A Computational Approach for Human-like Motion Generation in Upper Limb Exoskeletons Supporting Scapulohumeral Rhythms

TL;DR

This paper introduces a computational method for generating human-like shoulder motions in upper-limb exoskeletons, accounting for scapulohumeral rhythms and large range of motion, improving support for daily activities.

Contribution

It presents a novel CNS-based computational approach that models shoulder joint movement considering scapulohumeral rhythms, unlike previous fixed-center assumptions.

Findings

Model accurately reproduces human shoulder motions during ADL.

Method supports exoskeletons with different kinematics.

Comparison with experimental data shows high fidelity.

Abstract

This paper proposes a computational approach for generation of reference path for upper-limb exoskeletons considering the scapulohumeral rhythms of the shoulder. The proposed method can be used in upper-limb exoskeletons with 3 Degrees of Freedom (DoF) in shoulder and 1 DoF in elbow, which are capable of supporting shoulder girdle. The developed computational method is based on Central Nervous System (CNS) governing rules. Existing computational reference generation methods are based on the assumption of fixed shoulder center during motions. This assumption can be considered valid for reaching movements with limited range of motion (RoM). However, most upper limb motions such as Activities of Daily Living (ADL) include large scale inward and outward reaching motions, during which the center of shoulder joint moves significantly. The proposed method generates the reference motion based on a simple model of human arm and a transformation can be used to map the developed motion for other exoskeleton with different kinematics. Comparison of the model outputs with experimental results of healthy subjects performing ADL, show that the proposed model is able to reproduce human-like motions.