Reducing the muscle activity of walking using a portable hip exoskeleton based on human-in-the-loop optimization.

ABSTRACT: Introduction: Human-in-the-loop optimization has made great progress to improve the performance of wearable robotic devices and become an effective customized assistance strategy. However, a lengthy period (several hours) of continuous walking for iterative optimization for each individual makes it less practical, especially for disabled people, who may not endure this process. Methods: In this paper, we provide a muscle-activity-based human-in-the-loop optimization strategy that can reduce the time spent on collecting biosignals during each iteration from around 120 s to 25 s. Both Bayesian and Covariance Matrix Adaptive Evolution Strategy (CMA-ES) optimization algorithms were adopted on a portable hip exoskeleton to generate optimal assist torque patterns, optimizing rectus

SUBMITTER: Xu L 

PROVIDER: S-EPMC10192560 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature