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Identification of CVD risk parameters during sleep

dc.contributor.authorMonteiro, Clara Italiano
dc.contributor.authorHenriques, Jorge
dc.contributor.authorCarvalho, Paulo
dc.contributor.authorBorghi-Silva, Audrey
dc.contributor.authorBianchi, Anna M.
dc.contributor.authorMigliorini, Matteo
dc.contributor.authorCabiddu, Ramona
dc.contributor.authorTrimer, Vitor
dc.contributor.authorParedes, Simao
dc.contributor.authorRocha, Teresa
dc.date.accessioned2022-02-18T09:03:26Z
dc.date.available2022-02-18T09:03:26Z
dc.identifier.citationBianchi A. M. , Henriques J., Monteiro C. I. , Borghi-Silva A., Carvalho P., Migliorini M., Rocha T., Paredes S., Trimer V., Cabiddu R., "Identification of CVD risk parameters during sleep", 3rd IEEE EMBS International Conference on Biomedical and Health Informatics (IEEE BHI), Nevada, Amerika Birleşik Devletleri, 24 - 27 Şubat 2016, ss.352-355
dc.identifier.otherav_13ed19ff-cd35-4a09-9e06-bf6875279d6c
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/176406
dc.identifier.urihttps://doi.org/10.1109/bhi.2016.7455907
dc.description.abstractParameters obtained from the heart rate variability (HRV) signal have good prognostic value in the cardiovascular disease (CVD), thus can cover a relevant role in the estimation of the risk stratification, especially when they are associated to other clinical and demographic data. In the view of home monitoring of CVD patients, the possibility of using signals recorded only during night may greatly reduce the impact on the patient's daily life. In this paper, we want to discuss if the HRV parameters recorded only during the night are sufficient for estimating the CVD risk. In addition, we will discuss a possible procedure for the automatic calculation of the HRV parameters without the need of specialized personnel.
dc.language.isoeng
dc.subjectEngineering (miscellaneous)
dc.subjectBİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEM
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectMühendislik
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectBilgisayar Bilimleri
dc.subjectBilgi Güvenliği ve Güvenilirliği
dc.subjectBiyoenformatik
dc.subjectMühendislik ve Teknoloji
dc.subjectSignal Processing
dc.subjectGeneral Engineering
dc.subjectTheoretical Computer Science
dc.subjectGeneral Computer Science
dc.subjectElectrical and Electronic Engineering
dc.subjectComputer Science (miscellaneous)
dc.subjectComputer Science Applications
dc.subjectInformation Systems
dc.subjectPhysical Sciences
dc.subjectBİLGİSAYAR BİLİMİ, BİLGİ SİSTEMLERİ
dc.subjectBilgisayar Bilimi
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.titleIdentification of CVD risk parameters during sleep
dc.typeBildiri
dc.contributor.departmentPolytechnic University of Milan , ,
dc.contributor.firstauthorID3383878


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