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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書誌詳細

主要な著者:	Alina Nechyporenko, Marcus Frohme, Yaroslav Strelchuk, Vladyslav Omelchenko, Vitaliy Gargin, Liudmyla Ishchenko, Victoriia Alekseeva
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-12-01
シリーズ:	Applied Sciences
主題:	galvanic skin response photoplethysmography stress machine learning
オンライン･アクセス:	https://www.mdpi.com/2076-3417/14/24/11997
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