BOOK CHAPTERS
1. C. Sanchez, JJ. Rieta, F. Castells, R. Alcaraz, J. Millet, “Wavelet Domain Blind Signal Separation to Analyze Supraventricular Arrhythmias from Holter Registers”, Lecture Notes in Computer Science (Springer-Verlag Berlin Heidelberg), vol. 3195, pp. 1111-1117, 2004.
2. R. Alcaraz, JJ. Rieta “The contribution of nonlinear methods in the understanding of atrial fibrillation” in Atrial Fibrillation — Mechanisms and Treatment, Tong Liu (Ed.), chap. 8, InTech Open Science, 2013.
3. J J. Rieta, R. Alcaraz, “Application of signal analysis to atrial fibrillation” in Atrial Fibrillation — Mechanisms and Treatment, L. Sörnmo (Ed.), chap. 6, InTech Open Science, 2013.
4. L. Sörnmo, R. Alcaraz, P. Laguna, JJ. Rieta, “Characterization of f waves”, In: Sörnmo, L. (Eds) Atrial Fibrillation from an Engineering Perspective. Series in BioEngineering. Springer, Cham. https://doi.org/10.1007/978-3-319-68515-1_6.
5. R. Alcaraz, JJ. Rieta, “Analysis in atrial fibrillation”, In: Golemati, S., Nikita, K. (eds) Cardiovascular Computing—Methodologies and Clinical Applications. Series in BioEngineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-5092-3_17

SELECTED INTERNATIONAL JOURNALS (FROM MORE THAN 80 PUBLICATIONS)
1. M. García, M. Martínez-Iniesta, J. Ródenas, JJ. Rieta, R. Alcaraz, “A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation“, Physiological Measurement, vol. 39, no. 11, pp. 115006, 2018.
2. A. Martinez-Rodrigo, B. Garcia-Martinez, R. Alcaraz, P. González, A. Fernandez-Caballero, “Multiscale entropy analysis for recognition of visually elicited negative stress from EEG recordings“, International Journal of Neural Systems, vol. 29, no. 2, pp. 1850038, 2019.
3. M. Martínez-Iniesta, J. Ródenas, JJ. Rieta, R. Alcaraz, “The stationary wavelet transform as an efficient reductor of powerline interference for atrial bipolar electrocardiograms in cardiac electrophysiology“, Physiological Measurement, vol. 40, no. 7, pp. 075003, 2019.
4. A Martínez-Rodrigo, B. García-Martínez, L. Zunino, R. Alcaraz, A. Fernández-Caballero, “Multi-Lag Analysis of Symbolic Entropies on EEG Recordings for Distress Recognition“,  Front. Neuroinform., vol. 13, pp. 40, 2021. 
5. A. Huerta, A. Martinez-Rodrigo, V. Bertomeu-González, A. Quesada, JJ. Rieta, R. Alcaraz, “A deep learning approach for featureless robust quality assessment of intermittent atrial fibrillation recordings from portable and wearable devices“, Entropy, vol. 22, no.7, pp. 733, 2020.
6. R. Alcaraz, A. Martinez-Rodrigo, R. Zangroniz, JJ. Rieta, “Blending inverted lectures and laboratory experiments to improve learning in an introductory course in digital systems“, IEEE Transactions on Education, vol. 63, no. 3, pp. 144-154, 2020.
7. SB. Chen, F. Rajaee, A. Yousefpour, R. Alcaraz, YM. Chu, JF. Gómez-Aguilar, S. Bekiros, AA. Aly, H. Jahanshahi, “Antiretroviral therapy of HIV infection using a novel optimal type-2 fuzzy control strategy“, Alexandria Engineering Jornal, vol. 60, no. 1, pp. 1545-1555, 2021.
8. PY. Xiong, H. Jahanshahi, R. Alcaraz, YM. Chu, JF. Gómez-Aguilar, FE. Alsaadi, “Spectral entropy analysis and synchronization of multi-stable fractional-order chaotic system using a novel neural network-based chattering-free sliding mode technique“, Chaos, Solitons & Fractals, vol. 144, pp. 110576, 2021.
9. B. Garcia-Martinez, A. Martinez-Rodrigo, R. Alcaraz, A. Fernandez-Caballero, “A review o nonlinear methods using electroencephalographic recordings for emotion recognition“, IEEE Transaction on Affective Computing, vol. 12, no. 3, pp. 801-820, 2021.
10. R. Alcaraz, A. Martinez-Rodrigo, R. Zangroniz, JJ. Rieta, “Early prediction of students at risk of failing a face-to-face course in power electronic systems“, IEEE Transactions on Learning Technologies, vol 14, no. 5, pp. 590-603, 2021.
11. B.García-Martinez, A. Fernandez-Caballero, R. Alcaraz, A. Martinez-Rodrigo, “Assessment of dispersion patterns for negative stress detection from electroencephalographic signals“, Pattern Recognition, vol. 119, pp. 108094, 2021.
12. B. García-Martínez, A. Fernández-Caballero,  R. Alcaraz, A. Martínez-Rodrigo, “Cross-sample entropy for the study of coordinated brain activity in calm and distress conditions with electroencephalographic recordings“. Neural Comput & Applic, vol. 33, pp. 9343–9352, 2021.
13. D. Padovano, A. Martinez-Rodrigo, JM. Pastor, JJ. Rieta, R. Alcaraz, “On the generalization of sleep detection methods based on heart rate variability and machine learning“, IEEE Access, vol. 10, pp. 92710-92725, 2022.
14. B. Garcia-Martinez, A. Fernandez-Caballero, R. Alcaraz, A. Martinez-Rodrigo, “Application of dispersion entropy for the detection of emotions with electroencephalographic signals“, IEEE Transactions on Cognitive and Developmental Systems, vol. 14, no. 3, pp. 1179-1187, 2022.
15. A. Huerta, A. Martinez-Rodrigo, D. Carneiro, V. Bertomeu-González, JJ. Rieta, R. Alcaraz, “Comparison of supervised learning algorithms for quality assessment of wearable electrocardiograms with paroxysmal atrial fibrillation“, IEEE Access, vol. 11, pp. 106126-106140, 2023.
16. P. Escribano, J. Ródenas, M. García, MA. Arias, VM. Hidalgo, S. Calero, JJ. Rieta, R. Alcaraz, “Combination of frequency and time domain characteristics of the fibrillatory waves for enhanced prediction of persistent atrial fibrillation recurrence after catheter ablation“, Heliyon, vol. 10, pp. e25295, 2024.
17. P. Escribano, J. Ródenas, M. García, F. Hornero, J.M. Gracia-Baena, R. Alcaraz, JJ. Rieta, “Novel entropy-based metrics for long-term atrial fibrillation recurrence prediction following surgical ablation: Insights from preoperative electrocardiographic analysis“, Entropy, vol. 26, no. 1, pp. 28, 2024.
18. A. Huerta, A. Martinez-Rodrigo, V. Bertomeu-González, O. Ayo-Martin, JJ. Rieta, R. Alcaraz, “Single-lead electrocardiogram quality assessment in the context of paroxysmal atrial fibrillation through phase space plots“, Biomedical Signal Processing and Control, vol. 91, pp. 105920, 2024.

SELECTED INTERNATIONAL CONFERENCES (FROM MORE THAN 200 PUBLICATIONS)
1. R. Alcaraz, F. Sandberg, L. Sörnmo, JJ. Rieta, (invited paper), “Application of frequency and sample entropy to discriminate long-term recordings of paroxysmal and persistent atrial fibrillation”, 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4558-4561, 2010, Buenos Aires (Argentina).
2. A. Martínez, R. Alcaraz, JJ. Rieta, (invited paper), “Detection and removal of ventricular ectopic beats in atrial fibrillation recordings via principal component analysis”, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4693-4696, 2011, Boston (USA).
3. R. Alcaraz, F. Hornero, JJ. Rieta (invited paper), “Validation of surface atrial fibrillation organization indicators through invasive recordings”, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 5519-5522, 2011, Boston (USA).
4. JJ. Rieta, R. Alcaraz, (invited paper) “Novel parameters for AF complexity”, First European Conference for Standarization of Advanced ECG Analysis in Arrhythmia Diagnostics, 2013, Lugano (Switzerland).
5. A. Huerta, A. Martinez-Rodrigo, V. Bertomeu-Gonzalez, A. Quesada, JJ. Rieta, R. Alcaraz, “Quality assessment of very long-term ECG recordings using a convolutional neural network“, 7th IEEE E-Health and Bioengineering Conference (EHB), pp. 8970077, 2019. (19 citas, FWCI 3.18).  
6. D. Padovano, A. Martinez-Rodrigo, JM. Pastor, JJ. Rieta, R. Alcaraz, “An experimental review on obstructive sleep apnea detection based on heart rate variability and machine learning techniques“, 8th IEEE E-Health and Bioengineering Conference (EHB), pp. 9280302, 2020. (4 citas, FWCI 0.95).
7. A. Vraka, V. Bertomeu-González, J. Osca, F. Ravelli, R. Alcaraz, JJ. Rieta, “Study on how catheter ablation affects atrial structures in patients with paroxysmal atrial fibrillation: The case of the coronary sinus“, 8th IEEE E-Health and Bioengineering Conference (EHB), pp. 9280243, 2020. (6 citas, FWCI 1.43).
8. A. Huerta, V. A. Martinez-Rodrigo, JJ. Rieta, R. Alcaraz, “ECG quality assessment via deep learning and data augmentation“, Computing in Cardiology, 2021. (4 citas, FWCI 1.11).