Wearable Technology for Depression Assessment: A Scoping Review of Datasets

Authors

• ML Tlachac, Bryant UniversityFollow
• Hayley K. Elsbree, Bryant UniversityFollow
• Michael V. Heinz, Dartmouth-Hitchcock Medical CenterFollow

Document Type

Article

Keywords

digital health; data collection; digital phenotype; depressive disorder; activity tracking

Identifier Data

10.1109/TAFFC.2026.3704930

Publisher

IEEE

Rights Management

Copyright © 2026, IEEE

Abstract

As wearable technology continues to develop, wearable devices are becoming more common and being increasingly used to collect datasets for depression assessment. Documenting the collection procedures, recruitment strategies, and demographics of these datasets is important to allow for synthesis across the datasets and uncover common limitations. As such, in this scoping review, we identify 80 observational datasets collected by wearable devices through the start of 2025 that can be used for depression assessment. Of the 80 datasets, 50% used an actigraph and 47.5% used other wristbands. These wearable devices were used to collect activity, sleep, and heart rate for 87.5%, 69%, and 32.5% of the datasets, respectively. The most administered depression screening instrument, the Hamilton Depression Rating Scale, was only used in 26% of the datasets. Just over half of the datasets recruited patients and just over a fifth of the datasets recruited students. Further, over a tenth of the datasets focused on elderly adults. Excluding the 9% of datasets that did not report gender, 82% reported a majority of women. The collection dates were not available for 44% of the 80 datasets. This scoping review promises to serve as an invaluable resource to the affective research community as wearable technology becomes more ubiquitous and diversified.