Senén Barro

Algorithmic sequential decision-making in the frequency domain for life threatening ventricular arrhythmias and imitative artefacts: a diagnostic system

A preliminary study to approach the problem of reliably detecting life threatening ventricular arrhythmias in real time is described. An algorithm (DIAGNOSIS) has been developed in order to classify ECG signal records on the basis of the computation of four simple parameters calculated from a representation in the frequency domain. This algorithm uses a set of rules constituting an operative classification scheme based on the comparison of the parameters with a set of pre-established thresholds. This allows us to differentiate four general categories: ventricular fibrillation-flutter, ventricular rhythms, imitative artefacts and predominant sinus rhythm.

Fuzzy Logic in Medicine

A Call for a Stronger Role for Fuzzy Logic in Medicine.- Fuzzy Information Granulation of Medical Images. Blood Vessel Extraction from 3-D MRA Images.- Breast Cancer Classification Using Fuzzy Central Moments.- Awareness Monitoring and Decision-Making for General Anaesthesia.- Depth of Anesthesia Control with Fuzzy Logic.- Intelligent Alarms for Anaesthesia Monitoring Based on a Fuzzy Logic Approach.- Fuzzy Clustering in Medicine: Applications to Electrophysiological Signal Processing.- Fuzzy Logic in a Decision Support System in the Domain of Coronary Heart Disease Risk Assessment.- A Model-based Temporal Abductive Diagnosis Model for an Intensive Coronary Care Unit.- A Fuzzy Model for Pattern Recognition in the Evolution of Patients.- Mass Assignment Methods for Medical Classification Diagnosis.- Acquisition of Fuzzy Association Rules from Medical Data.

A model and a language for the fuzzy representation and handling of time

Abstract In this paper we present a model for the representation and handling of fuzzy temporal references. We define the concepts of date, time extent, and interval, according to the formalism of possibility theory. We introduce relations between the temporal entities dates and intervals, interpreted as constraints on the distance between dates and projected onto Fuzzy Temporal Constraint Satisfaction Networks. We introduce a language for the representation and manipulation of temporal entities and relations, which captures some of the terms we use in our expressions in the natural language and therefore, it is a flexible and powerful interface for those systems in which the representation of fuzzy temporal information is necessary. Our approach permits a common interpretation of qualitative and quantitative temporal relations, facilitating the relativization of the meaning of the temporal relations to each specific application context and the verification of relations between temporal entities.

Intelligent telemonitoring of critical-care patients

Sutil+ is an intelligent monitoring system that is under development. The aim is to endow the system with more intelligent behaviour and to make the presentation of information to the user as flexible as possible, in space, time, and form. We present two telemonitoring solutions that enable access to information resulting from the monitoring of patients in coronary care units, independent of the location of the system user. We concentrate on aspects of data acquisition and storage and, above all, interaction with the user.

Classifying multichannel ECG patterns with an adaptive neural network

In this article the authors describe the application of a new artificial neural network model aimed at the morphological classification of heartbeats detected on a multichannel ECG signal. They emphasize the special characteristics of the algorithm as an adaptive classifier with the capacity to dynamically self-organize its response to the characteristics of the ECG input signal. They also present evaluation results based on traces from the MIT-BIH arrhythmia database.

Design of a fuzzy controller in mobile robotics using genetic algorithms

The design of fuzzy controllers for the implementation of behaviors in mobile robotics is a complex and highly time-consuming task. The use of machine learning techniques, such as evolutionary algorithms or artificial neural networks for the learning of these controllers allows to automate the design process. In this paper, the automated design of a fuzzy controller using genetic algorithms for the implementation of the wall-following behavior in a mobile robot is described. The algorithm is based on the Iterative Rule Learning (IRL) approach, and a parameter (@d) is defined with the aim of selecting the relation between the number of rules and the quality and accuracy of the controller. The designer has to define the universe of discourse and the precision of each variable, and also the scoring function. No restrictions are placed neither in the number of linguistic labels nor in the values that define the membership functions.

Time-frequency analysis of heart-rate variability

We present the results of a study that shows the viability of a new technique for the diagnosis and monitoring of myocardial ischemia that is based on the utilization of heart-rate variability (HRV) information. Ischemia is understood as being the lack of oxygen supply to the heart, a situation that in an extreme and irreversible case results in acute myocardial infarction (AMI), a reason for which early detection and treatment is of great interest. The treatment of ischemia can be approached via the evolution of the ECG, and especially from one of the parameters extracted from it-the ST segment (ECG signal between S and T waves) deviation. The utility of this measure is found in its capacity for detecting abnormalities in the conduction of the cardiac impulse that are associated with the presence of ischemia.

SUTIL: Intelligent ischemia monitoring system

SUTIL is an intelligent monitoring system for intensive and exhaustive follow up of patients in coronary care units. This system processes electrocardiographic and hemodynamic signals in real time, with the main objective of detecting ischemic episodes. In this paper, we describe the tasks included in SUTIL. In addition to basic tasks, those at higher levels will also be presented. Some of these latter tasks attempt to mimic, to some extent, the way in which the human expert operates.

A framework for fuzzy quantification models analysis

A framework for description of fuzzy quantification models is presented. Within this framework, the fuzzy quantified statements evaluation problem is described as the compatibility between the fuzzy quantifier and a fuzzy cardinality or a fuzzy aggregation measure. A list of desirable properties for quantification models is presented and those models that fit the framework are confronted with it.

On the role of linguistic descriptions of data in the building of natural language generation systems

This paper explores the current state of the task of generating easily understandable information from data for people using natural language, which is currently addressed by two independent research fields: the natural language generation field - and, more specifically, the data-to-text sub-field - and the linguistic descriptions of data field. Both approaches are explained in a detailed description which includes: i) a methodological revision of both fields including basic concepts and definitions, models and evaluation procedures; ii) the most relevant systems, use cases and real applications described in the literature. Some reflections about the current state and future trends of each field are also provided, followed by several remarks that conclude by hinting at some potential points of mutual interest and convergence between both fields.