The Effect of Sleep Disturbances on the Quality of Sleep: An Adaptive Computational Network Model

Quentin Lee Hee, Lorenzo Hogendorp, Daan Warnaars, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper, an adaptive temporal-causal network model is presented for a normal night’s sleep and for how disturbances and their timing interfere with such a normal night of sleep. The goal of this computational model is to explore the area of how sleep disturbances influence a person’s health. This was achieved by simulating single and multiple sleep disturbances during sleep episodes and measuring the effect on light, deep, and REM sleep. The main finding from the simulated scenarios in this study is that disturbances, depending on their timing, can cause a lack of deep and/or REM sleep. This implies that sleep disturbances might lead to insufficient physical and/or emotional recovery.

Original languageEnglish
Title of host publicationProceedings of the Second International Conference on Innovations in Computing Research (ICR’23)
EditorsKevin Daimi, Abeer Al Sadoon
PublisherSpringer Science and Business Media Deutschland GmbH
Pages105-117
Number of pages13
ISBN (Electronic)9783031353086
ISBN (Print)9783031353079
DOIs
Publication statusPublished - 2023
Event2nd International Conference on Innovations in Computing Research, ICR 2023 - Madrid, Spain
Duration: 4 Sept 20236 Sept 2023

Publication series

NameLecture Notes in Networks and Systems
Volume721 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference2nd International Conference on Innovations in Computing Research, ICR 2023
Country/TerritorySpain
CityMadrid
Period4/09/236/09/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Hypnogram
  • Recovery
  • Sleep disturbances
  • Sleep model
  • Sleep quality
  • Sleep stages

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