Validation of Cable-Driven Experimental Setup to Assess Movements Made with Elbow Joint Assistance
Year: 2025
Type: article
Abstract: This article investigates a cable-driven experimental setup to simulate elbow joint assistance in the sagittal plane provided by an exosuit. Cable-driven exosuits, particularly fabric-based designs, significantly enhance rehabilitation by enabling targeted joint exercises and promoting functional recovery. To achieve an optimal design, these devices require an analysis of the cable tension, reaction forces, and moments and their dependency on the anchor position. This study presents a cable-driven experimental setup with two rigid bars and variable anchor positions, designed to mimic the human forearm, upper arm, and elbow joint, to evaluate the performance of a potential cable-driven exosuit. Based on the experimental setup, a static model was developed to validate the measured cable tension and estimate the reaction force at the joint and the moments at the anchor positions. Furthermore, based on the observations, an optimization problem was defined to identify optimal anchor positions to improve the exosuit’s design. The optimal position on the forearm and upper arm is studied between 15% and 50% distance from the elbow joint. Our findings suggest that prioritizing user comfort requires both anchor points to be as far away from the elbow joint as possible, i.e., 50% distance, whereas, for optimal exosuit performance, the forearm anchor position can be adjusted based on the joint angle while keeping the upper arm anchor position at the farthest point. The findings in the current work can be used to decide the anchor point position for designing an elbow exosuit.
Source: Applied Sciences
DOI: 10.3390/app15041892
Institutions: École Centrale de Nantes, Mahindra University, Nantes Université
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: I-Hub Foundation for Cobotics
Award: G1945333921
OpenAlex ID: W4407410783
