Publications in collaboration with researchers from Universidad CEU San Pablo (38)

2022

  1. Stochastic embeddings of dynamical phenomena through variational autoencoders

    Journal of Computational Physics, Vol. 454

2018

  1. A novel and simple strategy for evolving prototype based clustering

    Pattern Recognition, Vol. 82, pp. 16-30

  2. Simultaneous estimation of deterministic and fractal stochastic components in non-stationary time series

    Physica D: Nonlinear Phenomena, Vol. 374-375, pp. 45-57

2017

  1. Comparing HRV Variability Across Different Segments of a Recording

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 117-132

  2. Frequency Domain Analysis

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 37-68

  3. Heart Rate Variability Analysis with the R package RHRV Preface

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV

  4. How do I Get a Series of RR Intervals from a Clinical/Biological Experiment?

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 147-154

  5. Installing RHRV

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 145-146

  6. Introduction to Heart Rate Variability

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV

  7. Loading, Plotting, and Filtering RR Intervals

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 15-28

  8. Nonlinear and Fractal Analysis

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 69-116

  9. Nonparametric estimation of stochastic differential equations with sparse Gaussian processes

    Physical Review E, Vol. 96, Núm. 2

  10. Putting It All Together, a Practical Example

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 133-144

  11. Time-Domain Analysis

    HEART RATE VARIABILITY ANALYSIS WITH THE R PACKAGE RHRV (SPRINGER), pp. 29-36

2015

  1. A study on the representation of QRS complexes with the optimum number of Hermite functions

    Biomedical Signal Processing and Control, Vol. 22, pp. 11-18

  2. Introducing negative evidence in ensemble clustering application in automatic ECG analysis

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2013

  1. A New Methodology for Nonlinear Heart Function Analysis: Studying Just the Beat Morphology

    2013 COMPUTING IN CARDIOLOGY CONFERENCE (CINC)

  2. A new methodology for nonlinear heart function analysis: Studying just the beat morphology

    Computing in Cardiology

  3. A software toolkit for nonlinear Heart Rate Variability analysis

    Computing in Cardiology

  4. On the accuracy of representing heartbeats with Hermite basis functions

    BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing