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Snoring analysis for the screening of sleep apnea hypopnea syndrome with a single-channel device developed using polysomnographic and snoring databases
dc.contributor.author | Jané Campos, Raimon |
dc.contributor.author | Fiz Fernández, José Antonio |
dc.contributor.author | Solà Soler, Jordi |
dc.contributor.author | Gil de Mesquita, Joana Margarida |
dc.contributor.author | Morera Prat, Josep Maria |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.contributor.other | Institut de Bioenginyeria de Catalunya |
dc.date.accessioned | 2012-01-11T12:40:58Z |
dc.date.available | 2012-01-11T12:40:58Z |
dc.date.created | 2011 |
dc.date.issued | 2011 |
dc.identifier.citation | Jané, R. [et al.]. Snoring analysis for the screening of sleep apnea hypopnea syndrome with a single-channel device developed using polysomnographic and snoring databases. A: IEEE Engineering in Medicine and Biology Society. "Proceedings of the 33rd Annual International Conference of the IEEE EMBS". Boston: 2011, p. 8331-8333. |
dc.identifier.isbn | 978-1-4244-4122-8 |
dc.identifier.uri | http://hdl.handle.net/2117/14471 |
dc.description.abstract | Several studies have shown differences in acoustic snoring characteristics between patients with Sleep Apnea-Hypopnea Syndrome (SAHS) and simple snorers. Usually a few manually isolated snores are analyzed, with an emphasis on postapneic snores in SAHS patients. Automatic analysis of snores can provide objective information over a longer period of sleep. Although some snore detection methods have recently been proposed, they have not yet been applied to full-night analysis devices for screening purposes. We used a new automatic snoring detection and analysis system to monitor snoring during full-night studies to assess whether the acoustic characteristics of snores differ in relation to the Apnea-Hypopnea Index (AHI) and to classify snoring subjects according to their AHI. A complete procedure for device development was designed, using databases with polysomnography (PSG) and snoring signals. This included annotation of many types of episodes by an expert physician: snores, inspiration and exhalation breath sounds, speech and noise artifacts, The AHI of each subject was estimated with classical PSG analysis, as a gold standard. The system was able to correctly classify 77% of subjects in 4 severity levels, based on snoring analysis and sound-based apnea detection. The sensitivity and specificity of the system, to identify healthy subjects from pathologic patients (mild to severe SAHS), were 83% and 100%, respectively. Besides, the Apnea Index (AI) obtained with the system correlated with the obtained by PSG or Respiratory Polygraphy (RP) (r=0.87, p<0.05). |
dc.format.extent | 3 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica |
dc.subject.lcsh | Sleep apnea-hypopnea syndrome |
dc.subject.lcsh | SAHS |
dc.title | Snoring analysis for the screening of sleep apnea hypopnea syndrome with a single-channel device developed using polysomnographic and snoring databases |
dc.type | Conference report |
dc.subject.lemac | Síndromes d'apnea del son |
dc.subject.lemac | SAOS |
dc.contributor.group | Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics |
dc.identifier.doi | 10.1109/IEMBS.2011.6092054 |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 8952163 |
dc.description.version | Postprint (published version) |
local.citation.author | Jané, R.; Fiz, J.; Sola, J.; Mesquita, J.; Morera, J. |
local.citation.contributor | IEEE Engineering in Medicine and Biology Society |
local.citation.pubplace | Boston |
local.citation.publicationName | Proceedings of the 33rd Annual International Conference of the IEEE EMBS |
local.citation.startingPage | 8331 |
local.citation.endingPage | 8333 |