A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate-Reference-Cited by-同舟云学术

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A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate

Published:2023-11-06 Issue: Volume: Page:1-22
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Mukherjee Prithwijit¹,Halder Roy Anisha¹

Affiliation:

1. Institute of Radio Physics and Electronics, University of Calcutta, Kolkata, India

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2023.2275547

Reference58 articles.

1. ECG Pattern Analysis for Emotion Detection

2. Al-Shargie F Tang TB Badruddin N Kiguchi M. 2015. Simultaneous measurement of EEG-fNIRS in classifying and localizing brain activation to mental stress. Proceedings of the 2015 IEEE International Conference on Signal and Image Processing Applications; Kuala Terengganu Malaysia.

3. Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection

4. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

5. What Does Your Chair Know About Your Stress Level?

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1. EEG-Based Taste Perception Classification Using PCA Enhanced Attention-TLSTM Neural Network;2023 4th International Conference on Communication, Computing and Industry 6.0 (C216);2023-12-15

2. AromaNet: Integrating Attention Mechanism with Convolutional Neural Network for Olfactory Perception Classification Using EEG Signals;2023 4th International Conference on Communication, Computing and Industry 6.0 (C216);2023-12-15

3. A Fusion of CNN and Grey Wolf Optimization-Enhanced BiGRU for Epileptic Seizure Recognition Using EEG Signals;2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC);2023-12-04

4. EEG sensor driven assistive device for elbow and finger rehabilitation using deep learning;Expert Systems with Applications;2023-12

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