A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors
Please press ⭐ button and/or cite papers if you feel helpful.
This repository contains the codebase and dataset for the paper: A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors
https://arxiv.org/abs/2502.00973
Abstract: In this study, we introduce a novel method to predict mental health by building machine learning models for a non-invasive wearable device equipped with Laser Doppler Flowmetry (LDF) and Fluorescence Spectroscopy (FS) sensors. Besides, we present the corresponding dataset to predict mental health, e.g. depression, anxiety, and stress levels via the DAS-21 questionnaire. To our best knowledge, this is the world's largest and the most generalized dataset ever collected for both LDF and FS studies. The device captures cutaneous blood microcirculation parameters, and wavelet analysis of the LDF signal extracts key rhythmic oscillations. The dataset, collected from 132 volunteers aged 18-94 from 19 countries, explores relationships between physiological features, demographics, lifestyle habits, and health conditions. We employed a variety of machine learning methods to classify stress detection, in which LightGBM is identified as the most effective model for stress detection, achieving a ROC AUC of 0.7168 and a PR AUC of 0.8852. In addition, we also incorporated Explainable Artificial Intelligence (XAI) techniques into our analysis to investigate deeper insights into the model's predictions. Our results suggest that females, younger individuals and those with a higher Body Mass Index (BMI) or heart rate have a greater likelihood of experiencing mental health conditions like stress and anxiety. All related code and data are published online: https://github.com/leduckhai/Wearable_LDF-FS
This repository provides the necessary scripts, configurations, setup instructions, and dataset to reproduce the experiments discussed in the paper.
@article{nguyen2025wearable,
title={A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors},
author={Nguyen, Minh Ngoc and Le-Duc, Khai and Pham, Tan-Hanh and Nguyen, Trang and Luu, Quang Minh and Tran, Ba Kien and Hy, Truong-Son and Dremin, Viktor and Sokolovsky, Sergei and Rafailov, Edik},
journal={arXiv preprint arXiv:2502.00973},
year={2025}
}Core developers:
Khai Le-Duc
University of Toronto, Canada
Email: duckhai.le@mail.utoronto.ca
GitHub: https://github.com/leduckhai
Tan-Hanh Pham
Florida Institute of Technology, USA
GitHub: https://github.com/Hanhpt23
Personal page: https://hanhpt23.github.io