Alfredo Goñi

Learn More
The new advances in sensor technology, personal digital assistants (PDAs), and wireless communications favor the development of a new type of monitoring system that can provide patients with assistance anywhere and at any time. Of particular interest are the monitoring systems designed for people that suffer from heart arrhythmias, due to the increasing(More)
Patients suspected of suffering sleep apnea and hypopnea syndrome (SAHS) have to undergo sleep studies such as expensive polysomnographies to be diagnosed. Healthcare professionals are constantly looking for ways to improve the ease of diagnosis and comfort for this kind of patients as well as reducing both the number of sleep studies they need to undergo(More)
One important area of research that has emerged in recent years is the assessment of factors that contribute to the development of body image problems and, more concretely, to the development of body dissatisfaction. The female sociocultural beauty ideal, a constant object of research for over three decades now, is so ultra-thin that it is both unattainable(More)
The evolving telecommunications industry combined with medical information technology has been proposed as a solution to reduce health care cost and provide remote medical services. This paper aims to validate and show the feasibility and user acceptance of using a telerehabilitation system called Kinect Rehabilitation System (KiReS) in a real scenario,(More)
syntax. Assume a conceptualization as shown in Fig. 6, describing different kinds of illnesses and their relationships. Assume that there are also two symptoms Symptom1 and Symptom2whose conceptualization –accorded by the ontology designersclassifies them as subsumees of IllnessB and IllnessA2, respectively (i.e., it is admitted by ontology designers that(More)
We propose a new algorithm to detect and classify transient cardiac ischemia episodes, designed with the goal of providing a real-time execution without penalizing the classifier accuracy much. The algorithm is based on a novel mixture of time-domain analysis and machine learning techniques, specifically bagging of decision trees, and it has been developed(More)