Obstructive Sleep Apnea Detection Methods Based on Heart Rate Variability Analysis: Opportunities for a Future Cinc Challenge. - Daniele Padovano; Arturo Martínez-Rodrigo; José Manuel Pastor 001; José Joaquín Rieta; Raúl Alcaraz 001 (CinC, 2020)

Hidden Hazards Beneath Cross-Validation Methods in Machine Learning-Based Sleep Apnea Detection. - Daniele Padovano; Arturo Martínez-Rodrigo; José Manuel Pastor 001; José Joaquín Rieta; Raúl Alcaraz 001 (CinC, 2022)

On the Generalization of Sleep Apnea Detection Methods Based on Heart Rate Variability and Machine Learning. - Daniele Padovano; Arturo Martínez-Rodrigo; José Manuel Pastor 001; José Joaquín Rieta; Raúl Alcaraz 001 (IEEE Access, 2022)

Comparison of Machine Learning and Deep Learning Methods Based on Recurrence Analysis for Obstructive Sleep Apnea Detection. - Daniele Padovano; Arturo Martínez-Rodrigo; José Manuel Pastor 001; José Joaquín Rieta; Raúl Alcaraz 001 (CinC, 2023)

Intelligent Heart Rate Monitoring from a Social Robot. - Arturo Martínez-Rodrigo; José Carlos Castillo 001; Sara Carrasco-Martínez; Daniele Padovano; Ângelo Costa (ISAmI, 2023)

A Novel Nonlinear Method for Cardiovascular Data Synchronization. - Daniele Padovano; Arturo Martínez-Rodrigo; Norbert Marwan; Santiago Mula Muñoz; José Joaquín Rieta; Raúl Alcaraz 001 (IEEE Access, 2025)