Analysis of atrial fibrillation: from electrocardiogram signal processing to clinical management

Abstract

The analysis of atrial fibrillation in non-invasive ECG recordings has received considerable attention in recent years, spurring the development of signal processing techniques for more advanced characterization of the atrial waveforms than previously available. The present paper gives an overview of different approaches to the extraction of atrial activity in the ECG and to the characterization of the resulting atrial signal with respect to its spectral properties. So far, the repetition rate of the atrial waves is the most studied parameter and its significance in clinical management is briefly considered, including the identification of pathomechanisms and prediction of therapy efficacy.

Applications of Signal Analysis to Atrial Fibrillation

“…Segment length can be considered as the most important parameter in AF spectral analysis since it determines the estimation accuracy of the DAF by restricting spectral resolution. It is advisable that the segment length is chosen to be at least a few seconds so as to produce an acceptable variance of the power spectrum [1,2].…”

“…In this respect, the proper analysis and characterization of AF from ECG recordings requires the extraction or cancellation of the signal components associated to ventricular activity, that is, the QRS complex and the T wave. Unfortunately, a number of facts hinder this operation [2]. Firstly, the atrial activity presents in the ECG much lower amplitude, in some cases well under the noise level, than its ventricular counterpart.…”

Detection and removal of ventricular ectopic beats in atrial fibrillation recordings via principal component analysis

“…[6]. However, this extraction requires nonlinear signal processing techniques since the atrial and ventricular activity overlap spectrally and, therefore, cannot be separated by linear filtering [6]. Average beat subtraction (ABS) is the most widespread technique for AA extraction, especially for long-time Holter recordings, which routinely present no more than two or three leads.…”

“…Average beat subtraction (ABS) is the most widespread technique for AA extraction, especially for long-time Holter recordings, which routinely present no more than two or three leads. This method relies on the assumption that the average beat can represent approximately each individual beat [6]. However, QRST morphology is often subject to minor changes caused by respiration, patient movement, etc., and, therefore, QRST residua are often present in the estimated AA [7].…”

“…The atrial activity (AA) signal extraction under the best conditions is crucial in the study of the electrophysiological processes that underlie AF, such as refractory periods, autonomic response, drug effects, etc. [6]. However, this extraction requires nonlinear signal processing techniques since the atrial and ventricular activity overlap spectrally and, therefore, cannot be separated by linear filtering [6].…”