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Detection of sleep-disordered breathing in patients with spinal cord injury using a smartphone

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Castillo Escario, YolandaMés informacióMés informació
Kumru, Hatice
Ferrer Lluís, Ignasi
Vidal Samsó, Joan
Jané Campos, RaimonMés informacióMés informacióMés informació
Document typeArticle
Defense date2021-10-29
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 4.0 International
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 4.0 International
Abstract
Patients 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.
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. 
URIhttp://hdl.handle.net/2117/355847
DOI10.3390/s21217182
ISSN1424-8220
Publisher versionhttps://www.mdpi.com/1424-8220/21/21/7182
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  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Articles de revista [1.276]
  • BIOSPIN - Biomedical Signal Processing and Interpretation - Articles de revista [39]
  • Doctorat en Enginyeria Biomèdica - Articles de revista [82]
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