Published September 3, 2026 | Version 1.0.3
Dataset Restricted

A multimodal digital phenotyping dataset for depression and anxiety assessment under free-living conditions

Authors/Creators

  • 1. ROR icon VinUniversity
  • 2. RMIT University Vietnam
  • 3. ROR icon Ho Chi Minh City International University
  • 4. ROR icon Vietnam National University Ho Chi Minh City
  • 5. Nguyen Tri Phuong Hospital
  • 6. ROR icon Université Grenoble Alpes

Description

ABSTRACT: Despite affecting hundreds of millions of people globally, depression and anxiety remain understudied through digital phenotyping in resource-constrained settings, where limited clinical capacity highlights the need for scalable monitoring. In this work, we present Neurai-VN, a multimodal dataset from a Vietnamese population integrating passive sensing and active assessments across multiple temporal scales. Data were collected from 100 Vietnamese adults recruited from the general population over two weeks. Participants were grouped into four mutually exclusive diagnostic groups based on clinical assessments: depressive disorders, anxiety disorders, healthy controls, and other psychiatric conditions. The dataset contains (1) wearable signals and smartphone-derived data captured under free-living conditions; (2) clinical assessment data, including DSM-5-based psychiatric diagnoses and symptom severity ratings; and (3) longitudinal self-reports, including PHQ-9, GAD-7, daily symptom reports, and mood logs. Overall, the released dataset contains 1,730 participant-day records from 13 passive sensing modalities and 3,581 self-report records. The Neurai-VN dataset provides a resource for reproducible computational analyses and machine learning research on multimodal digital phenotyping for mental health-related outcomes.

Latest Update: Version 1.0.3, released 2026-09-03 (DOI: 10.5281/zenodo.22311204) 

Notes (English)

Notes:

  • This dataset is currently under preparation for submission to Sci. Data. A peer-reviewed publication associated with this dataset will be linked upon publication.
  • Users are encouraged to use the dataset for research and educational purposes in multimodal machine learning and mental health digital phenotyping.
  • Due to the sensitive nature of the human physiological and behavioral data, users must submit an access request (via Zenodo) and sign a Data Use Agreement (DUA) before downloading the dataset. Users are requested to cite the Zenodo record (DOI) in any resulting work(s).

Contact:  

  • For technical inquiries, please email to: 24cuong.pq@vinuni.edu.vn

Files

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We encourage students, researchers, and other qualified users to explore and make use of this dataset for scientific and related research purposes. We ask all users to handle the data responsibly and in accordance with the DUA and applicable data protection requirements.

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Additional details

Software

Repository URL
https://github.com/neurai-vn/Neurai-VN-data-descriptor