The joint study of respiratory and cardiac activity suggests indirect methods to derive the respiratory signal by electrocardiogram (ECG) processing. Potential advantages of such methods are low cost, high convenience, and continuous noninvasive respiratory monitoring. Recent works show that the respiratory signal can be accurately evaluated by single-channel ECG processing. The aim of this paper is to introduce a new method based on the Empirical Mode Decomposition (EMD) for the respiratory signal evaluation. A comparison versus popular algorithms for the respiratory signal extraction is also shown. Preliminary results confirm that EMD algorithm provides better performances, with respect to others, especially in the case of respiratory waveform reconstruction.

ECG-derived respiratory signal using Empirical Mode Decomposition

LA FORESTA, Fabio;Campolo M;MORABITO, Francesco Carlo
2011

Abstract

The joint study of respiratory and cardiac activity suggests indirect methods to derive the respiratory signal by electrocardiogram (ECG) processing. Potential advantages of such methods are low cost, high convenience, and continuous noninvasive respiratory monitoring. Recent works show that the respiratory signal can be accurately evaluated by single-channel ECG processing. The aim of this paper is to introduce a new method based on the Empirical Mode Decomposition (EMD) for the respiratory signal evaluation. A comparison versus popular algorithms for the respiratory signal extraction is also shown. Preliminary results confirm that EMD algorithm provides better performances, with respect to others, especially in the case of respiratory waveform reconstruction.
978-1-4244-9336-4
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/18546
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