arXiv Machine Learning By Minh Ngoc Nguyen, Khai Le-Duc, Tan-Hanh Pham, Trong Nhan Nguyen, Bailey Trang, Ba Kien Tran, Viktor Dremin, Sergei Sokolovsky, Edik Rafailov, Truong-Son Hy

A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors

Read the original on arXiv Machine Learning →

arXiv:2502. 00973v2 Announce Type: replace Abstract: Mental health problems such as stress, anxiety, and depression affect millions of people worldwide.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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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.

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Unit-Independent Low-Rate Wrist GSR Processing for Stress Detection Using Phasic nSCR Features

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