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Initial evaluation of substituting a sleep diary by smartwatch measurement

  • Healthy sleep is required for sufficient restoration of the human body and brain. Therefore, in the case of sleep disorders, appropriate therapy should be applied timely, which requires a prompt diagnosis. Traditionally, a sleep diary is a part of diagnosis and therapy monitoring for some sleep disorders, such as cognitive behaviour therapy for insomnia. To automatise sleep monitoring and make it more comfortable for users, substituting a sleep diary with a smartwatch measurement could be considered. With the aim of providing accurate results, a study with a total of 30 night recordings was conducted. Objective sleep measurement with a Samsung Galaxy Watch 4 was compared with a subjective approach (sleep diary), evaluating the four relevant sleep characteristics: time of getting asleep, wake up time, sleep efficiency (SE), and total sleep time (TST). The performed analysis has demonstrated that the median difference between both measurement approaches was equal to 7 and 3 minutes for a time of getting asleep and wake up time correspondingly, which allows substituting a subjective measurement with a smartwatch. The SE was determined with a median difference between the two measurement methods of 5.22%. This result also implicates a possibility of substitution. Some single recordings have indicated a higher variance between the two approaches. Therefore, the conclusion can be made that a substitution provides reliable results primarily in the case of long-term monitoring. The results of the evaluation of the TST measurement do not allow to recommend substitution of the measurement method.

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Metadaten
Author:Maksym GaidukORCiD, Ralf SeepoldORCiDGND, Natividad Martínez MadridORCiD, Simone OrcioniORCiD, Massimo ContiORCiD, Juan Antonio OrtegaORCiD
DOI:https://doi.org/10.1016/j.procs.2022.09.396
ISSN:1877-0509
Parent Title (English):Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference, KES2022, 7 - 9 September 2022, Verona, Italy (Procedia Computer Science)
Volume:207
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Conference Proceeding
Language:English
Year of Publication:2022
Release Date:2022/11/14
Tag:Sleep diary; Sleep study; Wearable
First Page:3370
Last Page:3377
Note:
Corresponding author: Maksym Gaiduk
Institutes:Institut für Angewandte Forschung - IAF
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