Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/186185
Full metadata record
DC FieldValueLanguage
dc.contributor.authorFerrer Lluis, Ignasi-
dc.contributor.authorCastillo Escario, Yolanda-
dc.contributor.authorMontserrat, Josep Maria-
dc.contributor.authorJané, Raimon-
dc.date.accessioned2022-06-01T10:56:24Z-
dc.date.available2022-06-01T10:56:24Z-
dc.date.issued2021-07-01-
dc.identifier.issn1424-8220-
dc.identifier.urihttp://hdl.handle.net/2445/186185-
dc.description.abstractPoor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep position affects the severity and occurrence of these complications, and positional therapy is one of the less invasive treatments to deal with them. Sleep positions can be self-reported, which is unreliable, or determined by using specific devices, such as polysomnography, polygraphy or cameras, that can be expensive and difficult to employ at home. The aim of this study is to determine how smartphones could be used to monitor and treat sleep position at home. We divided our research into three tasks: (1) develop an Android smartphone application (‘SleepPos’ app) which monitors angle-based high-resolution sleep position and allows to simultaneously apply positional treatment; (2) test the smartphone application at home coupled with a pulse oximeter; and (3) explore the potential of this tool to detect the positional occurrence of desaturation events. The results show how the ‘SleepPos’ app successfully determined the sleep position and revealed positional patterns of occurrence of desaturation events. The ‘SleepPos’ app also succeeded in applying positional therapy and preventing the subjects from sleeping in the supine sleep position. This study demonstrates how smartphones are capable of reliably monitoring high-resolution sleep position and provide useful clinical information about the positional occurrence of desaturation events.-
dc.format.extent22 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherMDPI-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3390/s21134531-
dc.relation.ispartofSensors, 2021, vol. 21, num.13, p. 4531-
dc.relation.urihttps://doi.org/10.3390/s21134531-
dc.rightscc by (c) Ferrer Lluis, Ignasi et al., 2021-
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.sourceArticles publicats en revistes (Institut de Bioenginyeria de Catalunya (IBEC))-
dc.subject.classificationTelèfons intel·ligents-
dc.subject.classificationEnginyeria biomèdica-
dc.subject.classificationSon-
dc.subject.otherSmartphones-
dc.subject.otherBiomedical engineering-
dc.subject.otherSleep-
dc.titleSleeppos app: An automated smartphone application for angle based high resolution sleep position monitoring and treatment-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.date.updated2022-06-01T06:39:24Z-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/713673/EU//INPhINIT-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.idimarina6519606-
dc.identifier.pmid34282793-
Appears in Collections:Articles publicats en revistes (Institut de Bioenginyeria de Catalunya (IBEC))

Files in This Item:
File Description SizeFormat 
2021_Sensors_SleepPos_Jane.pdf3.49 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons