Evaluating Body Movement and Breathing Signals for Identification of Sleep/Wake States
Gaiduk M, Seepold R, Madrid NM, Penzel T, Weber L, Conti M, Orcioni S, Ortega JA (2022)
Publication Type: Conference contribution
Publication year: 2022
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 866 LNEE
Pages Range: 206-211
Conference Proceedings Title: Lecture Notes in Electrical Engineering
Event location: Virtual, Online
ISBN: 9783030954970
DOI: 10.1007/978-3-030-95498-7_29
Abstract
Recognition of sleep and wake states is one of the relevant parts of sleep analysis. Performing this measurement in a contactless way increases comfort for the users. We present an approach evaluating only movement and respiratory signals to achieve recognition, which can be measured non-obtrusively. The algorithm is based on multinomial logistic regression and analyses features extracted out of mentioned above signals. These features were identified and developed after performing fundamental research on characteristics of vital signals during sleep. The achieved accuracy of 87% with the Cohen’s kappa of 0.40 demonstrates the appropriateness of a chosen method and encourages continuing research on this topic.
Involved external institutions
Hochschule Konstanz University of Applied Sciences (HTWG)
Germany (DE)
I.M. Sechenov First Moscow State Medical University
Russian Federation (RU)
Charité - Universitätsmedizin Berlin
Germany (DE)
Università Politecnica delle Marche (UNIVPM) / Marche Polytechnic University
Italy (IT)
University of Seville / Universidad de Sevilla
Spain (ES)
Germany (DE)
I.M. Sechenov First Moscow State Medical University
Russian Federation (RU)
Charité - Universitätsmedizin Berlin
Germany (DE)
Università Politecnica delle Marche (UNIVPM) / Marche Polytechnic University
Italy (IT)
University of Seville / Universidad de Sevilla
Spain (ES)
How to cite
APA:
Gaiduk, M., Seepold, R., Madrid, N.M., Penzel, T., Weber, L., Conti, M.,... Ortega, J.A. (2022). Evaluating Body Movement and Breathing Signals for Identification of Sleep/Wake States. In Sergio Saponara, Alessandro De Gloria (Eds.), Lecture Notes in Electrical Engineering (pp. 206-211). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
MLA:
Gaiduk, Maksym, et al. "Evaluating Body Movement and Breathing Signals for Identification of Sleep/Wake States." Proceedings of the International Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2021, Virtual, Online Ed. Sergio Saponara, Alessandro De Gloria, Springer Science and Business Media Deutschland GmbH, 2022. 206-211.
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