Fine-Grained Sleep-Wake Behaviour Analysis

dc.cclicenceN/Aen
dc.contributor.authorFallmann, Sarah
dc.contributor.authorChen, Liming
dc.contributor.authorChen, Feng
dc.date.acceptance2019-05-26
dc.date.accessioned2020-06-02T09:38:25Z
dc.date.available2020-06-02T09:38:25Z
dc.date.issued2020-04-09
dc.description.abstractSleep 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.en
dc.funderEuropean Union (EU) Horizon 2020en
dc.identifier.citationFallmann, S., Chen, L. and Chen, F. (2020) Fine-Grained Sleep-Wake Behaviour Analysis. 2019 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, 2019, pp. 667-674en
dc.identifier.doihttps://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00150
dc.identifier.isbn9781728140346
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/19686
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidNo. 676157.en
dc.publisherIEEEen
dc.researchinstituteCyber Technology Institute (CTI)en
dc.titleFine-Grained Sleep-Wake Behaviour Analysisen
dc.typeConferenceen

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