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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19457
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | Detecting cardiac pathologies via machine learning on heart rate variability measure between the related heart beat series |
| Authors Name: | Priyadharshini S , Jenolinrex M |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188374
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| Published Paper Id: | IJRTI2310116 |
| Published In: | Volume 8 Issue 10, October-2023 |
| DOI: | |
| Abstract: | Heart rate monitoring is an essential practice for evaluating an individual's cardiovascular health and overall well-being. It entails the measurement and tracking of the number of heart beats per minute (bpm). Various methods are utilized for heart rate monitoring, each possessing its own level of precision and purpose. These methods include manual pulse checks, wearable devices, chest strap monitors, electrocardiograms (ECGs), photo plethysmography (PPG), and mobile apps. In our study, we propose the utilization of Random Forest and Gaussian Naive Bayes algorithms to effectively analyze and predict heart rate patterns. The objective of this system is to enhance the accuracy and reliability of heart rate predictions for a wide range of healthcare applications. By combining these two techniques, our proposed system aims to improve the precision of heart rate forecasts, enabling the early detection of irregularities and facilitating proactive intervention. The effectiveness of this hybrid approach is demonstrated through extensive experimentation and evaluation using real-world heart rate data. |
| Keywords: | Remote Photo plethysmography (rPPG), Remote Heart Rate Estimation, Illumination Variation, Heart Rate Monitoring |
| Cite Article: | "Detecting cardiac pathologies via machine learning on heart rate variability measure between the related heart beat series", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 10, page no.869 - 873, October-2023, Available :http://www.ijrti.org/papers/IJRTI2310116.pdf |
| Downloads: | 000205099 |
| 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 |
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Published Paper ID: IJRTI2310116
Registration ID:188374
Published In: Volume 8 Issue 10, October-2023
DOI (Digital Object Identifier):
Page No: 869 - 873 Country: salem-636209, tamilnadu , India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2310116 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2310116 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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