ISSN2320-2882
Impact Factor9.17
UGC ParametersAligned
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CrossRefDOI
ESTD2013
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis
Authors
Labeeba N , Adithya P , Ashna K , Shilpa V , Krishnaja P
Keywords
Stress detection, multimodal analysis, electro- cardiogram (ECG), affective computing, deep learning, sentiment analysis.
Abstract
The rising problem of stress now affects mental health, work efficiency, and total human health. The process of detecting stress at an early stage works to establish both prompt treatment and the avoidance of extended health issues. The research presents a dual system which detects stress in real time through two different approaches that track body functions and assess emotional states to achieve better stress measurement outcomes. The system uses multiple methods to assess how body functions and human emotional signals interact which helps to measure a person's stress level more accurately. The research team applied machine learning and deep learning methods for their study of stress pattern detection using data that they collected. The system uses multiple models that work together to evaluate incoming data and determine whether a person experiences stress through a final stress assessment. The proposed framework uses information from multiple sources to solve the problems that single-modality systems face when detecting stress. The created method offers an effective method which can monitor people continuously while it supports mental health monitoring and workplace wellness programs and human- computer interaction needs.
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How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJCRT — journal style
"A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 3, page no.i181-i187, March 2026, Available :https://ijcrt.org/papers/IJCRT2603986.pdf
APA — 7th edition
N, L., P, A., K, A., V, S., & P, K. (2026). A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis. International Journal of Creative Research Thoughts, 14(3), i181-i187. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986
MLA — 9th edition
N, Labeeba, et al. "A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis." International Journal of Creative Research Thoughts, vol. 14, no. 3, 2026, pp. i181-i187, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986.
Chicago — 17th, bibliography
N, Labeeba, et al. "A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis." International Journal of Creative Research Thoughts 14, no. 3 (2026): i181-i187. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986.
Harvard — author–date
N, L. et al. (2026) 'A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis', International Journal of Creative Research Thoughts, 14(3), pp. i181-i187. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986
IEEE — numbered reference
L. N, A. P, A. K, S. V and K. P, "A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis," IJCRT, vol. 14, no. 3, pp. i181-i187, Mar. 2026.
Vancouver — biomedical
N L, P A, K A, V S, P K. A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis. IJCRT. 2026 Mar;14(3):i181-i187.
AMA — 11th edition
N L, P A, K A, V S, P K. A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis. IJCRT. 2026;14(3):i181-i187. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2603986,
author = {Labeeba N and Adithya P and Ashna K and Shilpa V and Krishnaja P},
title = {A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {3},
pages = {i181-i187},
year = {2026},
month = {March},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - N, Labeeba
AU - P, Adithya
AU - K, Ashna
AU - V, Shilpa
AU - P, Krishnaja
TI - A Hybrid Framework For Real-Time Stress Detection Via Bio-Signal And Affective Analysis
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 3
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986
SP - i181-i187
ER -
Issue
Volume 14 Issue 3,
March-2026
Pages : i181-i187
Article Information
- Pages
- i181-i187
- Published
- March 2026
- Registration ID
- IJCRT_304115
- Published Paper ID
- IJCRT2603986
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Kozhikode, Kerala, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 142
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2603986
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2603986.pdf
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International Journal of Creative Research Thoughts
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2320-2882
ISSN
9.17
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2013
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Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal of Creative Research Thoughts for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
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