ECG signals are corrupted by several kinds of noise and artifacts, which negatively affect any subsequent analysis. In the literature, the only approach that can handle any noise and artifacts corrupting the ECG is linear time-invariant filtering. However, it suffers from some important limitations regarding effectiveness and computational complexity. In this paper we propose a novel frame- work for ECG signal preprocessing based on the notion of quadratic variation reduction. The framework is very general, since it can cope with all the different kinds of noise and artifacts that corrupt ECG records. It relies on a single algorithmic structure, thus enjoying an easy and robust implementation. Results show that the framework is effective in improving the quality of ECG, while preserving signal morphology. Moreover, it is very fast, even on long recordings, thus being perfectly suited for real-time applications and implementation on devices with reduced computational power, such as handheld devices.

A Framework for ECG Signal Preprocessing based on Quadratic Variation Reduction / Villani, Valeria. - 41:(2014), pp. 41-44. (Intervento presentato al convegno Computing in Cardiology tenutosi a Cambridge, USA nel Sep. 7-10, 2014).

A Framework for ECG Signal Preprocessing based on Quadratic Variation Reduction

VILLANI, VALERIA
2014

Abstract

ECG signals are corrupted by several kinds of noise and artifacts, which negatively affect any subsequent analysis. In the literature, the only approach that can handle any noise and artifacts corrupting the ECG is linear time-invariant filtering. However, it suffers from some important limitations regarding effectiveness and computational complexity. In this paper we propose a novel frame- work for ECG signal preprocessing based on the notion of quadratic variation reduction. The framework is very general, since it can cope with all the different kinds of noise and artifacts that corrupt ECG records. It relies on a single algorithmic structure, thus enjoying an easy and robust implementation. Results show that the framework is effective in improving the quality of ECG, while preserving signal morphology. Moreover, it is very fast, even on long recordings, thus being perfectly suited for real-time applications and implementation on devices with reduced computational power, such as handheld devices.
2014
Computing in Cardiology
Cambridge, USA
Sep. 7-10, 2014
41
41
44
Villani, Valeria
A Framework for ECG Signal Preprocessing based on Quadratic Variation Reduction / Villani, Valeria. - 41:(2014), pp. 41-44. (Intervento presentato al convegno Computing in Cardiology tenutosi a Cambridge, USA nel Sep. 7-10, 2014).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1141724
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