Recognition of sleep/wake states analyzing heart rate, breathing and movement signals : Fachvortrag

  • This document presents an algorithm for a non-obtrusive recognition of Sleep/Wake states using signals derived from ECG, respiration, and body movement captured while lying in a bed. As a core mathematical base of system data analytics, multinomial logistic regression techniques were chosen. Derived parameters of the three signals are used as the input for the proposed method. The overall achieved accuracy rate is 84% for Wake/Sleep stages, with Cohen’s kappa value 0.46. The presented algorithm should support experts in analyzing sleep quality in more detail. The results confirm the potential of this method and disclose several ways for its improvement.

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Metadaten
Author:Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Thomas PenzelORCiDGND, Juan Antonio OrtegaORCiD, Martin GlosGND, Natividad Martínez MadridORCiD
Parent Title (English):41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019), 23-27 July 2019, Messe Berlin, Germany
Document Type:Conference Proceeding
Language:English
Year of Publication:2019
Release Date:2019/09/10
Tag:Multinomial logistic regression; Sleep study; Sleep/Wake states
Institutes:Fakultät Informatik
Open Access?:Nein
Relevance:Externer wissenschaftlicher Fachvortrag oder Poster