Normal and Abnormal ECG Signal Classification using Deep Learning

Author:

Bahuguna Renu1,Upadhyay Soumya1,Aditi 1,Kumar Vipin2,Saini Amit3,Jain Abhishek4

Affiliation:

1. Information Technology, COER Uiversity,Roorkee,Uttarakhand,India

2. Medi-Cap University,Department of CSE,Indore,India

3. Dev Bhoomi Uttarakhand University,Department of E.C.E.E.C.E.,Dehradun,U.K.,India

4. Phonics Group of Institutions,Department of Computer Science and Engineering

Publisher

IEEE

Reference14 articles.

1. Cardiac Pathologies Detection and Classification in12-lead ECG;smisek;Proceedings Computers in Cardiology,2020

2. A comparative study on facial expression recognition using local binary patterns, convolutional neural network and frequency neural network

3. Automated characterization of arrhythmias using nonlinear features from tachycardia ECG beats

4. PTB-XL, a large publicly available electrocardiography dataset (version 1.0.1);wagner;Data Science Journal,2020

5. PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals;goldberger;Circulation,2000

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1. Low-Cost Wearable Hand Glove For Physiological Signal Monitoring;2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE);2024-04-25

2. Prediction of ECG Cardiac Abnormality Signal using Supervised Prediction Model;2023 IEEE 11th Conference on Systems, Process & Control (ICSPC);2023-12-16

3. Certain Examination on ECG Classification using Hybrid Machine Learning Models;2023 Third International Conference on Smart Technologies, Communication and Robotics (STCR);2023-12-09

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