 6 Hz, respectively. Kinetic and kinematic variables for the last 30 s of each trial were calculated in Visual3D (C-motion Inc., Germantown, MD, USA). Net joint torques were calculated via inverse dynamics. EMG signals were processed in MATLAB (23.2.0.2391609 (R2023b)) (MathWorks, Inc., Natick, MA, USA) using a Butterworth band-pass filter (16-500 Hz), full-wave rectification, and a Butterworth low-pass filter at 20 Hz. EMG signals during biofeedback and recall trials were normalized to the mean EMG signal during the stance phase of baseline walking.  
All the kinetic and kinematic variables were recorded during the last minute of each trial of the baseline, acquisition, and recall trials and analyzed during the last 30 s of each trial.  
Primary outcome variables included peak VGRF, knee extension torque, and knee flexion angle during the first half of the stance phase. Secondary outcome measures included peak hip extension torque, hip flexion angle, knee flexion excursion, knee extension torque  
Figure 3: The experimental setup involved projecting real-time vertical ground reaction force (VGRF) biofeedback in front of the participants with a horizontal yellow targeted line set at 10 to 15% higher than their baseline first peak of VGRF.  
contribution, and peak VL and GMAX normalized EMG during the first half of the stance phase. Knee flexion excursion was calculated as the difference between peak knee flexion angle during loading response and knee flexion angle at heel strike [27]. To evaluate how biofeedback affects the knee extension torque changes relative to the hip extension torque, the knee extension torque relative contribution was calculated as  
Knee Extension Torque Contribution Percentage = (Knee extension torque/ (Knee extension torque + Hip extension torque)) \(\times\)100.  
A higher percentage indicates a greater reliance on knee extension torque relative to hip extension torque. All variables were calculated for each stride and averaged across strides on the right leg for each trial.