Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation

JD Diaz, MA Diaz, NC Castro, B Glover, G Manoharan, OJ Escalona

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

Abstract

The objective of this study, was to build support vector machines (SVM) for predicting success of electric shocks in the internal cardioversion (IC) of patients with atrial fibrillation (AF). Some investigations have found correlations between parameters and necessary energy for defibrillating AF, but no tool exist for predicting whether an electric shock will be successful or not in low energy IC. Thirty eight patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in our study. Two catheters were positioned in the right atrial appendage (RAA) and the coronary sinus (CS), to deliver a biphasic shock waveform, synchronized with the R wave of the electrocardiogram (ECG) signal. A voltage step-up protocol (50-300 V) was used for patient cardioversion. The ECG was analyzed for an average time interval of 52,8 +/- 10.1 s (corresponding to segments before each shock). Residual atrial fibrillatory signal (RAFS) was estimated by means of bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The atria[ fibrillatory frequency (AFF) and the instantaneous frequency (IF) series were extracted from the RAFS. AFF was calculated from whole segments and from the 10 seconds of the RAFS previous shocks. The mean, standard deviation and approximate entropy of the IF time series were computed. RR intervals of the ECG segments were also analyzed. A total of 26 patients were successfully cardioverted, employing 167 shocks (141 non successful). SVMs were built for classifying success on shocks for energy up to 2, 3 and 6 Joules, employing different combinations of the computed parameters. A maximal exactitude of 93.42% (sensitivity=92.31% and specificity=93.65%) was obtained classifying shocks below 2 Joules, 95.51% (sensitivity=92.86% and specificity=96%) for shocks up to 3 Joules, and 92.91% (sensitivity=78.95% and specificity=95.37%) for shocks <= 6 Joules.
LanguageEnglish
Title of host publicationUnknown Host Publication
Place of PublicationHEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
Pages1168-1172
Number of pages5
Publication statusPublished - 2008
EventIV LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING 2007, BIOENGINEERING SOLUTIONS FOR LATIN AMERICA HEALTH, VOLS 1 AND 2 -
Duration: 1 Jan 2008 → …

Publication series

NameIFMBE Proceedings

Conference

ConferenceIV LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING 2007, BIOENGINEERING SOLUTIONS FOR LATIN AMERICA HEALTH, VOLS 1 AND 2
Period1/01/08 → …

Fingerprint

Electric Countershock
Atrial Fibrillation
Shock
Electrocardiography
Sensitivity and Specificity
Support Vector Machine
Atrial Appendage
Coronary Sinus
Victoria
Entropy
Catheters

Keywords

  • Support vector machine
  • cardioversion
  • atrial fibrillatory frequency
  • instantaneous frequency
  • QRS cancellation
  • defibrillation

Cite this

Diaz, JD., Diaz, MA., Castro, NC., Glover, B., Manoharan, G., & Escalona, OJ. (2008). Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation. In Unknown Host Publication (pp. 1168-1172). (IFMBE Proceedings). HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY.
Diaz, JD ; Diaz, MA ; Castro, NC ; Glover, B ; Manoharan, G ; Escalona, OJ. / Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation. Unknown Host Publication. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2008. pp. 1168-1172 (IFMBE Proceedings).
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abstract = "The objective of this study, was to build support vector machines (SVM) for predicting success of electric shocks in the internal cardioversion (IC) of patients with atrial fibrillation (AF). Some investigations have found correlations between parameters and necessary energy for defibrillating AF, but no tool exist for predicting whether an electric shock will be successful or not in low energy IC. Thirty eight patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in our study. Two catheters were positioned in the right atrial appendage (RAA) and the coronary sinus (CS), to deliver a biphasic shock waveform, synchronized with the R wave of the electrocardiogram (ECG) signal. A voltage step-up protocol (50-300 V) was used for patient cardioversion. The ECG was analyzed for an average time interval of 52,8 +/- 10.1 s (corresponding to segments before each shock). Residual atrial fibrillatory signal (RAFS) was estimated by means of bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The atria[ fibrillatory frequency (AFF) and the instantaneous frequency (IF) series were extracted from the RAFS. AFF was calculated from whole segments and from the 10 seconds of the RAFS previous shocks. The mean, standard deviation and approximate entropy of the IF time series were computed. RR intervals of the ECG segments were also analyzed. A total of 26 patients were successfully cardioverted, employing 167 shocks (141 non successful). SVMs were built for classifying success on shocks for energy up to 2, 3 and 6 Joules, employing different combinations of the computed parameters. A maximal exactitude of 93.42{\%} (sensitivity=92.31{\%} and specificity=93.65{\%}) was obtained classifying shocks below 2 Joules, 95.51{\%} (sensitivity=92.86{\%} and specificity=96{\%}) for shocks up to 3 Joules, and 92.91{\%} (sensitivity=78.95{\%} and specificity=95.37{\%}) for shocks <= 6 Joules.",
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author = "JD Diaz and MA Diaz and NC Castro and B Glover and G Manoharan and OJ Escalona",
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Diaz, JD, Diaz, MA, Castro, NC, Glover, B, Manoharan, G & Escalona, OJ 2008, Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation. in Unknown Host Publication. IFMBE Proceedings, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, pp. 1168-1172, IV LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING 2007, BIOENGINEERING SOLUTIONS FOR LATIN AMERICA HEALTH, VOLS 1 AND 2, 1/01/08.

Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation. / Diaz, JD; Diaz, MA; Castro, NC; Glover, B; Manoharan, G; Escalona, OJ.

Unknown Host Publication. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2008. p. 1168-1172 (IFMBE Proceedings).

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

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T1 - Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation

AU - Diaz, JD

AU - Diaz, MA

AU - Castro, NC

AU - Glover, B

AU - Manoharan, G

AU - Escalona, OJ

N1 - 4th Latin American Congress on Biomedical Engineering 2007 - Bioengineering Solutions for Latin America Health, Margarita Isl, VENEZUELA, SEP 24-28, 2007

PY - 2008

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N2 - The objective of this study, was to build support vector machines (SVM) for predicting success of electric shocks in the internal cardioversion (IC) of patients with atrial fibrillation (AF). Some investigations have found correlations between parameters and necessary energy for defibrillating AF, but no tool exist for predicting whether an electric shock will be successful or not in low energy IC. Thirty eight patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in our study. Two catheters were positioned in the right atrial appendage (RAA) and the coronary sinus (CS), to deliver a biphasic shock waveform, synchronized with the R wave of the electrocardiogram (ECG) signal. A voltage step-up protocol (50-300 V) was used for patient cardioversion. The ECG was analyzed for an average time interval of 52,8 +/- 10.1 s (corresponding to segments before each shock). Residual atrial fibrillatory signal (RAFS) was estimated by means of bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The atria[ fibrillatory frequency (AFF) and the instantaneous frequency (IF) series were extracted from the RAFS. AFF was calculated from whole segments and from the 10 seconds of the RAFS previous shocks. The mean, standard deviation and approximate entropy of the IF time series were computed. RR intervals of the ECG segments were also analyzed. A total of 26 patients were successfully cardioverted, employing 167 shocks (141 non successful). SVMs were built for classifying success on shocks for energy up to 2, 3 and 6 Joules, employing different combinations of the computed parameters. A maximal exactitude of 93.42% (sensitivity=92.31% and specificity=93.65%) was obtained classifying shocks below 2 Joules, 95.51% (sensitivity=92.86% and specificity=96%) for shocks up to 3 Joules, and 92.91% (sensitivity=78.95% and specificity=95.37%) for shocks <= 6 Joules.

AB - The objective of this study, was to build support vector machines (SVM) for predicting success of electric shocks in the internal cardioversion (IC) of patients with atrial fibrillation (AF). Some investigations have found correlations between parameters and necessary energy for defibrillating AF, but no tool exist for predicting whether an electric shock will be successful or not in low energy IC. Thirty eight patients with AF, for elective DC cardioversion at the Royal Victoria Hospital in Belfast, were included in our study. Two catheters were positioned in the right atrial appendage (RAA) and the coronary sinus (CS), to deliver a biphasic shock waveform, synchronized with the R wave of the electrocardiogram (ECG) signal. A voltage step-up protocol (50-300 V) was used for patient cardioversion. The ECG was analyzed for an average time interval of 52,8 +/- 10.1 s (corresponding to segments before each shock). Residual atrial fibrillatory signal (RAFS) was estimated by means of bandpass filtering and ventricular activity (QRST) cancellation. QRST complexes were cancelled using a recursive least squared (RLS) adaptive filter. The atria[ fibrillatory frequency (AFF) and the instantaneous frequency (IF) series were extracted from the RAFS. AFF was calculated from whole segments and from the 10 seconds of the RAFS previous shocks. The mean, standard deviation and approximate entropy of the IF time series were computed. RR intervals of the ECG segments were also analyzed. A total of 26 patients were successfully cardioverted, employing 167 shocks (141 non successful). SVMs were built for classifying success on shocks for energy up to 2, 3 and 6 Joules, employing different combinations of the computed parameters. A maximal exactitude of 93.42% (sensitivity=92.31% and specificity=93.65%) was obtained classifying shocks below 2 Joules, 95.51% (sensitivity=92.86% and specificity=96%) for shocks up to 3 Joules, and 92.91% (sensitivity=78.95% and specificity=95.37%) for shocks <= 6 Joules.

KW - Support vector machine

KW - cardioversion

KW - atrial fibrillatory frequency

KW - instantaneous frequency

KW - QRS cancellation

KW - defibrillation

M3 - Conference contribution

T3 - IFMBE Proceedings

SP - 1168

EP - 1172

BT - Unknown Host Publication

CY - HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY

ER -

Diaz JD, Diaz MA, Castro NC, Glover B, Manoharan G, Escalona OJ. Use of Support Vector Machines in Predicting Success of Intracardiac Cardioversion by Electric Shocks in Patients with Atrial Fibrillation. In Unknown Host Publication. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY. 2008. p. 1168-1172. (IFMBE Proceedings).