Nuria Ortigosa

Obstacle-Free Pathway Detection by Means of Depth Maps

The detection of surrounding obstacle-free space is an essential task for many intelligent automotive and robotic applications. In this paper we present a method to detect obstacle-free pathways in real-time using depth maps from a pair of stereo images. Depth maps are obtained by processing the disparity between left and right images from a stereo-vision system. The proposed technique assumes that depth of pixels in obstacle-free pathways should increase slightly and linearly from the bottom of the image to the top. The proposed real-time detection checks whether the depth of groups of image columns matches a linear model. Only pixels fulfilling the matching requirements are identified as obstacle-free pathways. Experimental results with real outdoor stereo images show that the method performance is promising.

Raw data extraction from electrocardiograms with Portable Document Format

During the last two decades there has been a thorough research and development of standards and protocols in order to cope with different electrocardiogram formats from heterogeneous acquisition systems. Despite the efforts of public and private consortiums on creating a standardized electrocardiogram (ECG) storage format, there is still not a single one. Indeed, there is also the necessity of access to raw data of the ECGs previously acquired. Most of these documents have been saved as Adobe PDF files, since for medical staff it is an easy format for later visualization. However, this format presents difficulties when trying to access original raw data for subsequent studies and signal analysis. In this manner, this paper presents an application that obtains plain numerical data from ECG files stored with PDF format. Data can also be exported to one of the most common file formats in existence, to be easily accessed thereafter.

Atrial fibrillation subtypes classification using the General Fourier-family Transform

Atrial fibrillation patients can be classified into paroxysmal, persistent and permanent attending to the temporal pattern of this arrhythmia. The surface electrocardiogram hides this differentiation. A classification method to discriminate between the different subtypes of atrial fibrillation by using short segments of electrocardiograms recordings is presented. We will process the electrocardiograms (ECGs) using time-frequency techniques with a global accuracy of 80%. Real cases are evaluated showing promising results for an implementation in a semiautomated diagnostic system.

Heart morphology differences induced by intrauterine growth restriction and preterm birth measured on the ECG at preadolescent age

Intrauterine Growth Restriction (IUGR) and premature birth are associated with higher risk of cardiovascular diseases throughout adulthood. The aim of this study was to evaluate the influence of these factors in ventricular electrical remodeling in preadolescents. Electrocardiography was performed in a cohort of 33-IUGR, 32-preterm with appropriate weight and 60 controls. Depolarization and repolarization processes were studied by means of the surface ECG, including loops and angles corresponding to QRS and T-waves. The angles between the dominant vector of QRS and the frontal plane XY were different among the study groups: controls [20.03°(10.11°-28.64°)], preterm [25.48°(19.79°-33.56°)], and IUGR [27.77°(16.59°-33.23°)]. When compared to controls, IUGR subjects also presented wider angles between the difference of QRS and T-wave dominant vectors and the XY-plane [5.28°±12.15° vs 0.49°±14.15°, p<0.05] while preterm ones showed smaller frontal QRS-T angle [4.68°(2.20°-12.89°) vs 6.57°(2.72°-11.31°), p<0.05]. Thus, electrical remodeling is present in IUGR and preterm preadolescents, and might predispose them to cardiovascular diseases in adulthood. Follow-up studies are warranted.

Fuzzy Free Path Detection from Disparity Maps by Using Least-Squares Fitting to a Plane

A method to detect obstacle-free paths in real-time which works as part of a cognitive navigation aid system for visually impaired people is proposed. It is based on the analysis of disparity maps obtained from a stereo vision system which is carried by the blind user. The presented detection method consists of a fuzzy logic system that assigns a certainty to be part of a free path to each group of pixels, depending on the parameters of a planar-model fitting. We also present experimental results on different real outdoor scenarios showing that our method is the most reliable in the sense that it minimizes the false positives rate.

FUZZY FREE PATH DETECTION BASED ON DENSE DISPARITY MAPS OBTAINED FROM STEREO CAMERAS

In this paper we propose a fuzzy method to detect free paths in real-time using digital stereo images. It is based on looking for linear variations of depth in disparity maps, which are obtained by processing a pair of rectified images from two stereo cameras. By applying least-squares fitting over groups of disparity maps columns to a linear model, free paths are detected by giving a certainty using a fuzzy rule. Experimental results on real outdoor images are also presented.

Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers

Cardiac resynchronization therapy (CRT) is an effective treatment for those patients with severe heart failure. Regrettably, there are about one third of CRT “non-responders”, i.e. patients who have undergone this form of device therapy but do not respond to it, which adversely affects the utility and cost-effectiveness of CRT. In this paper, we assess the ability of a novel surface ECG marker to predict CRT response. We performed a retrospective exploratory study of the ECG previous to CRT implantation in 43 consecutive patients with ischemic (17) or non-ischemic (26) cardiomyopathy. We extracted the QRST complexes (consisting of the QRS complex, the S-T segment, and the T wave) and obtained a measure of their energy by means of spectral analysis. This ECG marker showed statistically significant lower values for non-responder patients and, joint with the duration of QRS complexes (the current gold-standard to predict CRT response), the following performances: 86% accuracy, 88% sensitivity, and 80% specificity. In this manner, the proposed ECG marker may help clinicians to predict positive response to CRT in a non-invasive way, in order to minimize unsuccessful procedures.

Gabor frames for classification of paroxysmal and persistent atrial fibrillation episodes

In this study, we propose a new classification method for early differentiation of paroxysmal and persistent atrial fibrillation episodes, i.e. those which spontaneously or with external intervention will return to sinus rhythm within 7 days of onset from the ones where the arrhythmia is sustained for more than 7 days. Today, clinicians provide patients classification once the course of the arrhythmia has been disclosed. This classification problem is dealt with in this study. We study a sparse representation of surface electrocardiogram signals by means of Gabor frames and afterwards we apply a linear discriminant analysis. Thus, we provide an early discrimination, obtaining promising performances on a heterogeneous cohort of patients in terms of pharmacological treatment and state of progression of the arrhythmia: 95% sensitivity, 82% specificity, 89% accuracy. In this manner, the proposed method can help clinicians to choose the most appropriate treatment using the electrocardiogram, which is a widely available and non-invasive technique. This early differentiation is clinically highly significant in order to choose optimal patients who may undergo catheter ablation with higher success rates.

Classification of persistent and long-standing persistent atrial fibrillation by means of surface electrocardiograms

Abstract Atrial fibrillation, which is the most common cardiac arrhythmia, is typically classified into four clinical subtypes: paroxysmal, persistent, long-standing persistent and permanent. The ability to distinguish between them is of crucial significance in choosing the most suitable therapy for each patient. Nevertheless, classification is currently established once the natural history of the arrhythmia has been disclosed as it is not possible to make an early differentiation. This paper presents a novel method to discriminate persistent and long-standing atrial fibrillation patients by means of a time-frequency analysis of the surface electrocardiogram. Classification results provide approximately 75% accuracy when evaluating ECGs of consecutive unselected patients from a tertiary center and higher than 80% when patients are not under antiarrhythmic treatment or do not have structural heart disease (76% sensitivity and 88% specificity). Moreover, to our knowledge, this is the first study that discriminates between persistent and long-standing persistent subtypes in a heterogeneous population sample and without discontinuing antiarrhythmic therapy to patients. Thus, it can help clinicians to address the most suitable therapeutic approach for each patient.

Classification of atrial fibrillation episodes by means of phase variations of time-frequency transforms

This study aimed to assess an early classification of paroxysmal and persistent atrial fibrillation (AF) episodes by means of the surface ECG on a heterogeneous cohort of patients (in terms of antiarrhythmic treatment and state of evolution of the arrhythmia), which is similar to the context that clinicians find at tertiary centres in their daily work. 129 consecutive unselected patients suffering from an AF episode conformed the study population (23 paroxysmal and 106 persistent). Modulus and phase features extracted from several time-frequency transforms of the ECG were studied, and it was phase variations which arose as determinant providing the best classification results using a Linear Discriminant Analysis classifier trained with 20 signals. Obtained performances for the latter feature were: Accuracy = 83.5% (total correct classifications), Sensitivity = 78.6% (paroxysmal AF episodes correctly classified), Specificity = 84.2% (persistent subjects properly classified). This results would aid electrophysiologists to choose and prescribe the most suitable treatment to lower recurrence and stop the natural progression of the arrhythmia in general scenarios.