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This article presents an interface adaptation methodology to hypermedia systems based on the methodology developed by Barbosa [1], where the site development with breast cancer contents is used to refine the students' knowledge of the healthy area of UFSC who receive in their classroom. While this system was been developed it was defined the adaptation will only occur in the interface shown to the user with the use of different medias during the presentation of the contents which are introduced according to the individual characteristics of the students based on the Multiple Intelligence Theory (MI). [ABSTRACT FROM AUTHOR]

This article presents a methodology for the development in the training system, to be applied in clinical staff, for the use the multiparametric monitor. This training system is personalized to the user's characteristic in the acquisition of information in the medical area, through the use in several ways of presentation of the content (text, flowcharts, drawings and animation), that would be based in the user's cognitive profile (their Multiple Intelligences (MI)). For the accomplishment of such adaptation the methodology proposes the use of MLP (Multi-Layer Perceptron) and IAC (Interaction Activation and Competition) neural network. In an initial evaluation with some user, the adaptation system demonstrated to be more stimulating in the knowledge acquisition than a no adaptation system. [ABSTRACT FROM AUTHOR]

This paper describes a proposed methodology for the development of adaptive sites for use in training, collaborative learning, distance education and, mainly, continuing education, applicable to the operation of hospital equipment by healthcare professionals. The mechanism of adaptation of the site, that employs neural networks of the Multi-layer Perceptron and Interactive Activation and Competition types, is focused on the interface through the use of different media in the presentation of the content. The characteristics of the user are based on the cognitive theory of Multiple Intelligences. The system automatically modifies the form of content presentation using text, flow chart, drawing and animation as well as offering the possibility for the user to explicitly alter the medium through which defined content is presented with the aim of matching this to their current needs. For the evaluation of the proposed method a case study was carried out, based on a multiparametric monitor. The operating manual for the equipment was implemented in two sites: one "adaptive" and one "static" that provide the same content, enabling the carrying out of a motivational evaluation between the different approaches. The results clearly indicate that the benefits to the user are greater using the site with the proposed methodology. [ABSTRACT FROM AUTHOR]

The video-EEG is a non-invasive diagnostic method, characterized for the register of the concomitant electroencephalogram to the writing of a clinical event. This work is a development of computational system to assist the automatic recognition of electrographic epileptic seizure. The system is a video-EEG that has to synchronize, to reproduce video and EEG signals in a computer and emitting a final report with clinical observations. There are applied tools and methodologies for automatic detection of epileptic standards, more specifically, electrographic epileptic seizure, to reach the best performance of the projected system. The pediatrics population is the most benefits with the video-EEG register, in view of the peculiarity of the epileptic seizure in infancy, the difficulty of these patients in describing subjective phenomena and characterizing the nature of an event, exactly when this is attended by a professional. However, the children represent a great challenge for the accomplishment of the long-term video- EEG, in view of hospitalization as an important stressor factor, as well as, the difficulty of the child in understanding the procedure. There are few publications on the diagnostic value of the video-EEG of short duration with pediatrics patients. The application of mathematic tools and methodologies for automatic detection of electrographic epileptic seizure improve the performance of the system. [ABSTRACT FROM AUTHOR]