Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/14794
Title: Mobile three-dimensional visualisation technologies for clinician-led fall prevention assessments
Authors: Hamm, J
Money, AG
Atwal, A
Ghinea, G
Keywords: assistive equipment;assistive technologies;falls prevention;health care;occupational therapy;three-dimensional visualisation technology
Issue Date: 17-Aug-2017
Publisher: SAGE Publications
Citation: Hamm, J., Money, A.G., Atwal, A and Ghinea, G. (2019) ‘Mobile three-dimensional visualisation technologies for clinician-led fall prevention assessments’, Health Informatics Journal, 25, (3), pp. 788 - 810. doi: 10.1177/1460458217723170.
Abstract: Copyright © The Author(s) 2017. The assistive equipment provision process is routinely carried out with patients to mitigate fall risk factors via the fitment of assistive equipment within the home. However, currently, over 50% of assistive equipment is abandoned by the patients due to poor fit between the patient and the assistive equipment. This paper explores clinician perceptions of an early stage three-dimensional measurement aid prototype, which provides enhanced assistive equipment provision process guidance to clinicians. Ten occupational therapists trialled the three-dimensional measurement aid prototype application; think-aloud and semi-structured interview data was collected. Usability was measured with the System Usability Scale. Participants scored three-dimensional measurement aid prototype as ‘excellent’ and agreed strongly with items relating to the usability and learnability of the application. The qualitative analysis identified opportunities for improving existing practice, including, improved interpretation/recording measurements; enhanced collaborative practice within the assistive equipment provision process. Future research is needed to determine the clinical utility of this application compared with two-dimensional counterpart paper-based guidance leaflets.
URI: https://bura.brunel.ac.uk/handle/2438/14794
DOI: https://doi.org/10.1177%2F1460458217723170
ISSN: 1460-4582
Appears in Collections:Dept of Computer Science Research Papers

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