Wearable activity trackers, accuracy, adoption, acceptance and health impact: A systematic literature review
Open accessAbstract
Wearable activity trackers (WAT) are electronic monitoring devices that enable users to track and monitor their health-related physical fitness metrics including steps taken, level of activity, walking distance, heart rate, and sleep patterns. Despite the proliferation of these devices in various contexts of use and rising research interests, there is limited understanding of the broad research landscape. The purpose of this systematic review is therefore to synthesize the existing wealth of research on WAT, and to provide a comprehensive summary based on common themes and approaches. This article includes academic work published between 2013 and 2017 in PubMed, Embase, Scopus, Web of Science, ACM Digital Library, and Google Scholar. A final list of 463 articles was analyzed for this review. Topic modeling methods were used to identify six key themes (topics) of WAT research, namely: (1) Technology Focus, (2) Patient Treatment and Medical Settings, (3) Behavior Change, (4) Acceptance and Adoption (Abandonment), (5) Self-monitoring Data Centered, and (6) Privacy. We take an interdisciplinary approach to wearable activity trackers to propose several new research questions. The most important research gap we identify is to attempt to understand the rich human-information interaction that is enabled by WAT adoption.
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Demand for wearable devices has risen substantially in recent years.
“Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen considerably in the last few years [1-3].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [3]
Many studies have focused on novel technologies, presenting prototypes, or investigating feasibility and acceptance of a wearable device in a specific setting.
“Many studies have focused on novel technologies, presenting prototypes, or investigating the feasibility and acceptance of a wearable device in a specific setting [3,27].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [3]
Similar to other reviews, most devices were wrist-worn fitness trackers and accelerometers, and most were from Fitbit, measuring PA, HR, and sleep.
“Similar to other reviews, most devices were wrist-worn fitness trackers and accelerometers, and most of them are from the company Fitbit, measuring PA, HR, and sleep [3,27,31,224,225].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [3]
These vital signs and device types seem to become the standard in wearable research.
“These vital signs and device types seem to become the standard in wearable research [3,27,31,224,225].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [3]
There is a positive trend in wearable studies, underlining growing interest in wearables in health research.
“Overall, we have identified a positive trend in wearable studies, underlining the growing interest in wearables in health research, in line with other reviews [3,224-226].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [3]
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- Authors
- Shin, G., Jarrahi, M. H., Fei, Y., Karami, A., Gafinowitz, N., Byun, A., & Lu, X.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of South Carolina (US)
- Seoul National University (KR)
- Corresponding author
- Shin, Grace
- Venue
- Journal of Biomedical Informatics
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 93
- Pages
- 103153
- ISSN
- 1532-0464 (ISSN-L)
- OpenAlex
- W2927358919
- Cited by
- 326
- References
- 182
- Citations by year
- 2026: 23 · 2025: 45 · 2024: 45 · 2023: 47 · 2022: 52 · 2021: 63 · 2020: 42 · 2019: 9
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Biomedical Informatics (publishedVersion)
- PubMed (publishedVersion)
- Scholar Commons (University of South Carolina) (submittedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- wearable activity trackers, physical activity monitoring, device accuracy, technology adoption, user acceptance, abandonment, behavior change, self-monitoring, privacy, human-computer interaction, health effects, wearable sensors
- MeSH terms
- Fitness Trackers, Adult, Diffusion of Innovation, Humans, Patient Acceptance of Health Care
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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.
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