Clinical Applications of Mobile Health Wearable–Based Sleep Monitoring: Systematic Review
Open accessPublished version of a preprint
Abstract
Background: Sleep disorders are a major public health issue. Nearly 1 in 2 people experience sleep disturbances during their lifetime, with a potential harmful impact on well-being and physical and mental health. Objective: The aim of this study was to better understand the clinical applications of wearable-based sleep monitoring; therefore, we conducted a review of the literature, including feasibility studies and clinical trials on this topic. Methods: We searched PubMed, PsycINFO, ScienceDirect, the Cochrane Library, Scopus, and the Web of Science through June 2019. We created the list of keywords based on 2 domains: wearables and sleep. The primary selection criterion was the reporting of clinical trials using wearable devices for sleep recording in adults. Results: The initial search identified 645 articles; 19 articles meeting the inclusion criteria were included in the final analysis. In all, 4 categories of the selected articles appeared. Of the 19 studies in this review, 58 % (11/19) were comparison studies with the gold standard, 21% (4/19) were feasibility studies, 15% (3/19) were population comparison studies, and 5% (1/19) assessed the impact of sleep disorders in the clinic. The samples were heterogeneous in size, ranging from 1 to 15,839 patients. Our review shows that mobile-health (mHealth) wearable–based sleep monitoring is feasible. However, we identified some major limitations to the reliability of wearable-based monitoring methods compared with polysomnography. Conclusions: This review showed that wearables provide acceptable sleep monitoring but with poor reliability. However, wearable mHealth devices appear to be promising tools for ecological monitoring.
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?
Other more complex sensing modalities such as EEG and EOG are less employed in consumer wearable and mobile devices, rather in only clinical devices that limit their employment.
“Apart from these two types of sensors, there are also other more complex sensing modalities such as electroencephalography (EEG) and electrooculography (EOG) [171], e.g. for sleep monitoring, but they are less employed in consumer wearable and mobile devices, rather in only clinical devices that limit their employment.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [171]
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 49 · Cited by 167
Research works printed but not linked: 1
- [3]World Health Organization International Statistical Classification of Diseases and Related Health Problems. 10th Revision. Fifth Edition 2016 Geneva, Switzerland World Health Organization
- Authors
- Guillodo, E., Lemey, C., Simonnet, M., Walter, M., Baca-García, E., Masetti, V., Moga, S., Larsen, M., HUGOPSY Network, Ropars, J., & Berrouiguet, S.
- Affiliations
- Université de Bretagne Occidentale (FR)
- IMT Atlantique (FR)
- Black Dog Institute (AU)
- Inserm (FR)
- ORCID
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2020-04-01
- Volume
- 8
- Issue
- 4
- Pages
- e10733
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC7160700
- OpenAlex
- W2981705411
- Cited by
- 167
- References
- 49
- Citations by year
- 2026: 19 · 2025: 30 · 2024: 33 · 2023: 35 · 2022: 25 · 2021: 15 · 2020: 10
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion)
- UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
- Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, public-domain)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Hispana (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Physiology › Obstructive Sleep Apnea Research
- Keywords
- wearable devices, sleep monitoring, mobile health, sleep disorders, polysomnography comparison, feasibility, ecological monitoring, clinical application
- MeSH terms
- Wearable Electronic Devices, Adolescent, Adult, Humans, Sleep, Reproducibility of Results, Telemedicine, Polysomnography
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
