UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 10 | October 2025

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Published in:

Volume 7 Issue 6
June-2020
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2006618


Registration ID:
567520

Page Number

90-98

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Title

AI-based Stress Monitoring Using Heart Rate Variability: A Survey

Authors

Abstract

Stress is both a physiological and psychological response to external or internal stimuli that disrupt homeostasis. Prolonged exposure to stress can result in negative health consequences, including cardiovascular disease, anxiety, depression, and a weakened immune system. Heart Rate Variability (HRV)—the variation in the time intervals between heartbeats—is a well-recognized biomarker for autonomic nervous system (ANS) activity, particularly in reflecting the balance between sympathetic and parasympathetic responses. Recent advancements in Artificial Intelligence (AI) have enabled the development of robust, non-invasive stress monitoring systems based on HRV data. AI models can identify complex patterns within HRV signals to accurately classify and predict stress levels in real time. This manuscript discusses various AI techniques, including machine learning, deep learning, and the integration of wearable technology, and their roles in stress detection and management. Additionally, ethical considerations—such as data privacy, informed consent, and inclusivity—are highlighted to ensure the responsible implementation of these technologies.

Key Words

AI, HRV, Linear Features, Non-linear Features, Stress.

Cite This Article

"AI-based Stress Monitoring Using Heart Rate Variability: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.90-98, June 2020, Available :http://www.jetir.org/papers/JETIR2006618.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"AI-based Stress Monitoring Using Heart Rate Variability: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp90-98, June 2020, Available at : http://www.jetir.org/papers/JETIR2006618.pdf

Publication Details

Published Paper ID: JETIR2006618
Registration ID: 567520
Published In: Volume 7 | Issue 6 | Year June-2020
DOI (Digital Object Identifier):
Page No: 90-98
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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