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Stress Net: Multimodal Stress Detection using ECG and EEG Signals

This research work introduces Integrity of Time Domain Features & Machine Learning for Stress Classification using ECG & EEG Signals. Stress is a prevalent mental health issue in our daily lives, affecting many individuals. The impact of stress can lead to various problems, including hear...

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Main Authors: Lakshmi, K., Chitra, K.
Format: Article
Language:English
English
Published: INTI International University 2024
Subjects:
QA Mathematics
QA75 Electronic computers. Computer science
QA76 Computer software
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Online Access:http://eprints.intimal.edu.my/2066/1/jods2024_59.pdf
http://eprints.intimal.edu.my/2066/2/607
http://eprints.intimal.edu.my/2066/
http://ipublishing.intimal.edu.my/jods.html
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id my-inti-eprints.2066
record_format eprints
spelling my-inti-eprints.20662024-11-28T04:34:35Z http://eprints.intimal.edu.my/2066/ Stress Net: Multimodal Stress Detection using ECG and EEG Signals Lakshmi, K. Chitra, K. QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software RC0254 Neoplasms. Tumors. Oncology (including Cancer) This research work introduces Integrity of Time Domain Features & Machine Learning for Stress Classification using ECG & EEG Signals. Stress is a prevalent mental health issue in our daily lives, affecting many individuals. The impact of stress can lead to various problems, including heart attacks and depression. This research work aims to identify anxiety through a physical examination using both EEG and ECG signals. By analyzing and monitoring these signals, we can improve stress detection exactness, ultimately identifying and addressing mental health problems. This research work is used to prevent early detection of diseases such as depression and suicidal attempts. This task can benefit society as a whole. Moreover, using ECG signals to assess cardiovascular and related risk factors in the early stages has been explored through machine learning techniques. INTI International University 2024-11 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2066/1/jods2024_59.pdf text en cc_by_4 http://eprints.intimal.edu.my/2066/2/607 Lakshmi, K. and Chitra, K. (2024) Stress Net: Multimodal Stress Detection using ECG and EEG Signals. Journal of Data Science, 2024 (59). pp. 1-8. ISSN 2805-5160 http://ipublishing.intimal.edu.my/jods.html
institution INTI International University
building INTI Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider INTI International University
content_source INTI Institutional Repository
url_provider http://eprints.intimal.edu.my
language English
English
topic QA Mathematics
QA75 Electronic computers. Computer science
QA76 Computer software
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
spellingShingle QA Mathematics
QA75 Electronic computers. Computer science
QA76 Computer software
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Lakshmi, K.
Chitra, K.
Stress Net: Multimodal Stress Detection using ECG and EEG Signals
description This research work introduces Integrity of Time Domain Features & Machine Learning for Stress Classification using ECG & EEG Signals. Stress is a prevalent mental health issue in our daily lives, affecting many individuals. The impact of stress can lead to various problems, including heart attacks and depression. This research work aims to identify anxiety through a physical examination using both EEG and ECG signals. By analyzing and monitoring these signals, we can improve stress detection exactness, ultimately identifying and addressing mental health problems. This research work is used to prevent early detection of diseases such as depression and suicidal attempts. This task can benefit society as a whole. Moreover, using ECG signals to assess cardiovascular and related risk factors in the early stages has been explored through machine learning techniques.
format Article
author Lakshmi, K.
Chitra, K.
author_facet Lakshmi, K.
Chitra, K.
author_sort Lakshmi, K.
title Stress Net: Multimodal Stress Detection using ECG and EEG Signals
title_short Stress Net: Multimodal Stress Detection using ECG and EEG Signals
title_full Stress Net: Multimodal Stress Detection using ECG and EEG Signals
title_fullStr Stress Net: Multimodal Stress Detection using ECG and EEG Signals
title_full_unstemmed Stress Net: Multimodal Stress Detection using ECG and EEG Signals
title_sort stress net: multimodal stress detection using ecg and eeg signals
publisher INTI International University
publishDate 2024
url http://eprints.intimal.edu.my/2066/1/jods2024_59.pdf
http://eprints.intimal.edu.my/2066/2/607
http://eprints.intimal.edu.my/2066/
http://ipublishing.intimal.edu.my/jods.html
_version_ 1817849528835899392
score 13.223943

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