Fine-Grained Sleep-Wake Behaviour Analysis

Sarah Fallmann, Liming Chen, Feng Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Sleep stages are traditionally assessed by experts from polysomnography measurements following specific guidelines. Sleep stage behaviour is subsequently used to detect anomalies and diagnose diseases in a laboratory setting. Recently, with the development of Internet of Things, there is a trend to use everyday technologies for sleep behaviour analysis at home, having the potential to eliminate expensive in-hospital monitoring. We propose a fine-grained sleep-wake behaviour analysis approach, which takes into consideration the influences of various factors, such as gender, health status and race. In addition, we investigate the combination of multiple data sources, in particular, actigraphy and heart rate variability, for enhancing model accuracy. Initial results show the proposed approach is recognising sleep and wake stages accurately and is providing a flexible recognition approach towards personalised sleep-based health monitoring.
Original languageEnglish
Title of host publication2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Place of PublicationLeicester, UK
PublisherIEEE Xplore
Pages667-674
Number of pages7
ISBN (Electronic)978-1-7281-4034-6
ISBN (Print)978-1-7281-4035-3
DOIs
Publication statusPublished - 19 Aug 2019
Event2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) - Leicester, United Kingdom
Duration: 19 Aug 201923 Aug 2019

Conference

Conference2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Period19/08/1923/08/19

Keywords

  • Diseases
  • electrocardiography
  • medical signal detection
  • medical signal processing
  • patient monitoring
  • sleep

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