In conclusion, this study illustrates that an RL approach can be an alternative technique to conventional inverse dynamic analysis in human biomechanics study and EMG-driven human-machine interfacing applications.Ĭhallenges in application of these methods remain, especially regarding simulation accuracy, data availability, and signal quality. In addition, a biomechanically reasonable joint moment-angle-EMG relationship (i.e., dependence of joint moment on joint angle and EMG) was predicted using only 15 s of collected data. The correlation coefficients between predicted and measured kinematics, derived from the kinematics-driven agent and subject-specific EMG-driven agents, were 98% ± 1% and 94% ± 3% for the wrist, respectively, and were 95% ± 2% and 84% ± 6% for the metacarpophalangeal joint, respectively. The results demonstrated that both trained RL agents are feasible to estimate joint moment for wrist and metacarpophalangeal (MCP) joint motion prediction. To quantify the performance of trained RL agents, the estimated joint moment was used to drive a forward dynamic model for estimating kinematics, which was then compared with measured kinematics using Pearson correlation coefficient. Using the proximal policy optimization approach, we trained two types of RL agents that estimated joint moment based on measured kinematics or measured EMGs, respectively.
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Forearm and hand kinematics and forearm EMGs from four muscles during free finger and wrist movement were collected from six healthy subjects. Here, we explore feasibility of RL to assist joint moment estimation for biomechanical applications. Reinforcement learning (RL) has potential to provide innovative solutions to existing challenges in estimating joint moments in motion analysis, such as kinematic or electromyography (EMG) noise and unknown model parameters. Journal of Verification, Validation and Uncertainty Quantification.Journal of Thermal Science and Engineering Applications.Journal of Offshore Mechanics and Arctic Engineering.Journal of Nuclear Engineering and Radiation Science.Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems.Journal of Nanotechnology in Engineering and Medicine.Journal of Micro and Nano-Manufacturing.Journal of Manufacturing Science and Engineering.Journal of Engineering Materials and Technology.Journal of Engineering for Sustainable Buildings and Cities.Journal of Engineering for Gas Turbines and Power.Journal of Engineering and Science in Medical Diagnostics and Therapy.Journal of Electrochemical Energy Conversion and Storage.Journal of Dynamic Systems, Measurement, and Control.Journal of Computing and Information Science in Engineering.Journal of Computational and Nonlinear Dynamics.Journal of Autonomous Vehicles and Systems.ASME Letters in Dynamic Systems and Control.ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering.Mechanical Engineering Magazine Select Articles.
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