The Transferable Methodologies of Detection Sleep Disorders Thanks to the Actigraphy Device for Parkinson's Disease Detection

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dc.contributor.authorSkibiƄska, Justynacs
dc.contributor.authorBurget, Radimcs
dc.coverage.issue1cs
dc.coverage.volume2021cs
dc.date.accessioned2022-04-12T10:55:08Z
dc.date.available2022-04-12T10:55:08Z
dc.date.issued2021-06-03cs
dc.description.abstractDue to population aging, society is struggling with an increasing number of patients with neurodegenerative diseases. One of them is Parkinson's disease. Early detection of Parkinson's disease is very important since there is no cure and the treatment is more effective when administered early. Wearable devices can be of great help - they are cheap and reachable, they can last for many days without charging, can provide long time monitoring, and are minimally invasive to human life. In the paper, we briefly desribe the sensors and actigraphs suitable for the analysis of sleep disturbance in Parkinson's patients and noctural symptoms of Parkinson's disease. Moreover, we pointed out how to collect the data and what could have an influence on the final performance of the automatic models. Additionally, as the main aim of this paper, we have analysed and desribed the machine learning algorithms used in the area of analysis accelerometer singla for sleep / awake stages recognition or diseases which manifested in changes in sleep patterns. We though that these algorithms, because of the nature of Parkinon's patients' sleep patterns, will be simultaneously appropriate for the detection of Parkinon's disease.en
dc.formattextcs
dc.format.extent1-11cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationCEUR Workshop Proceedings. 2021, vol. 2021, issue 1, p. 1-11.en
dc.identifier.doi10.5281/zenodo.4947588cs
dc.identifier.issn1613-0073cs
dc.identifier.other171775cs
dc.identifier.urihttp://hdl.handle.net/11012/203011
dc.language.isoencs
dc.publisherCEURcs
dc.relation.ispartofCEUR Workshop Proceedingscs
dc.relation.urihttp://ceur-ws.org/Vol-2880/paper1.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1613-0073/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectmachine learningen
dc.subjectParkinson diseaseen
dc.subjectactigraphyen
dc.subjectwearable deviceen
dc.subjectIoT healthcare deviceen
dc.subjecteHealthen
dc.subjectHealth 4.0en
dc.titleThe Transferable Methodologies of Detection Sleep Disorders Thanks to the Actigraphy Device for Parkinson's Disease Detectionen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-171775en
sync.item.dbtypeVAVen
sync.item.insts2022.04.12 12:55:08en
sync.item.modts2022.04.12 12:15:09en
thesis.grantorVysokĂ© učenĂ­ technickĂ© v Brně. Fakulta elektrotechniky a komunikačnĂ­ch technologiĂ­. Ústav telekomunikacĂ­cs
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