1,721,732 research outputs found

    Right ventricular infarction: the role of echocardiography

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    Review article, abstract not availabl

    AUTOMATIC GENERATION OF FUZZY RULES FOR REACTIVE ROBOT CONTROLLERS

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    Basic tasks for navigation of autonomous vehicles can be performed as reactive behaviors, that directly map sensory data into control commands with no need of internal representations. Fuzzy systems can efficiently realize such a direct mapping by means of comprehensible linguistic rules. Automatic learning of rules from representative data simplifies the programming of the control system especially when dealing with dynamically changing environments. We present two methods for the automatic extraction of fuzzy rules from numerical data acquired by recording the choices of a human operator driving the vehicle in representative training situations. They are applied to build a reactive wall-follower, the first component of a more articulated control system for indoor navigation of a TRC Labmate mobile robot. The produced wall-followers are compared in terms of complexity and quality of behavior in actual navigation runs of the robot along arbitrarily shaped walls

    A visual approach for driver inattention detection

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    Monitoring driver fatigue, inattention, and lack of sleep is very important in preventing motor vehicles accidents. A visual system for automatic driver vigilance has to address two fundamental problems. First of all, it has to analyze the sequence of images and detect if the driver has his eyes open or closed, and then it has to evaluate the temporal occurrence of eyes open to estimate the driver's visual attention level. In this paper we propose a visual approach that solves both problems. A neural classifier is applied to recognize the eyes in the image, selecting two candidate regions that might contain the eyes by using iris geometrical information and symmetry. The novelty of this work is that the algorithm works on complex images without constraints on the background, skin color segmentation and so on. Several experiments were carried out on images of subjects with different eye colors, some of them wearing glasses, in different light conditions. Tests show robustness with respect to situations such as eyes partially occluded, head rotation and so on. In particular, when applied to images where people have eyes closed the proposed algorithm correctly reveals the absence of eyes. Next, the analysis of the eye occurrence in image sequences is carried out with a probabilistic model to recognize anomalous behaviors such as driver inattention or sleepiness. Image sequences acquired in the laboratory and while people were driving a car were used to test the driver behavior analysis and demonstrate the effectiveness of the whole approach

    The ultrasonic characterization of myocardial hypertrophy: new prospects

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    The extensive use of ultrasound imaging in cardiology has greatly contributed to expand both its diagnostic possibilities and its utility in the interpretation of physiopathologic mechanisms. Conventional echocardiography is the more specific technique for the diagnosis of myocardial hypertrophy which, in turn, is one of the most important cardiovascular risk factors. The improvement of ultrasound technology may expand the possibility of noninvasive characterization of left ventricular hypertrophy by adding to the already known information about left ventricular mass and function, and that relative to the degree of hypertrophy-related fibrosis. In the present paper the authors reviewed the knowledge about biological and hemodynamic factors which contribute to the development and regression of myocardial hypertrophy. The possible role of new ultrasonic technology in the tissue characterization of myocardial hypertrophy is also discussed
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