Full-chain Biomechanical Analysis of Human Movement with Musculoskeletal Simulation and Wearable Sensors

Measurement and biomechanical analysis of human movement are important in diverse fields, such as rehabilitation, sports science, ergonomics, and human-robot interaction. However, the accessibility of conventional motion analysis systems - typically based on optical motion capture (Mocap) and force plates - is limited by their high cost and spatial constraints. Recent studies have increasingly exploited the application of wearable sensors, such as inertial measurement units (IMUs) and pressure insoles, to assess human movements. However, the integration of multiple sensor types for estimating internal biomechanical parameters, such as joint torques and muscle activations, remains underdeveloped and insufficiently validated. In this study, we combined wearable sensors with musculoskeletal simulation to enhance a full-chain biomechanical analysis of human movement. Data were simultaneously collected from an integrated wearable sensor system including IMUs and pressure insoles and a laboratory-based Mocap system on five able-bodied participants performing three daily movements: walking, squat and sit-to-stand. Joint angles, joint torques, and muscle activations were estimated with musculoskeletal simulation framework OpenSim. The results demonstrated that the wearable system could provide a sufficiently accurate biomechanical analysis, particularly in sagittal plane joint angles and ankle joint torque. However, the lack of shear force measurement from pressure insoles limited the accuracy in the knee and hip joint estimation. The estimated muscle activation from static optimization showed a similar on-off trend as measured EMG data. These findings highlighted the potential of wearable sensor-based motion analysis as a viable alternative to the conventional lab-based systems, particularly for out-of-lab applications.