Real-time ECG Analysis and Classification using Neural Networks in IoT devices-Reference-Cited by-同舟云学术

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Real-time ECG Analysis and Classification using Neural Networks in IoT devices

Published:2023-12-08 Issue: Volume:2 Page:1-5
ISSN:
Container-title:2023 Innovations in Power and Advanced Computing Technologies (i-PACT)
language:
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Author:

A Mohamed Imran¹,Ramachandran Sitharthan²,M Sunder³,R Abishek⁴,S Sai Prasath⁵,S Sabarivelan⁶

Affiliation:

1. School of Electrical Engineering, Vellore Institute of Technology,Chennai,India

2. Vellore Institute of Technology,Centre for Smart Grid Technologies,Chennai,India

3. 20BEI0031, School of Electrical Engineering, Vellore Institute of Technology,Vellore,India

4. 20BEI0053, School of Electrical Engineering, Vellore Institute of Technology,Vellore,India

5. 20BEI0002, School of Electrical Engineering, Vellore Institute of Technology,Vellore,India

6. 20BEI0059, School of Electrical Engineering, Vellore Institute of Technology,Vellore,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10433943/10433945/10434526.pdf?arnumber=10434526

Reference14 articles.

1. Intelligent Deep Models Based on Scalograms of Electrocardiogram Signals for Biometrics

2. Emotion Recognition from ECG Signals Using Wavelet Scattering and Machine Learning

3. Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection

4. Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances

5. Development of an embedded system and MATLAB-based GUI for online acquisition and analysis of ECG signal

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