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José Rieta

Universitat Politècnica de València Spain

José Joaquín Rieta: Received the M. Eng. degrees in Image and Sound Engineering from the Universidad Politécnica de Madrid, Spain, in 1991, the M. Sc. degree in Telecommunications and the Ph.D. degree in Biomedical Signal Processing from the Universidad Politécnica de Valencia, Spain, in 1996 and 2003, respectively. He is Full Professor at the Electronic Engineering Department of the Universidad Politécnica de Valencia, becoming Lecturer since 1994. He has taught several subjects related to Electronic and Biomedical Instrumentation, Analog Systems, Data conversion Systems and Control Engineering, and has been the author of several academic publications in these areas. In 2006 he founded the Biosignals & Minimally Invasive Technologies (BioMIT.org) research group in the same University, where is the CEO and responsible of the advanced biomedical signal processing line. His research interests include the application of machine learning, artificial intelligence, statistical and non-linear signal processing to biomedical signals, specially focused in cardiac signals aimed at developing clinical solutions to study, monitor and characterize the cardiovascular system and cardiovascular pathologies.

3chapters authored

Chapters authored

The Contribution of Nonlinear Methods in the Understanding of Atrial Fibrillation

By Raúl Alcaraz and José Joaquín Rieta

Part of the book: Atrial Fibrillation

Applications of Signal Analysis to Atrial Fibrillation

By José Joaquín Rieta and Raúl Alcaraz

Part of the book: Atrial Fibrillation

Recent Advances in the Noninvasive Study of Atrial Conduction Defects Preceding Atrial Fibrillation

By Raúl Alcaraz and José Joaquín Rieta

The P-wave represents the electrical activity in the electrocardiogram (ECG) associated with the heart's atrial contraction. This wave has merited significant research efforts in recent years with the aim to characterize atrial depolarization from the ECG. Indeed, the alterations of the P-wave main time, frequency, and wavelet features have been widely studied to predict the onset of atrial fibrillation (AF), both spontaneously and after a specific treatment, such as pharmacological or electrical cardioversion, catheter ablation, as well as cardiac surgery. To this respect, the P-wave prolongation is today a clinically accepted marker of high risk of suffering AF. However, given the relatively low P-wave amplitude in the ECG, its analysis has been most widely carried out from signal-averaged ECG signals. Unfortunately, these kind of recordings are uncommon in routine clinical practice and, moreover, they obstruct the possibility of studying the information carried by each single P-wave as well as its variability over time. These limitations have motivated the recent development of the beat-to-beat P-wave analysis, which has proven to be very useful in revealing interesting information about the altered atrial conduction preceding the onset of AF. Within this context, the main goal of this chapter is to review the most recent advances reached by this kind of analysis in the noninvasive assessment of atrial conduction alterations. Thus, the chapter will introduce and discuss the existing methods of the beat-to-beat P-wave analysis and their application to predict the onset of AF as well as its advantages and disadvantages compared with the signal-averaged P-wave analysis.

Part of the book: Abnormal Heart Rhythms

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