Schizophrenia is a chronic mental illness, characterized by the loss of the notion of reality, failing to distinguish it from the imaginary. It affects the patient in life’s major areas, such as work, interpersonal relationships, or self-care, and the usual treatment is performed with the help of anti-psychotic medication, which targets primarily the hallucinations, delirium, etc. Other symptoms, such as the decreased emotional expression or avolition, require a multidisciplinary approach, including psychopharmacology, cognitive training, and many forms of therapy. In this context, this paper addresses the use of digital technologies to design and develop innovative rehabilitation techniques, particularly focusing on mental health rehabilitation, and contributing for the promotion of well-being and health from a holistic perspective. In this context, serious games and virtual reality allows for creation of immersive environments that contribute to a more effective and lasting recovery, with improvements in terms of quality of life. The use of machine learning techniques will allow the real-time analysis of the data collected during the execution of the rehabilitation procedures, as well as enable their dynamic and automatic adaptation according to the profile and performance of the patients, by increasing or reducing the exercises’ difficulty. It relies on the acquisition of biometric and physiological signals, such as voice, heart rate, and game performance, to estimate the stress level, thus adapting the difficulty of the experience to the skills of the patient. The system described in this paper is currently in development, in collaboration with a health unit, and is an engineering effort that combines hardware and software to develop a rehabilitation tool for schizophrenic patients. A clinical trial is also planned for assessing the effectiveness of the system among negative symptoms in schizophrenia patients.
The continuous development of graphics hardware is contributing to the creation of 3D virtual worlds with high level of detail, from models of large urban areas, to complete infrastructures, such as residential buildings, stadiums, industrial settings or archaeological sites, to name just a few. Adding virtual humans or avatars adds an extra touch to the visualization providing an enhanced perception of the spaces, namely adding a sense of scale, and enabling simulations of crowds. Path planning for crowds in a meaningful way is still an open research field, particularly when it involves an unknown polygonal 3D world. Extracting the potential paths for navigation in a non automated fashion is no longer a feasible option due to the dimension and complexity of the virtual environments available nowadays. This implies that we must be able to automatically extract information from the geometry of the unknown virtual world to define potential paths, determine accessibilities, and prepare a navigation structure for real time path planning and path finding. A new image based method is proposed that deals with arbitrarily a priori unknown complex virtual worlds, namely those consisting of multilevel passages (e.g. over and below a bridge). The algorithm is capable of extracting all the information required for the actual navigation of avatars, creating a hierarchical data structure to help both high level path planning and low level path finding decisions. The algorithm is image based, hence it is tessellation independent, i.e. the algorithm does not rely on the underlying polygonal structure of the 3D world. Therefore, the number of polygons does not have a significant impact on the performance, and the topology has no weight on the results.
In this paper we present ASAP - Automated Search with Agents in PubMed, a web-based service aiming to manage and automate scientific literature search in the PubMed database. The system allows the creation and management of web agents, parameterized thematically and functionally, that crawl the PubMed database autonomously and periodically, aiming to search and retrieve relevant results according the requirements provided by the user. The results, containing the publications list retrieved, are emailed to the agent owner on a weekly basis, during the activity period defined for the web agent. The ASAP service is devoted to help researchers, especially from the field of biomedicine and bioinformatics, in order to increase their productivity, and can be accessed at: http://esa.ipb.pt/~agentes.
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