Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
With all the advancements in artificial intelligence and healthcare technologies, the real-time health monitoring feature has now become more accessible. This paper proposes a novel approach on integrating virtual heart rate detection for personalized content recommendation. Our project model includes computer vision and signal processing techniques to detect heart rate variations from facial video streams using OpenCV. By applying filtering and the feature extraction methods, we tend to ensure accurate heart rate estimation and a seamless content suggestion. Experimental outcomes denote a significant level of increase in user engagement and mental wellbeing of the users.
Keywords:
Machine Learning, OpenCV, Signal Processing, Remote Photoplethysmography
Cite Article:
"AI Driven Content Personalization via Virtual Heart Rate Detection", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.c285-c290, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503243.pdf
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000520
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator