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

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

doi:10.1109/ISCAS.2018.8351600

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

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

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 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 language	English
Title of host publication	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538648810
DOIs	https://doi.org/10.1109/ISCAS.2018.8351600
State	Published - 26 Apr 2018
Event	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy Duration: 27 May 2018 → 30 May 2018

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2018-May
ISSN (Print)	0271-4310

Conference

Conference	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Country/Territory	Italy
City	Florence
Period	27/05/18 → 30/05/18

Keywords

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

Access to Document

10.1109/ISCAS.2018.8351600

Cite this

Tsai, S.-H., Tsai, M. S., & Jiang, Y. C. F. (2018). A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation. In 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings Article 8351600 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2018-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2018.8351600

Tsai, Shang-Ho ; Tsai, Min Shan ; Jiang, Yu Chen Fan. / A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation. 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (Proceedings - IEEE International Symposium on Circuits and Systems).

@inproceedings{7113172d35dd4557a57b8f4a4c3b4691,

title = "A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation",

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.",

keywords = "amplitude spectrum area (AMSA), defibrillation timing, frequency variation (FV), ventricular fibrillation (VF)",

author = "Shang-Ho Tsai and Tsai, {Min Shan} and Jiang, {Yu Chen Fan}",

year = "2018",

month = apr,

day = "26",

doi = "10.1109/ISCAS.2018.8351600",

language = "English",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings",

address = "美國",

note = "2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 ; Conference date: 27-05-2018 Through 30-05-2018",

}

Tsai, S-H, Tsai, MS & Jiang, YCF 2018, A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation. in 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings., 8351600, Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2018-May, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018, Florence, Italy, 27/05/18. https://doi.org/10.1109/ISCAS.2018.8351600

A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation. / Tsai, Shang-Ho; Tsai, Min Shan; Jiang, Yu Chen Fan.
2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8351600 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2018-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation

AU - Tsai, Shang-Ho

AU - Tsai, Min Shan

AU - Jiang, Yu Chen Fan

PY - 2018/4/26

Y1 - 2018/4/26

N2 - 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.

AB - 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.

KW - amplitude spectrum area (AMSA)

KW - defibrillation timing

KW - frequency variation (FV)

KW - ventricular fibrillation (VF)

UR - http://www.scopus.com/inward/record.url?scp=85057099832&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2018.8351600

DO - 10.1109/ISCAS.2018.8351600

M3 - Conference contribution

AN - SCOPUS:85057099832

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018

Y2 - 27 May 2018 through 30 May 2018

ER -

Tsai SH, Tsai MS, Jiang YCF. A Novel System and Statistical Analysis for Predicting Defibrillation Timing during Ventricular Fibrillation. In 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8351600. (Proceedings - IEEE International Symposium on Circuits and Systems). doi: 10.1109/ISCAS.2018.8351600

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this