Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

Banner header
69.067 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Departaments
  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
  • Ponències/Comunicacions de congressos
  • View Item
  •   DSpace Home
  • E-prints
  • Departaments
  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
  • Ponències/Comunicacions de congressos
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis

Thumbnail
View/Open
EMBC17_0787_FI.pdf (539,4Kb)
 
10.1109/EMBC.2017.8037078
 
  View UPCommons Usage Statistics
  LA Referencia / Recolecta stats
Includes usage data since 2022
Cita com:
hdl:2117/132761

Show full item record
Rodríguez Benítez, Javier
Voss, Andreas
Caminal Magrans, PereMés informacióMés informacióMés informació
Bayés Genis, Antoni
Giraldo Giraldo, BeatrizMés informacióMés informacióMés informació
Document typeConference lecture
Defense date2017
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF = 35%, 30 patients) of heart attack. RR, SBP and T Tot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics
Description
© 2017 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
CitationRodriguez, J. [et al.]. Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "Conference of the IEEE Engineering in Medicine and Biology Society". 2017. 
URIhttp://hdl.handle.net/2117/132761
DOI10.1109/EMBC.2017.8037078
DL10.1109/EMBC.2017.8037078
ISBN978-1-5090-2809-2
Publisher versionhttps://ieeexplore.ieee.org/document/8037078
Collections
  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Ponències/Comunicacions de congressos [1.571]
  • BIOSPIN - Biomedical Signal Processing and Interpretation - Ponències/Comunicacions de congressos [70]
  View UPCommons Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
EMBC17_0787_FI.pdf539,4KbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Metadata under:Metadata under CC0
  • Contact Us
  • Send Feedback
  • Privacy Settings
  • Inici de la pàgina