Fall prevention is one of the most important components in senior care. We present a technique to augment an assistive walking device with the ability to prevent falls. Given an existing walking device, our method develops a fall predictor and a recovery policy by utilizing the onboard sensors and actuators. The key component of our method is a robust human walking policy that models realistic human gait under a moderate level of perturbations. We use this human walking policy to provide training data for the fall predictor, as well as to teach the recovery policy how to best modify the person's gait when a fall is imminent. Our evaluation shows that the human walking policy generates walking sequences similar to those reported in biomechanics literature. Our experiments in simulation show that the augmented assistive device can indeed help recover balance from a variety of external perturbations. We also provide a quantitative method to evaluate the design choices for an assistive device.
Personalised 3D Human Digital Twin with Soft-Body Feet for Walking Simulation
School of Mechanical and Aerospace Engineering, Nanyang Technological University（南洋理工大学机械与航空航天工程学院）；Rehabilitation Research Institute of Singapore (RRIS)（新加坡康复研究院）
A Data-Driven Reinforcement Learning Solution Framework for Optimal and Adaptive Personalization of a Hip Exoskeleton
NC State University（北卡罗来纳州立大学）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；Arizona State University（亚利桑那州立大学）；Hubei University of Technology（湖北工业大学）
A Three-Stage Offline SDRE-Based Control Framework for Human Motion Reproduction on a Suspended Bipedal Robot
Department of Applied Mathematics, National Yang Ming Chiao Tung University（应用数学系，阳明交通大学）；Department of Electrical Engineering, National Central University（电气工程系，国立中央大学）
The Strange Attractor Model of Bipedal Locomotion and its Consequences on Motor Control
School of Engineering and Informatics, University of Sussex（萨塞克斯大学工程与信息学院）；Rehabilitation Research Institute of Singapore, Nanyang Technological University（新加坡南洋理工大学新加坡康复研究院）；School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；School of Electronics Engineering, Kyungpook National University（庆北国立大学电子工程学院）；Escola Politecnica da Universidade de Sao Paulo（圣保罗大学理工学院）
