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Accelerometer based system for unobtrusive sleep apnea detection

  • Sleep is an essential part of human existence, as we are in this state for approximately a third of our lives. Sleep disorders are common conditions that can affect many aspects of life. Sleep disorders are diagnosed in special laboratories with a polysomnography system, a costly procedure requiring much effort for the patient. Several systems have been proposed to address this situation, including performing the examination and analysis at the patient's home, using sensors to detect physiological signals automatically analysed by algorithms. This work aims to evaluate the use of a contactless respiratory recording system based on an accelerometer sensor in sleep apnea detection. For this purpose, an installation mounted under the bed mattress records the oscillations caused by the chest movements during the breathing process. The presented processing algorithm performs filtering of the obtained signals and determines the apnea events presence. The performance of the developed system and algorithm of apnea event detection (average values of accuracy, specificity and sensitivity are 94.6%, 95.3%, and 93.7% respectively) confirms the suitability of the proposed method and system for further ambulatory and in-home use.

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Metadaten
Author:Andrei BoikoORCiD, Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Natividad Martínez MadridORCiD
DOI:https://doi.org/10.1016/j.procs.2023.10.148
ISSN:1877-0509
Parent Title (English):27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES2023, 6 - 8 September, Athens, Greece (Procedia Computer Science, Vol. 225)
Volume:225
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Conference Proceeding
Language:English
Year of Publication:2023
Release Date:2023/12/14
Tag:Contactless measurement; Accelerometer; Vital signals; Health monitoring; Sleep apnea
First Page:1592
Last Page:1600
Note:
Corresponding author: Andrei Boiko
Institutes:Institut für Angewandte Forschung - IAF
DDC functional group:500 Naturwissenschaften und Mathematik
600 Technik, Medizin, angewandte Wissenschaften
Open Access?:Ja
Relevance:Peer reviewed nach anderen Listungen (mit Nachweis zum Peer Review Verfahren)
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International