Movement-based assistive technology for control of digital applications in severe motor impairment: a scoping review.

Authors

Bruno Afonso, André Perrotta, Joaquim Alvarelhão

Published in

Disability and rehabilitation. Assistive technology. Pages 1-16. Jun 29, 2026. Epub Jun 29, 2026.

Abstract

Technological advances have enabled new ways for individuals with severe motor impairments (SMI) to interact with computer-based applications, yet standard human-computer interfaces often remain inaccessible, creating a need for assistive technologies (AT) tailored to diverse motor abilities. This scoping review aims to identify existing AT solutions that enable individuals with SMI to use residual movements for controlling digital applications, characterizing key trends and gaps. Searches were conducted in Scopus and Web of Science Core Collection for studies published between 2012 and June 2024, and data collection took place from July to December 2024. In total 49 articles were included in the review. In addition to descriptive indicators, cross-topic analyses were performed using relationship and correspondence analysis. Overall, the AT landscape for SMI users is dominated by head-based control and 2D pointer interaction for tasks such as typing and navigation. Three-quarters of the publications addressed SMI generically, without specifying underlying conditions or detailed movement profiles. Vision systems dominate, followed by electromyographic and kinematic setups. Most systems employed explicit direct mappings, with only 20% using machine learning. A quarter of systems incorporated auxiliary feedback, with haptics used in only a small minority. Despite advancements in sensor technology and signal processing, improvements are still needed in key areas: integrating multimodal input and feedback, applying machine learning to the design process, and clearly defining target motor profiles. Future research should address these gaps, exploring novel use cases beyond conventional computing tasks and expanding participation among individuals with SMI.

PMID:
42372282
Bibliographic data and abstract were imported from PubMed on 30 Jun 2026.

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