Intuitive movement-based prosthesis control enables arm amputees to reach naturally in virtual reality

Author:

Segas Effie1ORCID,Mick Sébastien12ORCID,Leconte Vincent1,Dubois Océane12,Klotz Rémi3,Cattaert Daniel1ORCID,de Rugy Aymar1ORCID

Affiliation:

1. Univ. Bordeaux, CNRS, INCIA, UMR 5287

2. ISIR UMR 7222, Sorbonne Université, CNRS, Inserm

3. CMPR Tour de Gassies

Abstract

Impressive progress is being made in bionic limbs design and control. Yet, controlling the numerous joints of a prosthetic arm necessary to place the hand at a correct position and orientation to grasp objects remains challenging. Here, we designed an intuitive, movement-based prosthesis control that leverages natural arm coordination to predict distal joints missing in people with transhumeral limb loss based on proximal residual limb motion and knowledge of the movement goal. This control was validated on 29 participants, including seven with above-elbow limb loss, who picked and placed bottles in a wide range of locations in virtual reality, with median success rates over 99% and movement times identical to those of natural movements. This control also enabled 15 participants, including three with limb differences, to reach and grasp real objects with a robotic arm operated according to the same principle. Remarkably, this was achieved without any prior training, indicating that this control is intuitive and instantaneously usable. It could be used for phantom limb pain management in virtual reality, or to augment the reaching capabilities of invasive neural interfaces usually more focused on hand and grasp control.

Funder

Direction Générale de l’Armement

Centre National de la Recherche Scientifique

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference59 articles.

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4. Decoding of grasping tasks from intraneural recordings in trans-radial amputee;Cracchiolo;Journal of Neural Engineering,2020

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