Authors:
Antonio Fasano
1
;
Valeria Villani
2
;
Luca Vollero
1
and
Federica Censi
3
Affiliations:
1
Università Campus Bio-Medico di Roma, Italy
;
2
Università Campus Bio-Medico di Roma and Italian National Institute of Health, Italy
;
3
Italian National Institute of Health, Italy
Keyword(s):
ECG, P-wave, Atrial fibrillation, Smoothing, Denoising, Quadratic variation, Convex optimization.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Cardiovascular Signals
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Atrial fibrillation is the most common persistent cardiac arrhythmia and it is characterized by a disorganized atrial electrical activity. Its occurrence can be detected, and even predicted, through P-waves time-domain and morphological analysis in ECG tracings. Given the low signal-to-noise ratio associated to P-waves, such analysis are possible if noise and artifacts are effectively filtered out from P-waves. In this paper a novel smoothing and denoising algorithm for P-waves is proposed. The algorithm is solution to a convex optimization problem. Smoothing and denoising are achieved reducing the quadratic variation of the measured P-waves. Simulation results confirm the effectiveness of the approach and show that the proposed algorithm is remarkably good at smoothing and denoising P-waves. The achieved SNR gain exceeds 15 dB for input SNR below 6 dB. Moreover the proposed algorithm has a computational complexity that is linear in the size of the vector to be processed. This proper
ty makes it suitable also for real-time applications.
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