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Title: Fall prevention intervention technologies: A conceptual framework and survey of the state of the art
Authors: Hamm, J
Money, AG
Atwal, A
Paraskevopoulos, I
Keywords: Falls prevention;Technology-based interventions;Conceptual framework;Collaborative care;Healthcare;Self-care
Issue Date: 2016
Publisher: Elsevier
Citation: Journal of Biomedical Informatics, 59: pp. 319–345, (2016)
Abstract: In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.
ISSN: 1532-0480
Appears in Collections:Dept of Computer Science Research Papers

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