A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation

Shang-Ho Tsai, Min Shan Tsai, Yu Chen Fan Jiang

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

1 Scopus citations

Abstract

This work proposes a new algorithm and analytical methods for predicting the successful rate of a defibrillation during ventricular fibrillation. Accurate predictions help in improving outcomes of cardiopulmonary resuscitation. This also helps in finding a good defibrillation timing to avoid ineffective defibrillation, which leads to myocardial damages and thus a poor prognosis after the resuscitation. Simulation results show that the proposed algorithm outperforms conventional methods in terms of several commonly used performance indices; meanwhile, the proposed analysis also well matches the practical experimental results.

Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538648810
DOIs
StatePublished - 26 Apr 2018
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: 27 May 201830 May 2018

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2018-May
ISSN (Print)0271-4310

Conference

Conference2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
CountryItaly
CityFlorence
Period27/05/1830/05/18

Keywords

  • amplitude spectrum area (AMSA)
  • defibrillation timing
  • frequency variation (FV)
  • ventricular fibrillation (VF)

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