My name is Antonio R Hidalgo-Muñoz. I graduated in Telecommunication Engineering from the University of Seville (Spain) in 2008, specialty in digital signal processing. My thesis dissertation dealt with physiological signal processing (specifically, EEG for affective computing) by applying machine learning techniques. My PhD was co-supervised by Dr. Manuel Vázquez Marrufo from the Department of Experimental Psychology at University of Seville and Dr. Ana Maria Tomé from the Institute of Electronics and Informatics Engineering of Aveiro (Portugal). I obtained my diploma with the highest distinction in 2013 and my thesis awarded one of the PhD Extraordinary Awards in Health Sciences of the University of Seville in 2016. During my academic career, I have conducted research into different sort of clinical data and physiological signals, including time signals as ECG or EEG, and MRI. Interestingly, in 2014 – 2015, I worked on the analysis on cardiac signals (both noninvasive standard 12-ECG leads and coronary sinus activity) to study atrial fibrillation (AF), the most prevalent cardiac arrhythmia, in the Laboratory of Computer Sciences, Signals and Systems at the University of Nice Sophia Antipolis (France). During my stay, I investigated relevant spectral and spatiotemporal ECG parameters in order to predict catheter ablation outcome at long-tem in patients suffering from persistent AF, resulting in the publication of 8 full papers in international conferences and journals. In 2016, I started to work in the CLLE-LTC group at the University of Toulouse II – Jean Jaurès (France), where I have implemented a protocol to evaluate both cognitive workload and emotional state in pilots by means of physiological measures, including cardiovascular activity. Currently, I collaborate with the French institute of science and technology for transport, development and networks in Lyon (France) and with SIPBA (Signal processing and biomedical applications) group at the University of Granada (Spain).

My research interests are:Advanced ECG signal processing, Atrial fibrillation and Cardiovascular activity linked to cognitive workload and emotion