Exploring the Feasibilities of Applying Min-Max Threshold Analysis with Machine Learning Techniques for Categorization of X-Wave in ECG Signal-Reference-Cited by-同舟云学术

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Exploring the Feasibilities of Applying Min-Max Threshold Analysis with Machine Learning Techniques for Categorization of X-Wave in ECG Signal

Published:2023-07-19 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Edge Computing and Applications (ICECAA)
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Author:

Velusamy Saravanan¹,Murugan Pallikonda Rajasekaran²,Ramaraj Kottaimalai²,Thiyagarajan Arunprasath³,Govindaraj Vishnuvarthanan³,Kamalakkannan Vidyavathi⁴

Affiliation:

1. Kalasalingam Academy of Research and Education,Department of ECE,Krishnankoil,Tamilnadu,India

2. Kalasalingam Academy of Research and Education,Department of Electronics and Communication Engineering,Krishnankoil,Tamilnadu,India

3. Kalasalingam Academy of Research and Education,Department of Biomedical Engineering,Krishnankoil,Tamilnadu,India

4. Selvam College of Technology,Department of Electronics and Communication Engineering,Namakkal,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10211064/10212098/10212176.pdf?arnumber=10212176

Reference38 articles.

1. Automatic QRS complex detection using two-level convolutional neural network

2. Noisy ECG Signal Analysis for Automatic Peak Detection

3. ECG Signal Classification Using Deep Learning Techniques Based on the PTB-XL Dataset

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