The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 1 of 144
Back to Result List

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

  • 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.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Thomas PenzelORCiDGND, Juan Antonio OrtegaORCiD, Martin GlosGND, Natividad Martínez MadridORCiD
DOI:https://doi.org/10.1109/EMBC.2019.8857596
ISBN:978-1-5386-1311-5
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
Publisher:IEEE
Document Type:Conference Proceeding
Language:English
Year of Publication:2019
Release Date:2019/09/10
Tag:Multinomial logistic regression; Sleep study; Sleep/Wake states
First Page:5712
Last Page:5715
Note:
Volltextzugriff für Angehörige der Hochschule Konstanz via IEEE Xplore möglich
Institutes:Fakultät Informatik
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (English):License LogoLizenzbedingungen IEEE