Stress Assessment with Convolutional Neural Network Using PPG Signals-Reference-Cited by-同舟云学术

Stress Assessment with Convolutional Neural Network Using PPG Signals

Published:2022-11-15 Issue: Volume: Page:
ISSN:
Container-title:2022 10th RSI International Conference on Robotics and Mechatronics (ICRoM)
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Author:

Hasanpoor Yasin¹,Tarvirdizadeh Bahram¹,Alipour Khalil¹,Ghamari Mohammad²

Affiliation:

1. University of Tehran, Tehran,Advanced Service Robots (ASR) Lab.,Department of Mechatronics Engineering, Faculty of New Sciences and Technologies,Tehran,Iran

2. Kettering University,Department of Electrical and Computer Engineering,Flint,Michigan,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10025024/10025031/10025071.pdf?arnumber=10025071

Reference27 articles.

1. Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection

2. Automatic Stress Detection Using Wearable Sensors and Machine Learning: A Review

3. Mental Stress Assessment Using PPG Signal a Deep Neural Network Approach

4. Psychological Stress Detection Using Photoplethysmography;sevil;IEEE Int Conf Biomedical and Health Informatics,2019

5. A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques

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1. Personalized Stress Detection Using Biosignals from Wearables: A Scoping Review;Sensors;2024-05-18

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

3. Wavelet-Based Analysis of Photoplethysmogram for Stress Detection Using Convolutional Neural Networks;2023 11th RSI International Conference on Robotics and Mechatronics (ICRoM);2023-12-19