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Assistive Technology
The Official Journal of RESNA
Volume 33, 2021 - Issue sup1: Companion Papers to the Global Report on Assistive Technology
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Research Article

Emerging technologies and their potential for generating new assistive technologies

Sarah Abdia Centre for Assistive Technology and Connected Healthcare, School of Health and Related Research, University of Sheffield, Sheffield, UKView further author information
, MSc,
Irene Kitsarab Technology and Innovation Support Division, IP for Innovators Department, IP and Innovation Ecosystems Sector, World Intellectual Property Organisation (WIPO), Geneva, SwitzerlandView further author information
, MSc,
Mark S. Hawleya Centre for Assistive Technology and Connected Healthcare, School of Health and Related Research, University of Sheffield, Sheffield, UKView further author information
, PhD &
L. P. de Wittea Centre for Assistive Technology and Connected Healthcare, School of Health and Related Research, University of Sheffield, Sheffield, UKCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-3013-2640View further author information
, PhDORCID Icon
Pages 17-26 | Accepted 15 Jun 2021, Published online: 24 Dec 2021

Citations (4)

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Read on this site (1)

Johan Borg, Wei Zhang, Emma M. Smith & Cathy Holloway. (2021) Introduction to the companion papers to the global report on assistive technology. Assistive Technology 33:sup1, pages 1-2.
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Articles from other publishers (3)

Tamara OwnsworthJessie MitchellJanelle GriffinRyan BellEmily GibsonCamila Shirota. (2023) Electronic Assistive Technology to Support Memory Function After Traumatic Brain Injury: A Systematic Review of Efficacy and User Perspectives. Journal of Neurotrauma 40:15-16, pages 1533-1556.
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Olga Lukashova-Sanz, Martin Dechant & Siegfried Wahl. (2023) The Influence of Disclosing the AI Potential Error to the User on the Efficiency of User–AI Collaboration. Applied Sciences 13:6, pages 3572.
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Ankita Tripathi, Meenu Shukla & Fatima Ziya. 2022. Leveraging AI Technologies for Preventing and Detecting Sudden Cardiac Arrest and Death. Leveraging AI Technologies for Preventing and Detecting Sudden Cardiac Arrest and Death 84 110 .

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