Characterization of Heart Rate Variability Changes Following Asphyxia in Rats

L. Moraru, L. Cimponeriu, S. Tong, N. Thakor, Anastasios Bezerianos

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Objectives: A non-invasive method to monitor the functioning of the autonomous nervous system consists in heart rate variability (HRV) analysis. The aim of this study was to investigate the changes on HRV after an asphyxia experiment in rats, using several linear (time and frequency domain) and nonlinear parameters (approximate entropy, SD1 and SD2 indices derived from Poincare plots). Methods: The experiments involved the study of HRV changes after cardiac arrest (CA) resulting from 5 min of hypoxia and asphyxia, followed by manual resuscitation and return of spontaneous circulation. 5 min stationary periods of RR intervals were selected for further analysis from 5 rats in following distinct situations: 1) baseline, 2) 30 min after CA, 3) 60 min after CA, 4) 90 min after CA, 5) 120 min after CA, 6) 150 min after CA. The ANS contribution has been delineated based on time and frequency domain analysis. Results and Conclusions The results indicate that the recovery process following the asphyxia cardiac arrest reflects the impaired functioning of the autonomic nervous system. Both linear and nonlinear parameters track the different phases of the experiment, with an increased sensitivity displayed by the approximate entropy (ApEn). After 150 min the ApEn RRI parameter recovers to its baseline value. The results forward the ApEn as a more sensitive parameter of the recovery process following the asphyxia.

Original languageEnglish (US)
Pages (from-to)118-121
Number of pages4
JournalMethods of information in medicine
Volume43
Issue number1
DOIs
StatePublished - 2004

Keywords

  • Approximate entropy
  • Autonomous nervous system
  • Heart Head rate variability
  • Linear and nonlinear analysis

ASJC Scopus subject areas

  • Health Informatics
  • Advanced and Specialized Nursing
  • Health Information Management

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