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Automatic silence events detector from smartphone audio signals: a pilot mHealth system for sleep apnea monitoring at home
dc.contributor.author | Castillo Escario, Yolanda |
dc.contributor.author | Ferrer Lluís, Ignasi |
dc.contributor.author | Montserrat, Josep Maria |
dc.contributor.author | Jané Campos, Raimon |
dc.contributor.other | Universitat Politècnica de Catalunya. Doctorat en Enginyeria Biomèdica |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2019-12-18T12:05:15Z |
dc.date.issued | 2019 |
dc.identifier.citation | Castillo-Escario, Y. [et al.]. Automatic silence events detector from smartphone audio signals: a pilot mHealth system for sleep apnea monitoring at home. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 4982-4985. |
dc.identifier.isbn | 978-1-5386-1311-5 |
dc.identifier.uri | http://hdl.handle.net/2117/174059 |
dc.description | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
dc.description.abstract | Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Recently, mHealth tools are being proposed to screen OSA patients at home. In this work, we analyzed full-night audio signals recorded with a smartphone microphone. Our objective was to develop an automatic detector to identify silence events (apneas or hypopneas) and compare its performance to a commercial portable system for OSA diagnosis (ApneaLink™, ResMed). To do that, we acquired signals from three subjects with both systems simultaneously. A sleep specialist marked the events on smartphone and ApneaLink signals. The automatic detector we developed, based on the sample entropy, identified silence events similarly than manual annotation. Compared to ApneaLink, it was very sensitive to apneas (detecting 86.2%) and presented an 83.4% positive predictive value, but it missed about half the hypopnea episodes. This suggests that during some hypopneas the flow reduction is not reflected in sound. Nevertheless, our detector accurately recognizes silence events, which can provide valuable respiratory information related to the disease. These preliminary results show that mHealth devices and simple microphones are promising non-invasive tools for personalized sleep disorders management at home |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria biomèdica |
dc.subject | Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica |
dc.subject.lcsh | Oximetry |
dc.subject.lcsh | Biomedical engineering |
dc.subject.lcsh | Smartphones |
dc.subject.other | Acoustic signals |
dc.subject.other | Biomedical signal processing |
dc.subject.other | MHealth |
dc.subject.other | Sleep apnea |
dc.subject.other | Smartphone |
dc.title | Automatic silence events detector from smartphone audio signals: a pilot mHealth system for sleep apnea monitoring at home |
dc.type | Conference lecture |
dc.subject.lemac | Oximetria |
dc.subject.lemac | Enginyeria biomèdica |
dc.subject.lemac | Telèfons intel·ligents |
dc.contributor.group | Universitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation |
dc.identifier.doi | 10.1109/EMBC.2019.8857906 |
dc.relation.publisherversion | https://ieeexplore.ieee.org/abstract/document/8857906 |
dc.rights.access | Open Access |
local.identifier.drac | 26200936 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/MICINN/2PE/DPI2015-68820 |
dc.date.lift | 10000-01-01 |
local.citation.author | Castillo-Escario, Y.; Ferrer, I.; Montserrat, J.M.; Jane, R. |
local.citation.contributor | Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
local.citation.publicationName | 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC): proceedings |
local.citation.startingPage | 4982 |
local.citation.endingPage | 4985 |