Proceedings ArticleDOI
ECG signal feature extraction and classification using Harr Wavelet Transform and Neural Network
K. Muthuvel,S. H. Krishna Veni,L. Padma Suresh,K. Bharathi Kannan +3 more
- pp 1396-1399
TLDR
In this work an algorithm has been develop to detect the five abnormal beat signals includes Left bundle branch block beat (LBBB), Right bundle branch blocks beat (RBBB, Premature Ventricular Contraction (PVC), Atrial Premature Beat (APB) and Nodal (junction) Prematures Beat (NPB) along with the normal beat.Abstract:
The heart is one of the crucial parts of a human being. The heart produces electrical signals and these cycles of electrical signals are called as cardiac cycles. The graphical recording of the cardiac cycle produced by an Electrocardiograph is called as Electro cardio gram (ECG) signal. The Electrocardiogram signal is used to diagnose the irregularity in heart beat. Automatic classification of ECG signals has applications in human-computer interaction, as well as in clinical application such as detection of key indicators of the onset of the certain illness. In this work an algorithm has been develop to detect the five abnormal beat signals includes Left bundle branch block beat (LBBB), Right bundle branch block beat (RBBB), Premature Ventricular Contraction (PVC), Atrial Premature Beat (APB) and Nodal (junction) Premature Beat (NPB) along with the normal beat. In order to prepare an appropriate input vector for the neural classifier several pre processing stages have been applied. Harr Wavelet Transform (HWT) is used in order to extract features from the ECG signal. Preprocessing and the classification of ECG signals is done using Forward Feed Neural Network Finally, the MIT-BIH [10] database is used to evaluate the proposed algorithm.read more
Citations
More filters
Journal ArticleDOI
An Improved AlexNet for Power Edge Transmission Line Anomaly Detection
TL;DR: The results show that the proposed methods can be effectively applied to the image recognition of various types of power equipment, and they greatly improve the recognition rate of power Equipment images, which has great potential for future real-time transmission line monitoring platform design.
Journal ArticleDOI
Set-Based Discriminative Measure for Electrocardiogram Beat Classification.
Wei Li,Jianqing Li,Qin Qin +2 more
TL;DR: A novel approach is proposed, named “Set-Based Discriminative Measure”, which first learns a discriminative metric space to ensure that intra- class distances are smaller than inter-class distances for ECG features in a global way, and then measures a new set-based dissimilarity in such learned space to cope with the local variation of samples.
Proceedings ArticleDOI
FPGA Implementation of Artificial Neural Network (ANN) for ECG Signal Classification
TL;DR: The hardware implementation of a classifier using an Artificial Neural Network (ANN) to classify four abnormalities of heartbeat with high accuracy with 86% testing accuracy in simulation and 85.6% in hardware is presented.
Journal ArticleDOI
Cardiac Severity Classification Using Pre Trained Neural Networks.
TL;DR: In this paper, the authors proposed a hybrid approach to classify different cardiac conditions using the feed forward back propagation neural network (FFBPNN) by providing a pre-processed ECG signal as an excitation.
Proceedings ArticleDOI
Similar Image Retrieval Based on Wavelet Transformation.
TL;DR: In this article, a block-based image retrieval scheme based on wavelet transformation is presented, which employs the wavelet transform technique to transform each block in the spatial domain to wavelet domain, and the mean value and the edge types are extracted from each transformed block.
References
More filters
Book
An introduction to wavelets
TL;DR: An Overview: From Fourier Analysis to Wavelet Analysis, Multiresolution Analysis, Splines, and Wavelets.
Journal ArticleDOI
An introduction to wavelets
TL;DR: The mathematics have been worked out in excruciating detail, and wavelet theory is now in the refinement stage, which involves generalizing and extending wavelets, such as in extending wavelet packet techniques.
Journal ArticleDOI
Texture classification and segmentation using wavelet frames
TL;DR: In this paper, a new approach to the characterization of texture properties at multiple scales using the wavelet transform is described, which uses an overcomplete wavelet decomposition, which yields a description that is translation invariant.
Journal ArticleDOI
Symbolic representation of neural networks
Rudy Setiono,Huan Liu +1 more
TL;DR: This algorithm uses symbolic rules to represent the network decision process and extracts rules from a neural network with discretized hidden unit activation values to preserve network accuracy and explain the prediction process.