International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation ECG Feature Extraction and Classifications using Deep Learning techniques , Authors : Vijendra V, Meghana Kulkarni , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 11, Issue 4, July - August 2022

Title:
ECG Feature Extraction and Classifications using Deep Learning techniques
Author Name:
Vijendra V, Meghana Kulkarni
Abstract:
Abstract: ECG Pattern recognition for features is most crucial factor in diagnostic systems. Identifying the diseases based on morphological features: Widely used techniques include ECG beats annotation and classification, Spatial domain Classification, time-frequency intra-domain Classification. The Optimized Computational deep learning Algorithms based on the parameters of Sensitivity, Specificity, Positive Predictivity Accuracy, True positive detection, True negative detection and false positive detection, false negative detection of ECG beats. The detection and Classification of beats based on Machine learning algorithms and comparison on convolutional neural networks (CNNs) by using Tensor Flow Platform. The implemented of ECG feature extraction and classification using Binary neural networks on Jupyter Notebook. The Classification of Artificial Neural Networks as 98.39% Accuracy with Adaptive thresholding on fiducial mean square algorithm. Different techniques and their accuracy parameters are compared with Advance Neuro Fuzzy Interface System, Autoencoders, Convolution neural network and Recurrent network Layers, Long short term memory. Keywords: Supervised Learning, Unsupervised Learning, Convolutional Neural Networks (CNNs), Lifting based Discrete Wavelet Transform (DWT), Positive Prediction, Sensitivity
Cite this article:
Vijendra V, Meghana Kulkarni , " ECG Feature Extraction and Classifications using Deep Learning techniques " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 11, Issue 4, July - August 2022 , pp. 011-015 , ISSN 2278-6856.
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