Disorder classification in the regulatory mechanism of the cardiovascular system

A. Jalali, A. Ghaffari, M. Ghasemi, H. Sadabadi, P. Ghorbanian, H. Golbayani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An approach to classify disorders in autonomic control of cardiovascular system is proposed in this paper. The target of this study is to highlight main features of malfunctions in cardiovascular system due to autonomic disorder. Collecting the data from the physionet archive, we divide patients into two groups of normal and abnormal, based on having autonomic disorder in their cardiovascular system or not. Systolic blood pressure (SBP) and heart rate (HR) time series are evaluated for each patient. We then plot the diagram of SBP against HR for all patients in a single figure. Fuzzy c-means clustering (FCM) method is also applied to cluster data into two groups. A neural network is then implemented to classify and to distinguish the two groups. The network is trained with data of a normal patient and is tested with data of other normal and abnormal patients. Result show that selected features can clearly detect disorders in autonomic system.

Original languageEnglish (US)
Title of host publicationComputers in Cardiology 2007, CAR 2007
Pages489-492
Number of pages4
DOIs
StatePublished - 2007
Externally publishedYes
EventComputers in Cardiology 2007, CAR 2007 - Durham, NC, United States
Duration: Sep 30 2007Oct 3 2007

Publication series

NameComputers in Cardiology
Volume34
ISSN (Print)0276-6574

Conference

ConferenceComputers in Cardiology 2007, CAR 2007
Country/TerritoryUnited States
CityDurham, NC
Period9/30/0710/3/07

ASJC Scopus subject areas

  • Computer Science Applications
  • Cardiology and Cardiovascular Medicine

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