Computational Tracking of Mental Health in Youth: Latin American Contributions to a Low-Cost and Effective Solution for Early Psychiatric Diagnosis

The early onset of mental disorders can lead to serious cognitive damage, and timely interventions are needed in order to prevent them. In patients of low socioeconomic status, as is common in Latin America, it can be hard to identify children at risk. Here, we briefly introduce the problem by reviewing the scarce epidemiological data from Latin America regarding the onset of mental disorders, and discussing the difficulties associated with early diagnosis. Then we present computational psychiatry, a new field to which we and other Latin American researchers have contributed methods particularly relevant for the quantitative investigation of psychopathologies manifested during childhood. We focus on new technologies that help to identify mental disease and provide prodromal evaluation, so as to promote early differential diagnosis and intervention. To conclude, we discuss the application of these methods to clinical and educational practice. A comprehensive and quantitative characterization of verbal behavior in children, from hospitals and laboratories to homes and schools, may lead to more effective pedagogical and medical intervention

Contribuição para o estudo do embarque de uma rede neural artificial em field programmable gate array (FPGA)

This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing

Desenvolvimento de um sistema de captura de baixo custo destinado a determinação da cinemática humana

The motion capture is a main tool for quantitative motion analyses. Since the XIX century, several motion caption systems have been developed for biomechanics study, animations, games and movies. The biomechanics and kinesiology involves and depends on knowledge from distinct fields, the engineering and health sciences. A precise human motion analysis requires knowledge from both fields. It is necessary then the use of didactics tools and methods for research and teaching for learning aid. The devices for analysis and motion capture currently that are found on the market and on educational institutes presents difficulties for didactical practice, which are the difficulty of transportation, high cost and limited freedom for the user towards the data acquisition. Therefore, the motion analysis is qualitatively performed or is quantitatively performed in highly complex laboratories. Based is these problems, this work presents the development of a motion capture system for didactic use hence a cheap, light, portable and easily used device with a free software. This design includes the selection of the device, the software development for that and tests. The developed system uses the device Kinect, from Microsoft, for its low cost, low weight, portability and easy use, and delivery tree-dimensional data with only one peripheral device. The proposed programs use the hardware to make motion captures, store them, reproduce them, process the motion data and graphically presents the data.