Contribuições para a análise de sinais neuronais e biomédicos

Following the new tendency of interdisciplinarity of modern science, a new field called neuroengineering has come to light in the last decades. After 2000, scientific journals and conferences all around the world have been created on this theme. The present work comprises three different subareas related to neuroengineering and electrical engineering: neural stimulation; theoretical and computational neuroscience; and neuronal signal processing; as well as biomedical engineering. The research can be divided in three parts: (i) A new method of neuronal photostimulation was developed based on the use of caged compounds. Using the inhibitory neurotransmitter GABA caged by a ruthenium complex it was possible to block neuronal population activity using a laser pulse. The obtained results were evaluated by Wavelet analysis and tested by non-parametric statistics. (ii) A mathematical method was created to identify neuronal assemblies. Neuronal assemblies were proposed as the basis of learning by Donald Hebb remain the most accepted theory for neuronal representation of external stimuli. Using the Marcenko-Pastur law of eigenvalue distribution it was possible to detect neuronal assemblies and to compute their activity with high temporal resolution. The application of the method in real electrophysiological data revealed that neurons from the neocortex and hippocampus can be part of the same assembly, and that neurons can participate in multiple assemblies. (iii) A new method of automatic classification of heart beats was developed, which does not rely on a data base for training and is not specialized in specific pathologies. The method is based on Wavelet decomposition and normality measures of random variables. Throughout, the results presented in the three fields of knowledge represent qualification in neural and biomedical engineering

Participatory design in the project of virtual learning environment of histology

This present article describes a research on the development, under the approach of participatory design, a virtual teaching-learning of Histology in which students and teachers participated actively in all stages of development of the educational environment. We postulates that the development of virtual learning environment of Histology, through the Participatory Design approach, contributes to greater acceptance and use by students and that the adoption of virtual environment for teaching and learning by teachers is a determining factor of use by students

Terapia ocupacional em ação interdisciplinar: jogos educativo-nutricionais na prevenção da obesidade infantil

The inter-subjectivity is the answer in the search for the solution of complex problems, which concerns interfaces of knowledge, respecting their borders. This paradigm is essential in the author's work. So, the search on screen is based on this perspective, by using inter-subject groups of work conduced by professionals of Computer Science, Social Communication, Architecture and Urbanism, Pedagogy, Psicopegagogy, Nutritional Science, Endocrinology, Occupational Therapy and Nursing, it was also part of this group an 8 year old child, daughter of one of the professional who took part of the group. This thesis aims to present the course of investigation developed, analyzing the action of inter-subject Occupational Therapy and Nutrition on the promotion of learning nutritional concepts through educative-nutritional games in order to prevent child's obesity in an educative context. The research was analytic, interventionist and almost experimental. It took place in a public school in Fortaleza, Ceará, Brazil, between August and December 2004. It was selected a sample non-probabilistic, by convenience, of 200 children, born from 1994 to 1996. It was selected almost nonprobabilistically, by convenience, 200 children born between 1994 and 1996. To analyze the results it was used a triangulation, associated by quantitative and qualitative approaches. The basis collect happened through games specially manufactured to these research- video-games, board games, memory games, puzzles, scramble, searching words and iterative basics. There were semi-structured interviews, direct and structured observations and focus in-groups. It was noticed the efficiency of educativenutritional games in the learning process, which lead to a changing of attitude towards the eating choices. These games gave similar results in relation to the compared variations preferences, experience and attitudes, theses attitudes were observed through the game; and the categories to compare the possibility of learning by playing, the fantasy in the learning process, learning concepts of nutritional education and the need of help in the learning process (mediation). It was proved that educativenutritional games could be used to teach nutritional concepts, in an inter-subjective action of Occupational Therapy and Nutrition in schools. The simultaneous application of these games lead to the optimization of child s learning process. It should be emphasized the need of studies about the adaptation of tools used in a child s Nutritional Education, with the help of inter-subjective action. Because just one subject, in a fractionated way can give an answer to complex problems and help to a change of the reality with effectiveness and resolution

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Estratégias baseadas em aprendizado para coordenação de uma frota de robôs em tarefas cooperativas

In multi-robot systems, both control architecture and work strategy represent a challenge for researchers. It is important to have a robust architecture that can be easily adapted to requirement changes. It is also important that work strategy allows robots to complete tasks efficiently, considering that robots interact directly in environments with humans. In this context, this work explores two approaches for robot soccer team coordination for cooperative tasks development. Both approaches are based on a combination of imitation learning and reinforcement learning. Thus, in the first approach was developed a control architecture, a fuzzy inference engine for recognizing situations in robot soccer games, a software for narration of robot soccer games based on the inference engine and the implementation of learning by imitation from observation and analysis of others robotic teams. Moreover, state abstraction was efficiently implemented in reinforcement learning applied to the robot soccer standard problem. Finally, reinforcement learning was implemented in a form where actions are explored only in some states (for example, states where an specialist robot system used them) differently to the traditional form, where actions have to be tested in all states. In the second approach reinforcement learning was implemented with function approximation, for which an algorithm called RBF-Sarsa($lambda$) was created. In both approaches batch reinforcement learning algorithms were implemented and imitation learning was used as a seed for reinforcement learning. Moreover, learning from robotic teams controlled by humans was explored. The proposal in this work had revealed efficient in the robot soccer standard problem and, when implemented in other robotics systems, they will allow that these robotics systems can efficiently and effectively develop assigned tasks. These approaches will give high adaptation capabilities to requirements and environment changes.

Três alternativas estocásticas para modelar morbimortalidade por doenças respiratórias e cardiovasculares via variáveis atmosféricas

Climate and air pollution, among others, are responsible factors for increase of health vulnerability of the populations that live in urban centers. Climate changes combined with high concentrations of atmospheric pollutants are usually associated with respiratory and cardiovascular diseases. In this sense, the main objective of this research is to model in different ways the climate and health relation, specifically for the children and elderly population which live in São Paulo. Therefore, data of meteorological variables, air pollutants, hospitalizations and deaths from respiratory and cardiovascular diseases a in 11-year period (2000-2010) were used. By using modeling via generalized estimating equations, the relative risk was obtained. By dynamic regression, it was possible to predict the number of deaths through the atmospheric variables and the betabinomial-poisson model was able to estimate the number of deaths and simulate scenarios. The results showed that the risk of hospitalizations due to asthma increases approximately twice for children exposed to high concentrations of particulate matter than children who are not exposed. The risk of death by acute myocardial infarction in elderly increase in 3%, 6%, 4% and 9% due to high concentrations CO, SO2, O3 and PM10, respectively. Regarding the dynamic regression modeling, the results showed that deaths by respiratory diseases can be predicted consistently. The beta-binomial-poisson model was able to reproduce an average number of deaths by heart insufficiency. In the region of Santo Amaro the observed number was 2.462 and the simulated was 2.508, in the Sé region 4.308 were observed and 4.426 simulated, which allowed for the generation of scenarios that may be used as a parameter for decision. Making with these results, it is possible to contribute for methodologies that can improve the understanding of the relation between climate and health and proved support to managers in environmental planning and public health policies.