Title
Automated Prediction Of Sudden Cardiac Death Risk Using Kolmogorov Complexity And Recurrence Quantification Analysis Features Extracted From Hrv Signals
Abstract
Sudden Cardiac Death (SCD) is an unexpected sudden death of a person followed by Ventricular Fibrillation (VF) or Ventricular Tachycardia (VT) which is usually diagnosed using Electrocardiogram (ECG). Prediction of developing SCD is important for expeditious treatment and thus reducing the mortality rate. In our previous paper, we have developed the Sudden Cardiac Death Index (SCDI) to predict the SCD four minutes prior to its onset using nonlinear features extracted from Discrete Wavelet Transform (DWT) coefficients using ECG signals. In this present paper, we are proposing an automated prediction of SCD using Recurrence Quantification Analysis (RQA) and Kolmogorov complexity parameters extracted from Heart Rate Variability (HRV) signals. The extracted features ranked using t-test are subjected to k-Nearest Neighbor (k-NN), Decision Tree (DT), Support Vector Machine (SVM) and Probabilistic Neural Network (PNN) classifiers for automated classification of normal and SCD classes for of 1min, 2min, 3min and 4 min before SCD durations. Our results show that, we are able to predict the SCD four minutes before its onset with an average accuracy of 86.8%, sensitivity of 80%, and specificity of 94.4% using k-NN classifier and average accuracy of 86.8%, sensitivity of 85%, specificity of 88.8% using PNN classifier. The performance of the proposed system can be improved further by adding more features and more robust classifiers.
Year
DOI
Venue
2015
10.1109/SMC.2015.199
2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS
Keywords
Field
DocType
Heart Rate, Sudden Cardiac Death, RQA
Pattern recognition,Ventricular fibrillation,Heart rate variability,Computer science,Support vector machine,Probabilistic neural network,Sudden cardiac death,Ventricular tachycardia,Artificial intelligence,Electrocardiography,Recurrence quantification analysis,Machine learning
Conference
ISSN
Citations 
PageRank 
1062-922X
6
0.50
References 
Authors
3
6
Name
Order
Citations
PageRank
Rajendra Acharya U14666296.34
Hamido Fujita22644185.03
Vidya Sudarshan320814.19
Dhanjoo N Ghista410211.91
Wei Jie Eugene Lim51015.06
Joel E. W. Koh626619.06