Integration of independent component analysis and neural networks for ECG beat classification

Authors:
Sung-Nien Yu;Kuan-To Chou
Affiliations:
Department of Electrical Engineering, National Chung Cheng University, 168 University Road, Ming Hsiung, Chia-Yi 621, Taiwan;Department of Electrical Engineering, National Chung Cheng University, 168 University Road, Ming Hsiung, Chia-Yi 621, Taiwan and Department of Electronic Engineering, Wu Feng Institute of Technolo ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

Citing 6
Cited 26

Independent component analysis, a new concept?

Signal Processing - Special issue on higher order statistics
An information-maximization approach to blind separation and blind deconvolution

Neural Computation
Advanced Methods in Neural Computing

Advanced Methods in Neural Computing
ECG beat classification using neuro-fuzzy network

Pattern Recognition Letters
Equivariant adaptive source separation

IEEE Transactions on Signal Processing
Fast and robust fixed-point algorithms for independent component analysis

IEEE Transactions on Neural Networks

A novel approach for classification of ECG arrhythmias: Type-2 fuzzy clustering neural network

Expert Systems with Applications: An International Journal
A sequential feature extraction approach for naïve bayes classification of microarray data

Expert Systems with Applications: An International Journal
Cardiac arrhythmias classification method based on MUSIC, morphological descriptors, and neural network

EURASIP Journal on Advances in Signal Processing
A two-stage mechanism for registration and classification of ECG using Gaussian mixture model

Pattern Recognition
A source adaptive independent component analysis algorithm through solving the estimating equation

Expert Systems with Applications: An International Journal
Development of ECG beat segmentation method by combining lowpass filter and irregular R-R interval checkup strategy

Expert Systems with Applications: An International Journal
A new method for classification of ECG arrhythmias using neural network with adaptive activation function

Digital Signal Processing
Clustering MIT--BIH arrhythmias with Ant Colony Optimization using time domain and PCA compressed wavelet coefficients

Digital Signal Processing
Partition-conditional ICA for Bayesian classification of microarray data

Expert Systems with Applications: An International Journal
Integration of type-2 fuzzy clustering and wavelet transform in a neural network based ECG classifier

Expert Systems with Applications: An International Journal
Fuzzy Clustered Probabilistic and Multi Layered Feed Forward Neural Networks for Electrocardiogram Arrhythmia Classification

Journal of Medical Systems
Using phase space reconstruction for patient independent heartbeat classification in comparison with some benchmark methods

Computers in Biology and Medicine
Superiority real-time cardiac arrhythmias detection using trigger learning method

ITBAM'11 Proceedings of the Second international conference on Information technology in bio- and medical informatics
ECG arrhythmia recognition via a neuro-SVM-KNN hybrid classifier with virtual QRS image-based geometrical features

Expert Systems with Applications: An International Journal
Classification of Arrhythmia Using Hybrid Networks

Journal of Medical Systems
An automatic method for holter ECG denoising using ICA

Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Detection of cardiac arrhythmia in electrocardiograms using adaptive feature extraction and modified support vector machines

Expert Systems with Applications: An International Journal
An effective ECG arrhythmia classification algorithm

ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
A Neuro-Fuzzy Identification of ECG Beats

Journal of Medical Systems
Automated Screening of Arrhythmia Using Wavelet Based Machine Learning Techniques

Journal of Medical Systems
Sparse Representation-Based Heartbeat Classification Using Independent Component Analysis

Journal of Medical Systems
An R-peak detection method that uses an SVD filter and a search back system

Computer Methods and Programs in Biomedicine
ECG arrhythmia classification based on optimum-path forest

Expert Systems with Applications: An International Journal
A methodology for embedded classification of heartbeats using random projections

Proceedings of the Conference on Design, Automation and Test in Europe
Early prediction of the highest workload in incremental cardiopulmonary tests

ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Evaluating the use of ECG signal in low frequencies as a biometry

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.07

Visualization

Abstract

In this paper, we propose a scheme to integrate independent component analysis (ICA) and neural networks for electrocardiogram (ECG) beat classification. The ICA is used to decompose ECG signals into weighted sum of basic components that are statistically mutual independent. The projections on these components, together with the RR interval, then constitute a feature vector for the following classifier. Two neural networks, including a probabilistic neural network (PNN) and a back-propagation neural network (BPNN), are employed as classifiers. ECG samples attributing to eight different beat types were sampled from the MIT-BIH arrhythmia database for experiments. The results show high classification accuracy of over 98% with either of the two classifiers. Between them, the PNN shows a slightly better performance than BPNN in terms of accuracy and robustness to the number of ICA-bases. The impressive results prove that the integration of independent component analysis and neural networks, especially PNN, is a promising scheme for the computer-aided diagnosis of heart diseases based on ECG.