Publikationen (75) Publikationen von JESUS MARIA RODRIGUEZ PRESEDO

2018

  1. Heartbeat Classification Using Abstract Features from the Abductive Interpretation of the ECG

    IEEE Journal of Biomedical and Health Informatics, Vol. 22, Núm. 2, pp. 409-420

  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 Method for Context-Based Adaptive QRS Clustering in Real Time

    IEEE Journal of Biomedical and Health Informatics, Vol. 19, Núm. 5, pp. 1660-1671

  2. A Noise Robust QRS Delineation Method Based on Path Simplification

    2015 COMPUTING IN CARDIOLOGY CONFERENCE (CINC)

  3. A noise robust QRS delineation method based on path simplification

    Computing in Cardiology

  4. 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

2014

  1. Using temporal abduction for biosignal interpretation: A case study on QRS Detection

    Proceedings - 2014 IEEE International Conference on Healthcare Informatics, ICHI 2014