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A machine learning approach for integrating phonocardiogram and electrocardiogram data for heart sound detection
Mains, Thu
Mains, Thu
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t24059_Mains.pdf
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2024-12
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Heart sound detection (HSD) is crucial for diagnosing cardiovascular diseases and monitoring cardiac health. While the traditional diagnostic methods often rely on either phonocardiogram (PCG) or electrocardiogram (ECG) data and often cause several performance degradations. In this work, we propose to combine the augmentation methodology with ECG and PCG fusion. Experiments are conducted with physioNet dataset used in CINC2016 Challenges. Experimental results show the proposed method outperforming benchmark systems by providing complementary information, hence improving performance with modality fusion.
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Thesis (M.S.)-- Wichita State University, College of Engineering, School of Computing
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Wichita State University
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© Copyright 2024 by Thu Mains
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