Quantitative analysis of heart rate baroreflex in healthy subjects using adaptive neuro fuzzy inference system approximation

Ali Jalali, Ali Ghaffari, Parham Ghorbanian, Fatemeh Jalali, C. Nataraj

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

Abstract

This paper is focused on the identification of the heart rate (HR) baroreflex mechanism using new nonlinear system identification approach. The proposed HR baroreflex model is based on inherent features of the autonomic nervous system for which we develop an adaptive neuro-fuzzy inference system (ANFIS) structure. The simulation results show significant improvements in prediction of HR as a model output by calculating the normalized root mean square error (NRMSE) in comparison with other reported methods. We have shown that for modeling of cardiovascular system regulation, our proposed nonlinear model is more accurate than other recently developed methods.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology 2010, CinC 2010
Pages951-954
Number of pages4
StatePublished - 2010
Externally publishedYes
EventComputing in Cardiology 2010, CinC 2010 - Belfast, United Kingdom
Duration: Sep 26 2010Sep 29 2010

Publication series

NameComputing in Cardiology
Volume37
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

ConferenceComputing in Cardiology 2010, CinC 2010
CountryUnited Kingdom
CityBelfast
Period9/26/109/29/10

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

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