Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13789
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dc.contributor.authorTarım, Ergün Alperay-
dc.contributor.authorErimez, Büşra-
dc.contributor.authorDeğirmenci, Mehmet-
dc.contributor.authorTekin, H. Cumhur-
dc.date.accessioned2023-10-03T07:15:34Z-
dc.date.available2023-10-03T07:15:34Z-
dc.date.issued2023-
dc.identifier.issn2640-4567-
dc.identifier.urihttps://doi.org/10.1002/aisy.202300174-
dc.identifier.urihttps://hdl.handle.net/11147/13789-
dc.descriptionArticle; Early Accessen_US
dc.description.abstractSleep problems are serious issues that make life difficult for all people, including sleep apnea. Sleep apnea, which causes breathlessness for more than 10 s, is linked to severe health problems due to the serious damage it can induce. To mitigate the risk of these disorders, the monitoring of patients has become increasingly challenging. Wearable technologies offer an effective healthcare solution for remote patient monitoring and diagnosis. A novel wearable system based on Arduino technology is introduced, specifically designed to monitor the breath patterns of patients. The analysis of breath data from patients holds great importance for the diagnosis and continuous monitoring of sleep apnea. To address this need, an advanced image processing system based on deep learning techniques is presented. This system automatically detects respiratory patterns, including inhalation, exhalation, and breathlessness. The device has an average of 97.6% sensitivity, 79.7% specificity, and 96% accuracy in identifying breath patterns. The designed device can offer patients and healthcare institutions a simple, inexpensive, noninvasive, and ergonomic system for the analysis of breath patterns that can be further extended for sleep apnea diagnosis.en_US
dc.description.sponsorshipTurkish Academy of Science [TUBA GEBIP 2020]; Science Academy (Bilim Akademisi) [BAGEP 2022]; Izmir Institute of Technology (IZTECH) [2020IYTE0042]; Scientific and Technological Research Council of Turkey (TUBITAK); Turkish Council of Higher Education; TUBITAKen_US
dc.description.sponsorship& nbsp;H.C.T. would like to thank the Outstanding Young Scientists Award funding (TUBA GEBIP 2020) from the Turkish Academy of Science, the Young Scientist Awards (BAGEP 2022) from the Science Academy (Bilim Akademisi), and the scientific research project (2020IYTE0042) funded by Izmir Institute of Technology (IZTECH). E.A.T. acknowledges the support of The Scientific and Technological Research Council of Turkey (TUBITAK) for the 2211-A BIDEB doctoral scholarship and the support of the Turkish Council of Higher Education for the 100/2000 CoHE doctoral scholarship. B.E. acknowledges the support of TUBITAK for the 2247-C STAR intern researcher scholarship. The authors would like to dedicate this article to the loving memories of our lost ones in the 2023 Kahramanmaras Earthquake.en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofAdvanced Intelligent Systemsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectbreath analysesen_US
dc.subjectdeep learningen_US
dc.subjectobject detectionen_US
dc.subjectsleep apneaen_US
dc.subjectwearable devicesen_US
dc.subjectOBSTRUCTIVE SLEEP-APNEAen_US
dc.subjectSENSORen_US
dc.subjectPRESSUREen_US
dc.subjectSYSTEMen_US
dc.titleA Wearable Device Integrated with Deep Learning-Based Algorithms for the Analysis of Breath Patternsen_US
dc.typeArticleen_US
dc.institutionauthor-
dc.departmentİzmir Institute of Technologyen_US
dc.identifier.wosWOS:001050244200001en_US
dc.identifier.scopus2-s2.0-85168392744en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1002/aisy.202300174-
dc.authorscopusid57200283702-
dc.authorscopusid58541825500-
dc.authorscopusid58018755000-
dc.authorscopusid56781554300-
dc.identifier.wosqualityN/A-
dc.identifier.scopusqualityQ4-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.dept03.01. Department of Bioengineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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