arXiv AI
Aug 5
From Wearable Data to Personalized and Actionable Health Insights
arXiv:2608. 03251v1 Announce Type: cross Abstract: Commercial wearable devices continuously capture rich physiological data (e.
A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors
arXiv:2502. 00973v2 Announce Type: replace Abstract: Mental health problems such as stress, anxiety, and depression affect millions of people worldwide.
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Hugging Face Trending Papers
Aug 4
From Wearable Data to Personalized and Actionable Health Insights
Commercial wearable devices continuously capture rich physiological data (e. g.
arXiv Computation and Language
Sep 7
WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data
WearableQA is a new benchmark that tests AI systems on health reasoning using real-world wearable data from 200 users, each with up to 500 days of daily measurements. It contains 4,084 ten‑option multiple‑choice questions derived from wearable time series, blood biomarkers, and demographics, and is organized into 16 question types that distinguish data‑driven computation from physiological interpretation and single‑signal from cross‑signal reasoning. Evaluation of 14 large language models shows wide performance gaps, indicating that the benchmark remains challenging and useful for diagnosing model capabilities.
arXiv AI
Jun 2
A Foundation Model for Wearable Movement Data in Mental Health Research
arXiv:2411. 15240v5 Announce Type: replace-cross Abstract: Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflecting fine-grained temporal behavioral trends.
Hugging Face Trending Papers
Jul 9
Unit-Independent Low-Rate Wrist GSR Processing for Stress Detection Using Phasic nSCR Features
Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ substantially from laboratory-grade palmar measurements. In this paper, we propose a unit-independent low-rate wrist GSR processing pipeline to extract the number of skin conductance responses per minute (nSCR/min) as a stress-related feature.
arXiv Machine Learning
Jul 10
Unit-Independent Low-Rate Wrist GSR Processing for Stress Detection Using Phasic nSCR Features
arXiv:2607. 08007v1 Announce Type: cross Abstract: Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ substantially from laboratory-grade palmar measurements.
arXiv AI
Jun 11
End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS
arXiv:2606. 11555v1 Announce Type: cross Abstract: The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics.
arXiv Machine Learning
Aug 7
A Low-Power Wearable Respiratory Sensor for Non-Invasive Stress Monitoring
arXiv:2608. 05697v1 Announce Type: cross Abstract: Respiration provides a continuously available window into physiological state and behavior.
arXiv Computation and Language
Aug 28
Towards Interpretable Depression Detection: Linking Acoustic Features to DSM-5 Indicators
The paper proposes a transparent framework that links speech acoustic features—such as pitch variability, pauses, and speech tempo—to DSM‑5 indicators of depression, offering interpretable, indicator‑level outputs instead of opaque black‑box models. It runs locally on commodity hardware to preserve privacy and has been preliminarily evaluated on the DAIC‑WOZ dataset, showing consistent associations between acoustic cues and DSM‑5 indicators of psychomotor change and concentration difficulty. Future work aims to validate the approach on longitudinal data and expand multimodal integration while keeping edge constraints.
arXiv Machine Learning
Aug 10
Neurai-VN Benchmark: Standardized Machine Learning Models for Multimodal Digital Phenotyping in Mental Health Classification
arXiv:2607. 25232v2 Announce Type: replace Abstract: Digital phenotyping (DP) using smartphones and wearable devices has shown considerable potential for mental health monitoring.
arXiv Machine Learning
Aug 11
Deep Multimodal Wearable Sensor Fusion for Detection of Body-Focused Repetitive Behaviors
arXiv:2608. 09830v1 Announce Type: new Abstract: Body-focused repetitive behaviors, such as hair pulling and skin picking, are compulsive motor actions commonly associated with obsessive-compulsive and anxiety disorders.
arXiv AI
Jul 24
HiMe: Real-Time Self-Hosted Personal Agent Platform for Health Insights with Wearable Devices
arXiv:2607. 21019v1 Announce Type: new Abstract: Traditional approaches to wearable health signal analysis, such as smartwatches, are constrained by rigid analytical frameworks and limited personalisation.