Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Devices capable of detailed functional assessment, such as the VICON and ViMove, are efficient at collecting data related to standardised functional tests in a clinical setting or in an ambulatory environment.
“Devices capable of detailed functional assessment, such as the VICON and ViMove are efficient at collecting data related to standardised functional tests in a clinical setting or even in an ambulatory environment [39].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [39]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 73 · Cited by 74
- Authors
- Camp, N., Lewis, M., Hunter, K., Johnston, J., Zecca, M., Di Nuovo, A., & Magistro, D.
- Affiliations
- Nottingham Trent University (GB)
- University of Derby (GB)
- Loughborough University (GB)
- Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK
- Corresponding author
- Magistro, Daniele
- ORCID
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2020-12-28
- Volume
- 18
- Issue
- 1
- Pages
- 163
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC7795436
- OpenAlex
- W3114326620
- Cited by
- 74
- References
- 73
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 20 · 2023: 17 · 2022: 18 · 2021: 5
- FWCI
- 0.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
- SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) (acceptedVersion)
- Figshare (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Derby Online Research Archive. (University of Derby) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Social Sciences › Demography › Technology Use by Older Adults
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
- Keywords
- activities of daily living, older adults, community-dwelling, home monitoring, wearable devices, environmental monitoring technology, independent living, caregiver burden, assistive technology
- MeSH terms
- Wearable Electronic Devices, Activities of Daily Living, Aged, Humans, Technology, Independent Living
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
