In this paper we propose a novel approach for estimating narrowband components from ECG records. The approach is based on the notion of modulated quadratic variation, meant as a measure of variability for narrowband signals. The algorithm is the closed-form solution to a constrained convex optimization problem, where narrowband components are estimated tracking the slow variations around a central frequency in the measured signal. The proposed approach is applied to power-line interference suppression. Numerical results confirm its effectiveness. Moreover, the approach is general and can be applied to any bioelectrical signal, either for denoising or diagnostic purposes. It is also very fast, as its computational complexity is linear in the size of the vector to process.
Fast Estimation of Narrowband Components for ECG Signals / Villani, Valeria. - (2014). (Intervento presentato al convegno Quarto Congresso del Gruppo Nazionale di Bioingegneria (GNB 2014) tenutosi a Pavia (IT) nel Jun. 25-27, 2014).
Fast Estimation of Narrowband Components for ECG Signals
VILLANI, VALERIA
2014
Abstract
In this paper we propose a novel approach for estimating narrowband components from ECG records. The approach is based on the notion of modulated quadratic variation, meant as a measure of variability for narrowband signals. The algorithm is the closed-form solution to a constrained convex optimization problem, where narrowband components are estimated tracking the slow variations around a central frequency in the measured signal. The proposed approach is applied to power-line interference suppression. Numerical results confirm its effectiveness. Moreover, the approach is general and can be applied to any bioelectrical signal, either for denoising or diagnostic purposes. It is also very fast, as its computational complexity is linear in the size of the vector to process.Pubblicazioni consigliate
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