3 accepted papers
Accurate prediction of human joint moments is essential for enhancing the stability, responsiveness, and control of wearable exoskeletons. Although machine learning approaches from inertial measurement unit (IMU) signals have advanced joint moment estimation, existing models still suffer from limite
Modeling and controlling the musculoskeletal system are crucial for understanding human motor functions, optimizing human-robot interaction, and developing embodied intelligence. However, existing musculoskeletal models are mainly limited to specific body parts and muscle groups, and still face chal
This paper presents a comparative analysis of model-based control strategies for a Bionic Ankle Tensegrity Exoskeleton (BATE), designed to emulate the self-stress equilibrium and self-supporting characteristics of the human ankle biotensegrity structure. Model-based control strategies are convention