Gait and Posture Analysis

This project develops a wearable, IMU-based framework for capturing and analysing human gait beyond conventional laboratory environments. The system uses strategically positioned inertial sensors around the hip, knee, and ankle to acquire lower-limb motion and derive reliable joint kinematics through sensor fusion and advanced filtering. Moving beyond conventional gait parameters, the project introduces and tests different frameworks like Kalman Filter (KF), Principle Component Analysis (PCA),Transfer Entropy (TE) to provide a data-driven perspective on inter-joint coordination and muscle strength. The framework is used to investigate how footwear characteristics and terrain variations influence gait dynamics and redistribute coordination among the hip, knee, and ankle. By identifying which joints predominantly generate, receive, or adapt to changes in movement, the research provides deeper insight into the mechanisms underlying human gait adaptation. The work has potential applications in objective gait assessment, rehabilitation, wearable biomechanics, and footwear design.