Single-lead f-wave extraction using diffusion geometry
| Autor: | Hau-Tieng Wu, John Malik, Chun-Li Wang, Neil Reed |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Physiology Computer science 0206 medical engineering Biomedical Engineering Biophysics Beat (acoustics) FOS: Physical sciences 02 engineering and technology Signal-To-Noise Ratio 030204 cardiovascular system & hematology Quantitative Biology - Quantitative Methods Statistics - Applications Diffusion Electrocardiography 03 medical and health sciences 0302 clinical medicine Physiology (medical) Atrial Fibrillation Euclidean geometry Applications (stat.AP) Quantitative Methods (q-bio.QM) Signal processing Subtraction Signal Processing Computer-Assisted Probability and statistics 020601 biomedical engineering Singular value Physics - Data Analysis Statistics and Probability Diffusion geometry FOS: Biological sciences Principal component analysis Algorithm Algorithms Data Analysis Statistics and Probability (physics.data-an) |
| DOI: | 10.48550/arxiv.1702.08638 |
| Popis: | A novel single-lead f-wave extraction algorithm based on the modern diffusion geometry data analysis framework is proposed. The algorithm is essentially an averaged beat subtraction algorithm, where the ventricular activity template is estimated by combining a newly designed metric, the "diffusion distance," and the non-local Euclidean median based on the non-linear manifold setup. We coined the algorithm DD-NLEM. Two simulation schemes are considered, and the new algorithm DD-NLEM outperforms traditional algorithms, including the average beat subtraction, principal component analysis, and adaptive singular value cancellation, in different evaluation metrics with statistical significance. The clinical potential is shown in the real Holter signal, and we introduce a new score to evaluate the performance of the algorithm. Comment: 31 pages, 8 figures |
| Databáze: | OpenAIRE |
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