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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2024
|
| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2066/ http://eprints.intimal.edu.my/2066/1/jods2024_59.pdf http://eprints.intimal.edu.my/2066/2/607 |
| _version_ | 1848766910877925376 |
|---|---|
| author | Lakshmi, K. Chitra, K. |
| author_facet | Lakshmi, K. Chitra, K. |
| author_sort | Lakshmi, K. |
| building | INTI Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T11:58:39Z |
| format | Article |
| id | intimal-2066 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:39Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-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 |
| 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 |
| title | 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_short | Stress Net: Multimodal Stress Detection using ECG and EEG Signals |
| title_sort | stress net: multimodal stress detection using ecg and eeg signals |
| topic | QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software RC0254 Neoplasms. Tumors. Oncology (including Cancer) |
| url | http://eprints.intimal.edu.my/2066/ http://eprints.intimal.edu.my/2066/ http://eprints.intimal.edu.my/2066/1/jods2024_59.pdf http://eprints.intimal.edu.my/2066/2/607 |