Mobile Data Collection for Depression Analysis: An App Framework for Monitoring Mood and Depression Using Smartphone and Wearable Data

Eliane Schröter, Franziska Klein, Patrick Elfert, Fynn Bredehorn, Julien Räker, Frerk Aschwege, Andreas Hein, Andreas Hein

2025

Abstract

Depression is a leading cause of disability worldwide, affecting around 5% of the global adult population. To address this problem, researchers are exploring methods for early detection of relapses, mood swings and their relation with health data and external influences. The aim of the present study was to evaluate the usability and feasibility of a mobile application designed for active and passive data collection, with potential future applications for improving mental healthcare through a virtual therapy assistant. The application allows users to self-report their mood, complete PHQ-9 questionnaires, and track measures such as sleep, physical activity, location, smartphone usage, and social media engagement. A six-week pilot study was conducted with 22 healthy participants (68% male, 32% female). Participants recorded their mood three times a day and completed weekly mental health assessments. Results showed that the application effectively collected relevant data and was user friendly. However, limitations included reliance on self-reported data, short study duration, and occasional technical issues with data collection. Despite these limitations, the study showed that it is possible to use smartphones and wearable technologies to monitor mental health, laying the foundation for future developments in digital therapeutic interventions and personalized healthcare through app-based virtual therapy assistants.

Paper Citation

in Harvard Style

Schröter E., Klein F., Elfert P., Bredehorn F., Räker J., Aschwege F. and Hein A. (2025). Mobile Data Collection for Depression Analysis: An App Framework for Monitoring Mood and Depression Using Smartphone and Wearable Data. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-731-3, SciTePress, pages 781-788. DOI: 10.5220/0013298700003911

in Bibtex Style

@conference{healthinf25,
author={Eliane Schröter and Franziska Klein and Patrick Elfert and Fynn Bredehorn and Julien Räker and Frerk Aschwege and Andreas Hein},
title={Mobile Data Collection for Depression Analysis: An App Framework for Monitoring Mood and Depression Using Smartphone and Wearable Data},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2025},
pages={781-788},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013298700003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Mobile Data Collection for Depression Analysis: An App Framework for Monitoring Mood and Depression Using Smartphone and Wearable Data
SN - 978-989-758-731-3
AU - Schröter E.
AU - Klein F.
AU - Elfert P.
AU - Bredehorn F.
AU - Räker J.
AU - Aschwege F.
AU - Hein A.
PY - 2025
SP - 781
EP - 788
DO - 10.5220/0013298700003911
PB - SciTePress