Galvanic Skin Response and Photoplethysmography for Stress Recognition Using Machine Learning and Wearable Sensors

Galvanic Skin Response and Photoplethysmography for Stress Recognition Using Machine Learning and Wearable Sensors

This study investigates stress recognition using galvanic skin response (GSR) and photoplethysmography (PPG) data and machine learning, with a new focus on air raid sirens as a stressor. It bridges laboratory and real-world conditions and highlights the reliability of wearable sensors in dynamic, hi...

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Bibliographic Details
Main Authors: Alina Nechyporenko, Marcus Frohme, Yaroslav Strelchuk, Vladyslav Omelchenko, Vitaliy Gargin, Liudmyla Ishchenko, Victoriia Alekseeva
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
galvanic skin response
photoplethysmography
stress
machine learning
Online Access:https://www.mdpi.com/2076-3417/14/24/11997
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