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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
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)
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 22160
Article Published : 8692
Total Authors : 22874
Total Reviewer : 819
Total Countries : 160
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| Paper Title: | A Comprehensive Literature Survey on Arrhythmia Detection Techniques: VLSI, Machine Learning, and Signal Processing Approaches |
| Authors Name: | Navyashree Ganpisetty , Dr. Shalini Shravan |
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IJRTI_202195
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| Published Paper Id: | IJRTI2504075 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | This literature survey provides a comprehensive analysis of various techniques employed for arrhythmia detection, categorized by their underlying methodologies including VLSI design, machine learning, signal processing, heart rate variability (HRV) analysis, and clinical applications. The study spans over two decades of research, highlighting the evolution of detection methods from traditional signal processing techniques to modern deep learning and hardware-accelerated solutions. Emphasis is placed on the accuracy, efficiency, and practicality of each approach, outlining their key contributions, benefits, and limitations. By comparing recent advancements with earlier frameworks, this survey aims to identify promising directions for future research in real-time and reliable arrhythmia detection systems. |
| Keywords: | Arrhythmia Detection, Electrocardiogram (ECG), VLSI Design, Machine Learning, Deep Learning, Heart Rate Variability (HRV), Signal Processing, Convolutional Neural Networks (CNN), Abnormal Heartbeat, Biomedical Engineering. |
| Cite Article: | "A Comprehensive Literature Survey on Arrhythmia Detection Techniques: VLSI, Machine Learning, and Signal Processing Approaches", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 4, page no.a554-a560, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504075.pdf |
| Downloads: | 000639 |
| 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: IJRTI2504075
Registration ID:202195
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: a554-a560 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504075 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504075 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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