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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Principais autores:	Alina Nechyporenko, Marcus Frohme, Yaroslav Strelchuk, Vladyslav Omelchenko, Vitaliy Gargin, Liudmyla Ishchenko, Victoriia Alekseeva
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2024-12-01
Series:	Applied Sciences
Assuntos:	galvanic skin response photoplethysmography stress machine learning
Acceso en liña:	https://www.mdpi.com/2076-3417/14/24/11997
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