Performance analysis of Machine Learning techniques for classification of stress levels using PPG signals-Reference-Cited by-同舟云学术

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Performance analysis of Machine Learning techniques for classification of stress levels using PPG signals

Published:2020-07 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)
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Author:

Awasthi Kushagra,Nanda Pranav,Suma K V

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9194990/9198311/09198481.pdf?arnumber=9198481

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Real-Time Stress Detection from Raw Noisy PPG Signals Using LSTM Model Leveraging TinyML;Arabian Journal for Science and Engineering;2024-05-07

2. Classification of Physiological States Through Machine Learning Algorithms Applied to Ultra-Short-Term Heart Rate and Pulse Rate Variability Indices on a Single-Feature Basis;IFMBE Proceedings;2024

3. PRV-based Stress Analysis on Display Color Temperatur in VR Environments;2023 International Conference on Fuzzy Theory and Its Applications (iFUZZY);2023-10-26

4. Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review (Preprint);JMIR Mental Health;2023-10-16

5. Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review (Preprint);2023-10-16

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