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Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

Author

Listed:
  • Nicola Camp

    (Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK)

  • Martin Lewis

    (Department of Sport and Exercise Science, University of Derby, Derby DE22 1GB, UK)

  • Kirsty Hunter

    (Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK)

  • Julie Johnston

    (Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK)

  • Massimiliano Zecca

    (Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK)

  • Alessandro Di Nuovo

    (Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK)

  • Daniele Magistro

    (Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK)

Abstract

The use of technology has been suggested as a means of allowing continued autonomous living for older adults, while reducing the burden on caregivers and aiding decision-making relating to healthcare. However, more clarity is needed relating to the Activities of Daily Living (ADL) recognised, and the types of technology included within current monitoring approaches. This review aims to identify these differences and highlight the current gaps in these systems. A scoping review was conducted in accordance with PRISMA-ScR, drawing on PubMed, Scopus, and Google Scholar. Articles and commercially available systems were selected if they focused on ADL recognition of older adults within their home environment. Thirty-nine ADL recognition systems were identified, nine of which were commercially available. One system incorporated environmental and wearable technology, two used only wearable technology, and 34 used only environmental technologies. Overall, 14 ADL were identified but there was variation in the specific ADL recognised by each system. Although the use of technology to monitor ADL of older adults is becoming more prevalent, there is a large variation in the ADL recognised, how ADL are defined, and the types of technology used within monitoring systems. Key stakeholders, such as older adults and healthcare workers, should be consulted in future work to ensure that future developments are functional and useable.

Suggested Citation

  • Nicola Camp & Martin Lewis & Kirsty Hunter & Julie Johnston & Massimiliano Zecca & Alessandro Di Nuovo & Daniele Magistro, 2020. "Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults," IJERPH, MDPI, vol. 18(1), pages 1-18, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2020:i:1:p:163-:d:469453
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    References listed on IDEAS

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    1. Norbert Noury & Pierre Barralon & Nicolas Vuillerme & Anthony Fleury, 2012. "Fusion of Multiple Sensors Sources in a Smart Home to Detect Scenarios of Activities in Ambient Assisted Living," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 3(3), pages 29-44, July.
    2. Heesook Son & Hyerang Kim, 2019. "A Pilot Study to Test the Feasibility of a Home Mobility Monitoring System in Community-Dwelling Older Adults," IJERPH, MDPI, vol. 16(9), pages 1-16, April.
    3. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
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