**1. Introduction**

Atrial fibrillation (AF) has been described as the arrhythmia of the twenty-first century given that it is the most commonly diagnosed sustained cardiac arrhythmia, affecting up to 1% of the general population and up to 15% of the population older than 70 years of age [1, 2]. Despite extensive research during the last decades, it is still unclear how AF starts and perpetuates itself [2]. Once AF appears, its usual evolution presents three different stages [3]. In the first one, named paroxysmal AF (PAF), patients present auto-limited episodes with a duration shorter than seven days, which terminate spontaneously without the need of medical inter‐ vention. However, approximately between 15 and 31% of PAF patients progress to permanent AF in four to eight years [4]. During this progression, recurrent episodes normally appear, but it is also still unknown why the duration of these episodes varies from patient to patient and from episode to episode [5]. Therefore, once a PAF episode has terminated spontaneously, the early prediction of the onset of the next PAF episode is a relevant clinical challenge. Such a prediction may minimize risks for AF patients and improve their quality of life, since a preventive therapy may be used to avoid recurrence of the arrhythmia. Thus, the maintenance of normal sinus rhythm may reduce symptoms, get better hemodynamics, and minimize the atrial remodeling, which increases the probability of recurrence of AF [6]. Moreover, the risk of suffering thromboembolic events can also be notably reduced [2].

The normal electrical conduction in the heart is generated by the sinoatrial node and is propagated throughout the right atrium and through the Bachmann's bundle to the left atrium, thus defining the P-wave in the electrocardiogram (ECG). However, when this progressive conduction is altered by accessory pathways, reentries, or conduction delays, the P-wave morphology will reflect this fact [7]. Currently, it is well known that both slowed conduction velocity as well as inhomogeneous cell refractory periods in several atrial regions are atrial electrophysiological alterations provoking and maintaining AF [8]. Such atrial conduction abnormalities result in prolonged and highly variable P-waves [9]. Thereby, the analysis of the P-wave has gained increasing interest in the last years [10].

Within this context, the noninvasive P-wave analysis has been performed, following two main recording approaches. On the one hand, it has been based on the standard 12-lead ECG [11]. On the other hand, some authors have based their studies on the P-wave vector magnitude obtained from Frank's orthogonal leads [12]. However, in both alternatives, only averagedsignal P-waves have been widely analyzed in order to minimize the shortcomings derived from the relatively low amplitude of this wave in the ECG [13]. Indeed, the duration of the averaged P-wave has been widely analyzed, and its prolongation has been associated with history of AF, development of arrhythmia after bypass surgery, and progression from paroxysmal to persistent AF [9]. Additionally, the fragmentation of the P-wave template has also been broadly studied from the spectral, gaussian, and wavelet domains [14, 15, 16]. In this case, a wide variety of features associated with the P-wave morphology have provided the ability to discern between PAF patients and healthy subjects [15, 16], to quantify the effects of different antiarrhythmic drugs [17], and to stratify the risk of recurrence of AF after electrical cardioversion [14], catheter ablation [18, 19], and coronary artery bypass grafting [20].

However, recording of the signal-averaged P-wave is not today a common practice in the clinical routine [21]. Moreover, this kind of analysis does not allow to exploit the information contained in every individual P-wave. Indeed, consecutive P-wave averaging hinders the interesting possibility of characterizing every single P-wave as well as its variability across time. Furthermore, the ability of all the previously defined signal-averaged P-wave features to stratify the risk of PAF has also proven to be seriously reduced when long-term ECG recordings, longer than 30 minutes, with no more than two or three available leads are analyzed [22, 23, 24]. Hence, further studies are required to tackle the crucial issue about the minimum time gap required between the detection of P-wave feature alterations that potentially would provoke the onset of PAF. Within this context, recent works have introduced new alternatives able to assess the P-wave time and spatial variability from routine clinical recordings. Some of these methods have proven to accurately anticipate the risk of arrhythmia, at least 60 minutes before its onset, which is a relevant advance in turning clinically useful PAF risk predictors [25, 26, 27]. Overall, the purpose of this chapter is to describe the most recent advances presented in the literature for the noninvasive assessment of atrial conduction defects and how the information provided by these methods has allowed significant advances in the prediction of PAF onset from the surface ECG.
