Evidence map›Paper›PMID 40373307›Full record

ArticleJournal of medical Internet research2025

Recognition of Basic Activities of Daily Living Using Wearable Devices for Older Adults: Scoping Review.

Samantha J Ray, Josh Cherian, Amanda Mae Liberty, Tracy Anne Hammond, Paula K Shireman

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Samantha J RayDepartment of Medical Physiology, College of Medicine, Texas A&M University, Bryan, TX, United States.ORCID https://orcid.org/0000-0003-3189-8899
Josh CherianCenter for Remote Health Monitoring, Department of Biomedical Engineering, School of Medicine, Wake Forest University, Winston-Salem, NC, United States.ORCID https://orcid.org/0000-0002-7749-2109
Amanda Mae LibertyDepartment of Medical Physiology, College of Medicine, Texas A&M University, Bryan, TX, United States.ORCID https://orcid.org/0009-0002-5874-788X
Tracy Anne HammondDepartment of Computer Science & Engineering, Texas A&M University, College Station, TX, United States.ORCID https://orcid.org/0000-0001-7272-0507
Paula K ShiremanDepartment of Medical Physiology, College of Medicine, Texas A&M University, Bryan, TX, United States.ORCID https://orcid.org/0000-0002-9701-5422

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTracking the performance of activities of daily living (ADLs) using ADL recognition has the potential to facilitate aging-in-place strategies, allowing older adults to live in their homes longer and enabling their families and caregivers to monitor changes in health status. However, the ADL recognition literature historically has evaluated systems in controlled settings with data from younger populations, creating the question of whether these systems will work in real-world conditions for older populations.

objectiveThis scoping review seeks to establish the state-of-the-art for recognizing basic ADLs using wearable sensors. This primary goal will identify literature gaps and research needed to make ADL tracking viable for aging-in-place solutions. In addition, this paper will quantify how many publications include older adults. This secondary goal assesses how often studies evaluate their system with older adult participants, enhancing the trustworthiness of the approach.

methodsWe conducted a scoping review using the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines. We identify studies focused on basic ADL recognition using wearable sensors within the PubMed, Association of Computing Machinery Digital Library (ACM DL), and Google Scholar databases using papers published in the last 5 calendar years (2019-2024) to identify current trends given the rapid changes in wearable technology devices. Publications must include at least one of the basic ADLs (ie, bathing, dressing, toileting, transferring, continence, and feeding) and include some sort of wearable sensor or device. Studies focusing on instrumental ADLs, general physical activity tracking, fall detection, or only using environmental devices are excluded. Studies that include older adults in the design or evaluation of their ADL recognition system are highlighted.

resultsThe database search identified 695 papers; 164 papers passed title screening. A total of 58 studies satisfied the inclusion criteria; only 8 studies included older adults despite most studies identifying this population as a focus for their research. Most studies focused on eating (n=27), hygiene (n=24), drinking (n=20), or transitions (n=13). Few works included toileting (n=3), dressing (n=2), or bathing (n=1) activities. Of the 8 studies that included older adults, 5 focused on recognition performance while 3 focused on user experience and system acceptability.

conclusionsBasic ADLs are unevenly covered in the literature; more research is needed for recognizing bathing, dressing, and toileting activities. Despite all studies stating the importance of tracking ADLs in older adults, only 14% (8/58) of the included works involve older adult participants. A commonality between these outcomes is difficulty collecting or obtaining adequate training data for ADL recognition systems. Many works are predominantly concerned with proving system feasibility and do not assess usability or real-world deployment. For these systems to move from academic experiments to actual systems with clinical utility, ADL recognition systems must consider the design requirements of being part of remote health monitoring systems.

Indexed as

Activities of Daily LivingWearable Electronic DevicesAgedHumansIndependent Livingactivities of daily livingactivity recognitionaging in placehealth monitoringwearable sensors

Identifiers

PMID40373307
PMCPMC12123235

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.