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dc.contributor.authorCastillo Escario, Yolanda
dc.contributor.authorKumru, Hatice
dc.contributor.authorFerrer Lluís, Ignasi
dc.contributor.authorVidal Samsó, Joan
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Biomèdica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2021-11-09T11:39:18Z
dc.date.available2021-11-09T11:39:18Z
dc.date.issued2021-10-29
dc.identifier.citationCastillo-Escario, Y. [et al.]. Detection of sleep-disordered breathing in patients with spinal cord injury using a smartphone. "Sensors", 29 Octubre 2021, vol. 21, núm. 21, p. 7182:1-7182:19.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2117/355847
dc.description.abstractPatients with spinal cord injury (SCI) have an increased risk of sleep-disordered breathing (SDB), which can lead to serious comorbidities and impact patients’ recovery and quality of life. However, sleep tests are rarely performed on SCI patients, given their multiple health needs and the cost and complexity of diagnostic equipment. The objective of this study was to use a novel smartphone system as a simple non-invasive tool to monitor SDB in SCI patients. We recorded pulse oximetry, acoustic, and accelerometer data using a smartphone during overnight tests in 19 SCI patients and 19 able-bodied controls. Then, we analyzed these signals with automatic algorithms to detect desaturation, apnea, and hypopnea events and monitor sleep position. The apnea–hypopnea index (AHI) was significantly higher in SCI patients than controls (25 ± 15 vs. 9 ± 7, p < 0.001). We found that 63% of SCI patients had moderate-to-severe SDB (AHI = 15) in contrast to 21% of control subjects. Most SCI patients slept predominantly in supine position, but an increased occurrence of events in supine position was only observed for eight patients. This study highlights the problem of SDB in SCI and provides simple cost-effective sleep monitoring tools to facilitate the detection, understanding, and management of SDB in SCI patients.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights©2021. MDPI
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subjectÀrees temàtiques de la UPC::Ciències de la salut::Medicina::Neurologia
dc.subject.lcshSleep disorders
dc.subject.lcshSmartphones
dc.subject.lcshSpinal cord--Wounds and injuries
dc.subject.otherSpinal cord injury
dc.subject.otherSleep-disordered breathing
dc.subject.otherSleep apnea
dc.subject.otherSleep position
dc.subject.otherSmartphone
dc.subject.otherBiomedical signal processing
dc.subject.otherMHealth
dc.subject.otherMonitoring
dc.titleDetection of sleep-disordered breathing in patients with spinal cord injury using a smartphone
dc.typeArticle
dc.subject.lemacTrastorns del son
dc.subject.lemacMedul·la espinal -- Ferides i lesions
dc.subject.lemacTelèfons intel·ligents
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation
dc.identifier.doi10.3390/s21217182
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/21/21/7182
dc.rights.accessOpen Access
local.identifier.drac32187700
dc.description.versionPostprint (published version)
local.citation.authorCastillo-Escario, Y.; Kumru, H.; Ferrer, I.; Vidal, J.; Jane, R.
local.citation.publicationNameSensors
local.citation.volume21
local.citation.number21
local.citation.startingPage7182:1
local.citation.endingPage7182:19


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