Biosymbiotic haptic feedback - Sustained long term human machine interfaces.

Closed-loop platform Continuous operation Haptic feedback Posture correction Robotic surgery training Wireless power transfer

Journal

Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289

Informations de publication

Date de publication:
01 Jun 2024
Historique:
received: 15 03 2024
revised: 16 05 2024
accepted: 24 05 2024
medline: 12 6 2024
pubmed: 12 6 2024
entrez: 11 6 2024
Statut: aheadofprint

Résumé

Haptic technology permeates diverse fields and is receiving renewed attention for VR and AR applications. Advances in flexible electronics, facilitate the integration of haptic technologies into soft wearable systems, however, because of small footprint requirements face challenges of operational time requiring either large batteries, wired connections or frequent recharge, restricting the utility of haptic devices to short-duration tasks or low duty cycles, prohibiting continuously assisting applications. Currently many chronic applications are not investigated because of this technological gap. Here, we address wireless power and operation challenges with a biosymbiotic approach enabling continuous operation without user intervention, facilitated by wireless power transfer, eliminating the need for large batteries, and offering long-term haptic feedback without adhesive attachment to the body. These capabilities enable haptic feedback for robotic surgery training and posture correction over weeks of use with neural net computation. The demonstrations showcase that this device class expands use beyond conventional brick and strap or epidermally attached devices enabling new fields of use for imperceptible therapeutic and assistive haptic technologies supporting care and disease management.

Identifiants

pubmed: 38861810
pii: S0956-5663(24)00437-8
doi: 10.1016/j.bios.2024.116432
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

116432

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest

Auteurs

Amanda Tyree (A)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Aman Bhatia (A)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Minsik Hong (M)

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Jessica Hanna (J)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Kevin Albert Kasper (KA)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Brandon Good (B)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Dania Perez (D)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Dema Nua Govalla (DN)

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Abigail Hunt (A)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Vasanth Sathishkumaraselvam (V)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Jordan Philip Hoffman (JP)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA.

Jerzy W Rozenblit (JW)

Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA; Bio5 Institute, University of Arizona, Tucson, AZ, 85721, USA. Electronic address: jerzy.rozenblit@arizona.edu.

Philipp Gutruf (P)

Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85721, USA; Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA; Bio5 Institute, University of Arizona, Tucson, AZ, 85721, USA; Neroscience GIDP, University of Arizona, Tucson, AZ, 85721, USA. Electronic address: pgutruf@arizona.edu.

Classifications MeSH