Intuitive movement-based prosthesis control enables arm amputees to reach naturally in virtual reality.
artificial intelligence
artificial neural network
human
neuroscience
prosthesis control
virtual reality
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
17 10 2023
17 10 2023
Historique:
medline:
23
10
2023
pubmed:
17
10
2023
entrez:
17
10
2023
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 37847150
doi: 10.7554/eLife.87317
pii: 87317
pmc: PMC10581689
doi:
pii:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023, Segas et al.
Déclaration de conflit d'intérêts
ES, SM, VL, OD, RK, DC, Ad No competing interests declared
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