This paper presents an accessible single-camera gait analysis framework that uses a standard RGB video camera and open-source software to extract sagittal-plane joint kinematics and illustrate model-based kinetic behavior. The proposed data pipeline converts RGB video frames into 2D joint trajectories using marker-based tracking, which are subsequently processed to compute joint angles and angular velocities. These kinematic variables are then integrated into a planar three-link inverse-dynamics model implemented in MATLAB® Simscape Multibody™, enabling the estimation of joint torque and power profiles from visually captured motion. The modeling implementation is first evaluated using a published reference dataset to verify the consistency of the inverse-dynamics computation, yielding normalized RMS differences below approximately 2% for joint torque profiles and below 5% for joint power profiles. Camera-derived joint trajectories are then applied to generate qualitative torque and power waveforms across the gait cycle. Geometric consistency analysis indicates stable reconstruction of proximal segment lengths, while larger variability is observed in distal segments due to projection effects and depth limitations inherent to monocular 2D tracking. The extracted joint-angle and angular-velocity profiles preserve characteristic waveform structures commonly observed in sagittal-plane gait analysis. Although torque and power magnitudes differ from reference data due to planar kinematic inputs and simplified ground-reaction-force assumptions, their temporal patterns remain qualitatively consistent across the gait cycle. The framework is intended for trend-level kinetic illustration, exploratory motion analysis, and instructional use in environments where laboratory-based gait analysis systems are unavailable.
Phathaisuang et al. (Mon,) studied this question.