Version 1
: Received: 6 November 2024 / Approved: 7 November 2024 / Online: 7 November 2024 (07:06:24 CET)
How to cite:
Santos, D. A Robust System for EMC to ECG Signal Conversion and Analysis Using Advanced Digital Signal Processing Techniques. Preprints2024, 2024110484. https://doi.org/10.20944/preprints202411.0484.v1
Santos, D. A Robust System for EMC to ECG Signal Conversion and Analysis Using Advanced Digital Signal Processing Techniques. Preprints 2024, 2024110484. https://doi.org/10.20944/preprints202411.0484.v1
Santos, D. A Robust System for EMC to ECG Signal Conversion and Analysis Using Advanced Digital Signal Processing Techniques. Preprints2024, 2024110484. https://doi.org/10.20944/preprints202411.0484.v1
APA Style
Santos, D. (2024). A Robust System for EMC to ECG Signal Conversion and Analysis Using Advanced Digital Signal Processing Techniques. Preprints. https://doi.org/10.20944/preprints202411.0484.v1
Chicago/Turabian Style
Santos, D. 2024 "A Robust System for EMC to ECG Signal Conversion and Analysis Using Advanced Digital Signal Processing Techniques" Preprints. https://doi.org/10.20944/preprints202411.0484.v1
Abstract
This paper presents a comprehensive system for converting and analyzing Electromagnetic Cardiac Interference (EMC) signals into high-quality Electrocardiogram (ECG) sig- nals. We introduce a multi-stage approach incorporating advanced preprocessing, adaptive filtering, robust QRS complex detection, and signal quality analysis. The proposed methodol- ogy demonstrates high efficiency in noise and artifact removal while preserving essential cardiac morphological features. Our system achieves a signal-to-noise ratio improvement of up to 20 dB and maintains QRS detection accuracy above 99% in normal conditions. The implemented solution provides automated documentation and quality metrics, making it suitable for both clinical and research applications.
Keywords
ECG signal processing; EMC conversion; QRS detection; digital filtering; signal quality assessment
Subject
Computer Science and Mathematics, Signal Processing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
