ArticleJournal of medical Internet research2023
Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 44 papers, 3 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
44 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Effectiveness of Wearable Digital Therapeutics in Improving Sleep Outcomes Among Individuals With Insomnia: Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- Speech analysis for detecting depression in older adults: a systematic review.Frontiers in psychology · 2025Pooled it
- The Performance of Wearable AI in Detecting Stress Among Students: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Evaluating a Mobile Digital Therapeutic for Vasomotor and Behavioral Health Symptoms Among Women in Midlife: Randomized Controlled Trial.JMIR mHealth and uHealth · 2025Trial
- Integration of Ecological Momentary Assessment and Intervention With Wearable-Based Digital Phenotypes to Treat Anxiety in Young Adults: Mixed Methods Experimental Study.JMIR mHealth and uHealth · 2026Article
- Intelligent Real-Time Healthcare and Biomedical Monitoring Systems: A Narrative Review of AI, IoT, and Emerging Technologies.Bioengineering (Basel, Switzerland) · 2026Review
- Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data.Scientific reports · 2026Article
- AI in Mental Health: Transforming Diagnosis and Management of Depression and Anxiety.Health science reports · 2026Article
- Sensor-Equipped Digital Technologies for Monitoring and Detecting Depressive Disorders: A Systematic Review.Health science reports · 2026Review
- Artificial Intelligence for Mental Health Monitoring: A Solution for Digital Behavioral Health Care and Education-An Umbrella Review.Health science reports · 2026Review
- Digital Therapeutics and Blended Care in Major Depressive Disorder: Current Evidence and Future Directions.Advances in experimental medicine and biology · 2026Review
- Music-evoked EEG signals for mental health assessment using two- and three-class classification.Frontiers in systems neuroscience · 2026Article
- HMDF-Net: a transfer learning-based heterogeneous multimodal dynamic fusion network for depression detection among inmates in correctional facilities.Frontiers in psychiatry · 2026Article
- Advancing mental health diagnostics: a review on the role of smartphones, wearable devices, and artificial intelligence in depression and anxiety detection.Biomedical engineering letters · 2025Review
- Integrating artificial intelligence with nanodiagnostics for early detection and precision management of neurodegenerative diseases.Journal of nanobiotechnology · 2025Review
- Explainable AI for Depression Detection and Severity Classification From Activity Data: Development and Evaluation Study of an Interpretable Framework.JMIR mental health · 2025Article
- Wearable devices in neurological disorders: a narrative review of status quo and perspectives.Annals of translational medicine · 2025Review
- The effects of multi-sensory public seating on emotion regulation in youth communities.Scientific reports · 2025Article
- Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review.Journal of medical Internet research · 2025Article
- Wearable Artificial Intelligence for Sleep Disorders: Scoping Review.Journal of medical Internet research · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence (AI) into wearable devices (wearable AI) has been exploited to provide mental health services.
objectiveThis review aimed to explore the features of wearable AI used for anxiety and depression to identify application areas and open research issues.
methodsWe searched 8 electronic databases (MEDLINE, PsycINFO, Embase, CINAHL, IEEE Xplore, ACM Digital Library, Scopus, and Google Scholar) and included studies that met the inclusion criteria. Then, we checked the studies that cited the included studies and screened studies that were cited by the included studies. The study selection and data extraction were carried out by 2 reviewers independently. The extracted data were aggregated and summarized using narrative synthesis.
resultsOf the 1203 studies identified, 69 (5.74%) were included in this review. Approximately, two-thirds of the studies used wearable AI for depression, whereas the remaining studies used it for anxiety. The most frequent application of wearable AI was in diagnosing anxiety and depression; however, none of the studies used it for treatment purposes. Most studies targeted individuals aged between 18 and 65 years. The most common wearable device used in the studies was Actiwatch AW4 (Cambridge Neurotechnology Ltd). Wrist-worn devices were the most common type of wearable device in the studies. The most commonly used category of data for model development was physical activity data, followed by sleep data and heart rate data. The most frequently used data set from open sources was Depresjon. The most commonly used algorithm was random forest, followed by support vector machine.
conclusionsWearable AI can offer great promise in providing mental health services related to anxiety and depression. Wearable AI can be used by individuals for the prescreening assessment of anxiety and depression. Further reviews are needed to statistically synthesize the studies' results related to the performance and effectiveness of wearable AI. Given its potential, technology companies should invest more in wearable AI for the treatment of anxiety and depression.
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Registered trials
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.