A Grasping Movement Intention Estimator for Intuitive Control of Assistive Devices

TL;DR

This paper presents i-GRIP, a novel movement goal estimator that enables intuitive control of assistive grasping devices by analyzing hand movements without requiring explicit commands, promising improved daily usability for users with impairments.

Contribution

The paper introduces i-GRIP, an innovative algorithm for estimating grasping intentions that operates seamlessly within a collaborative control framework, enhancing assistive device control.

Findings

i-GRIP demonstrated promising goal estimation accuracy.

The system responded effectively in experimental settings.

Potential for future daily use by individuals with impairments.

Abstract

This study introduces i-GRIP, an innovative movement goal estimator designed to facilitate the control of assistive devices for grasping tasks in individuals with upperlimb impairments. The algorithm operates within a collaborative control paradigm, eliminating the need for specific user actions apart from naturally moving their hand toward a desired object. i-GRIP analyzes the hand's movement in an object-populated scene to determine its target and select an appropriate grip. In an experimental study involving 11 healthy participants, i-GRIP showed promising goal estimation performances and responsiveness and the potential to facilitate the daily use of assistive devices for individuals with upper-limb impairments in the future.