Work

Multi-Objective Optimization and Experimental Validation of Assistive Strategies for a Hip Exoskeleton

Year: 2026

Type: article

Abstract: To address the limited assistive performance and insufficient individual adaptability of hip exoskeletons, a multi-objective optimization-based assistive strategy is proposed. A parameterized assistive torque model is constructed based on human gait characteristics, with the objectives of reducing joint load and improving human–robot interaction coordination. The NSGA-II (Non-dominated Sorting Genetic Algorithm II) is employed to optimize the assistive parameters, and the optimized results are implemented in a gait phase-based control method to achieve synchronized torque output over the gait cycle. Experimental validation is conducted on a hip exoskeleton platform using motion capture and electromyography measurements. The results demonstrate that the proposed method effectively reduces hip joint torque, decreases muscle activation levels, and enhances human–robot interaction performance.

Source: Applied Sciences

DOI: 10.3390/app16136536

Authors: Lin Li, Jilong Gao, Xinqin Gao, Youzhi Lu, Xupeng Wang

Institution: Xi'an University of Technology

Language: English

Topic: Prosthetics and Rehabilitation Robotics

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,896