Staff member


Javier Rodríguez Benítez

PhD Student
Biomedical Signal Processing and Interpretation
jrodriguez@ibecbarcelona.eu
+34 934 020 559
Staff member publications

Rodríguez, J. C., Arizmendi, C. J., Forero, C. A., Lopez, S. K., Giraldo, B. F., (2017). Analysis of the respiratory flow signal for the diagnosis of patients with chronic heart failure using artificial intelligence techniques IFMBE Proceedings VII Latin American Congress on Biomedical Engineering (CLAIB 2016) , Springer (Santander, Colombia) 60, 46-49

Patients with Chronic Heart Failure (CHF) often develop oscillatory breathing patterns. This work proposes the characterization of respiratory pattern by Wavelet Transform (WT) technique to identify Periodic Breathing pattern (PB) and Non-Periodic Breathing pattern (nPB) through the respiratory flow signal. A total of 62 subjects were analyzed: 27 CHF patients and 35 healthy subjects. Respiratory time series were extracted, and statistical methods were applied to obtain the most relevant information to classify patients. Support Vector Machine (SVM) were applied using forward selection technique to discriminate patients, considering four kernel functions. Differences between these parameters are assessed by investigating the following four classification issues: healthy subjects versus CHF patients, PB versus nPB patients, PB patients versus healthy subjects, and nPB patients versus healthy subjects. The results are presented in terms of average accuracy for each kernel function, and comparison groups.

Keywords: Chronic heart failure, Forward selection, Non-periodic breathing, Periodic breathing, Support vector machine


Giraldo, B. F., Rodríguez, J., Arcentales, A., Voss, A., Caminal, P., Bayes-Genis, A., (2015). Caracterización de pacientes isquémicos y dilatados a partir de las señales ECG y de presión sanguínea CASEIB Proceedings XXXIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB 2015) , Sociedad Española de Ingeniería Biomédica (Madrid, Spain) , 31-34

Las enfermedades cardiovasculares son una de las principales causas de muerte en países desarrollados. Se han analizado 42 pacientes con cardiomiopatía isquémica (ICM) o dilatada (DCM), clasificados en función de la fracción de eyección ventricular izquierda (LVEF), en grupos de alto riesgo (HR: LVEF


Rodríguez, J. E., Cruz, I., Vergés, E., Ayala, D., (2011). A connected-component-labeling-based approach to virtual porosimetry Graphical Models 73, (5), 296-310

Analyzing the pore-size distribution of porous materials, made up of an aggregation of interconnected pores, is a demanding task. Mercury intrusion porosimetry (MIP) is a physical method that intrudes mercury into a sample at increasing pressures to obtain a pore-size histogram. This method has been simulated in-silice with several approaches requiring prior computation of a skeleton. We present a new approach to simulate MIP that does not require skeleton computation. Our method is an iterative process that considers the diameters corresponding to pressures. At each iteration, geometric tests detect throats for the corresponding diameter and a CCL process collects the region invaded by the mercury. Additionally, a new decomposition model called CUDB, is used. This is suitable for computing the throats and performs better with the CCL algorithm than a voxel model. Our approach obtains the pore-size distribution of the porous medium, and the corresponding pore graph.

Keywords: Micro CT, Pore map, Porous media, Skeleton, Virtual MIP