Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
A fuzzy backpropagation algorithm
Fuzzy Sets and Systems
An ARMA order selection method with fuzzy reasoning
Signal Processing - Special section on information theoretic aspects of digital watermarking
Unsupervised feature extraction using neuro-fuzzy approach
Fuzzy Sets and Systems - Information processing
A fuzzy neural network for pattern classification and feature selection
Fuzzy Sets and Systems
Suppressed fuzzy c-means clustering algorithm
Pattern Recognition Letters
A fuzzy c-means variant for the generation of fuzzy term sets
Fuzzy Sets and Systems - Theme: Modeling and learning
Fuzzy least-squares algorithms for interactive fuzzy linear regression models
Fuzzy Sets and Systems - Theme: Modeling and learning
Evolutionary Training of a Neurofuzzy Network for Detection of P Wave of the ECG
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
A Self-Organizing Neural Fuzzy Inference Network
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
IEEE Transactions on Information Technology in Biomedicine
Compensatory neurofuzzy systems with fast learning algorithms
IEEE Transactions on Neural Networks
Conditional fuzzy clustering in the design of radial basis function neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Generalized clustering networks and Kohonen's self-organizing scheme
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Complex-valued wavelet artificial neural network for Doppler signals classifying
Artificial Intelligence in Medicine
Atrial fibrillation classification with artificial neural networks
Pattern Recognition
Computers in Biology and Medicine
Fuzzy neural network structure identification based on soft competitive learning
International Journal of Hybrid Intelligent Systems
Ontological fuzzy agent for electrocardiogram application
Expert Systems with Applications: An International Journal
A New Method for Diagnosis of Cirrhosis Disease: Complex-valued Artificial Neural Network
Journal of Medical Systems
Artificial Intelligence in Medicine
A new approach for epileptic seizure detection using adaptive neural network
Expert Systems with Applications: An International Journal
A new arrhythmia clustering technique based on Ant Colony Optimization
Journal of Biomedical Informatics
Expert Systems with Applications: An International Journal
A novel approach for classification of ECG arrhythmias: Type-2 fuzzy clustering neural network
Expert Systems with Applications: An International Journal
Knowledge and intelligent computing system in medicine
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
A new neural network with adaptive activation function for classification of ECG arrhythmias
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
A comparative study of DWT, CWT and DCT transformations in ECG arrhythmias classification
Expert Systems with Applications: An International Journal
On-node processing of ECG signals
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
International Journal of Knowledge Engineering and Soft Data Paradigms
Expert Systems with Applications: An International Journal
Fuzzy clustering complex-valued neural network to diagnose cirrhosis disease
Expert Systems with Applications: An International Journal
Comparison of unsupervised Arrhythmia classification techniques
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
AMI Screening Using Linguistic Fuzzy Rules
Journal of Medical Systems
A novel technique for identifying patients with ICU needs using hemodynamic features
Advances in Fuzzy Systems - Special issue on Hybrid Biomedical Intelligent Systems
The pattern classification based on fuzzy min-max neural network with new algorithm
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
An improved procedure for detection of heart arrhythmias with novel pre-processing techniques
Expert Systems: The Journal of Knowledge Engineering
Neural network and wavelet average framing percentage energy for atrial fibrillation classification
Computer Methods and Programs in Biomedicine
Hi-index | 0.02 |
Accurate and computationally efficient means of classifying electrocardiography (ECG) arrhythmias has been the subject of considerable research effort in recent years. This study presents a comparative study of the classification accuracy of ECG signals using a well-known neural network architecture named multi-layered perceptron (MLP) with backpropagation training algorithm, and a new fuzzy clustering NN architecture (FCNN) for early diagnosis. The ECG signals are taken from MIT-BIH ECG database, which are used to classify 10 different arrhythmias for training. These are normal sinus rhythm, sinus bradycardia, ventricular tachycardia, sinus arrhythmia, atrial premature contraction, paced beat, right bundle branch block, left bundle branch block, atrial fibrillation and atrial flutter. For testing, the proposed structures were trained by backpropagation algorithm. Both of them tested using experimental ECG records of 92 patients (40 male and 52 female, average age is 39.75+/-19.06). The test results suggest that a new proposed FCNN architecture can generalize better than ordinary MLP architecture and also learn better and faster. The advantage of proposed structure is a result of decreasing the number of segments by grouping similar segments in training data with fuzzy c-means clustering.