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Biomechanics beyond the lab: remote technology for osteoarthritis patient data-a scoping review

Hamilton, Rebecca I., Williams, Jenny and Holt, Cathy ORCID: https://orcid.org/0000-0002-0428-8078 2022. Biomechanics beyond the lab: remote technology for osteoarthritis patient data-a scoping review. Frontiers in Rehabilitation Sciences 3 , 1005000. 10.3389/fresc.2022.1005000

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License Start date: 14 November 2022

Abstract

The objective of this project is to produce a review of available and validated technologies suitable for gathering biomechanical and functional research data in patients with osteoarthritis (OA), outside of a traditionally fixed laboratory setting. A scoping review was conducted using defined search terms across three databases (Scopus, Ovid MEDLINE, and PEDro), and additional sources of information from grey literature were added. One author carried out an initial title and abstract review, and two authors independently completed full-text screenings. Out of the total 5,164 articles screened, 75 were included based on inclusion criteria covering a range of technologies in articles published from 2015. These were subsequently categorised by technology type, parameters measured, level of remoteness, and a separate table of commercially available systems. The results concluded that from the growing number of available and emerging technologies, there is a well-established range in use and further in development. Of particular note are the wide-ranging available inertial measurement unit systems and the breadth of technology available to record basic gait spatiotemporal measures with highly beneficial and informative functional outputs. With the majority of technologies categorised as suitable for part-remote use, the number of technologies that are usable and fully remote is rare and they usually employ smartphone software to enable this. With many systems being developed for camera-based technology, such technology is likely to increase in usability and availability as computational models are being developed with increased sensitivities to recognise patterns of movement, enabling data collection in the wider environment and reducing costs and creating a better understanding of OA patient biomechanical and functional movement data.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Frontiers Media
ISSN: 2673-6861
Funders: EPSRC
Date of First Compliant Deposit: 14 November 2022
Date of Acceptance: 5 October 2022
Last Modified: 14 Jun 2023 16:29
URI: https://orca.cardiff.ac.uk/id/eprint/154174

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