Anxiety reducing through a neurofeedback serious game with dynamic difficulty adjustment

Presently, society has to deal with a large number of mental issues. Anxiety disorder is a serious concern, affecting millions of people’s lives and, although methods to tackle the problem currently exist, these main treatments are being linked to some issues and improvements must be found. One of the alternatives is Neurofeedback, a biofeedback treatment, completely non-invasive and showing impressive results so far. It uses a neuroheadset equipment to read the neural activity of the brain, giving the user visual feedback about it. The purpose this, is to train the users’ brain in specific regions and frequencies, allowing the subjects to learn how to voluntarily control its neural activity, even outside of the session. Current applications using this method might be too simple, which can become tedious and disengaging. Serious games can help with these issues, since it can bring enjoyment and engagement while doing this type of treatment. The interest in games’ capabilities in education has been increasing over the past years, since it has been proved that games are an excellent tool for education and skill learning. Joining these concepts of game and neurofeedback, this project aims to create a serious game prototype, applying the current treatment knowledge. The development process of a new game with neuroheadset integration, capable of reading the neural activity of the user while playing and giving the appropriate feedback, will be described in the present document. Since studies proved that a good balance between challenge and skill increases the learning performance, a dynamic difficulty adjustment system is implemented within the game, allowing the game to adapt itself to each user’s skill individually, and keeping the user in a challenging, motivating zone. At the end of the document, the results of pilot test on a few subjects are shown.Na sociedade actual o número de problemas relacionados com perturbações mentais tem sido cada vez mais relevante, sendo esse o caso da ansiedade. O distúrbio de ansiedade é um problema que atinge milhões de pessoas e, embora existam métodos para combater este problema, estudos comprovam que estes têm algumas lacunas que podem trazer outros problemas associados, sendo portanto necessário procurar melhorias aos métodos actuais. Uma das alternativas tem apresentado excelentes resultados e denomina-se Neurofeedback. Este é um tratamento de biofeedback, nãoinvasivo e que utiliza um equipamento neuroheadset para capturar a actividade neuronal, apresentando indicações visuais sobre o comportamento do utilizador. Isto é feito com o objectivo de treinar o cérebro do utilizador, em regiões e frequências específicas, para que este seja capaz de controlar voluntariamente a sua actividade neuronal. As aplicações actualmente utilizadas com este intuito podem se tornar aborrecidas e monótonas devido à sua simplicidade. Um jogo sério pode ajudar com estes problemas, uma vez que é capaz de trazer divertimento e motivação para este tipo de tratamento. O crescente interesse nas capacidades educativas dos jogos sérios, tem identificado estes como excelentes ferramentas para a educação. Este projecto pretende portanto criar um protótipo de um jogo sério, aplicando os conceitos de neurofeedback. Neste documento, é apresentado o processo de desenvolvimento de um novo jogo com integração de um neuroheadset, capaz de identificar a actividade neuronal do jogador dando respostas adequadas. Uma vez que estudos comprovam que um bom balanço entre desafio apresentado e técnica do utilizador aumenta a capacidade de aprendizagem, foi implementado também um sistema de ajuste de dificuldade dinâmica, permitindo uma adaptação do jogo a cada indivíduo e mantendo este numa zona motivante de equilíbrio entre desafio e proficiência. No final serão apresentados os resultados de um teste piloto efectuado em alguns indivíduos

Recognizing Activities of Daily Living of People with Parkinson's

Tese de mestrado, Informática, Universidade de Lisboa, Faculdade de Ciências, 2022Parkinson's disease is a common neurodegenerative disease that affects a large part of the world's population. This disease involves a lot of symptoms, however the most prevalent is the change in the patient's movements or even the loss of functionality. There is no treatment, however it exists medication that relieves and reduces the symptoms for a period. A Parkinson’s patient needs to be watched by clinicians to understand if the medication is working correctly and to analyse the disease progression. The current way of doing this evaluation is at clinics where the patient needs to go to the clinic or to live there. With this into consideration it was requested a monitoring system of activities of daily living for Parkinson’s patient. The monitoring system consists in a mobile application in an Android smartphone serving as a diary for the patient of clinician to record the activities done at that moment. With this application, the patient needs to wear an accelerometer in the wrist to gather the acceleration in the 3-axis. The application besides the monitoring function, it gives the ability to the clinician to schedule lists of activities for the patient to do during the day, allowing the clinician to have some control. We carried out a study with 10 healthy participants which used the monitorization system for 3 days each. The patient would worn the accelerometer and record the activities that they would do throughout the day, was asked a minimum of 5 activities per day. Alongside this recording it was schedule 1 list of activities to be carried out each day, this list only had motor activities such as walk, sit down, and stand up. At the end of each participant study, it was made a questionnaire with standard usability questions and an interview that helped us understand if the system was reliable or not

Nutritional management and recommendations for hospital users and medical inpatients

Dissertação de mestrado em Engenharia InformáticaNutrition is fundamental to human well-being and health, especially when applied to patients who need special health care. In these cases, it is crucial that each patient has adequate nutrition to meet their needs, in order to accelerate their recovery process. Recommender systems make it possible to offer suggestions to users, adapted to their preferences and to previously obtained information about them. Food recommender systems are recommender systems applied to nutrition and diet. They are usually implemented feeding plans recommendation platforms based on food and the person using it. In this sense, the existing gap in the use of these recommendation systems applied to nutrition in health care is notorious. This is mainly due to the difficulty in associating the nutritional value of each food with the needs of patients. The main objective of this project is to fill the existing void, through the development and implementation of a platform that will allow the planning of meals taking into account the nutritional plan of the food and the specific needs associated with the users of the Vila Verde Social Canteen. The use of machine learning algorithms will allow us to identify how the connection between food and patient requirements can be made, making this task possible, which is complex due to the wide domain associated with it. This platform will be used for the generation of kitchen meal plans, which shall be produced using the algorithms developed after a bibliographic study and an investigation of the existing work, in order to understand how they can be implemented and which are the most adequate to the nutritional recommendations system.A nutrição é fundamental no bem-estar e na saúde do ser humano, principalmente quando aplicada a pacientes que necessitam de cuidados de saúde especiais. Nestes casos, é fulcral que cada paciente tenha uma nutrição adequada às suas necessidades, de forma a acelerar o seu processo de recuperação. Os sistemas de recomendação permitem oferecer sugestões aos utilizadores, adequados às suas preferências e às informações previamente obtidas acerca dos mesmos. Os sis-temas de recomendação de alimentos são sistemas de recomendação aplicados à nutrição e alimentação. Estes são usualmente implementados em plataformas de recomendações de receitas e planos de alimentação tendo como base a comida e a pessoa. Neste sentido, é notória a falha atual no que diz respeito à utilização destes sistemas de recomendação aplicados à nutrição em cuidados de saúde. Isto deve-se maioritariamente à dificuldade na associação entre o valor nutricional de cada alimento e as necessidades dos pacientes. Este projeto tem como principal objetivo preencher a lacuna existente, através do desen-volvimento e implementação de uma plataforma que irá permitir o planeamento de refeições tendo em conta o plano nutricional dos alimentos e as necessidades específicas associadas aos utentes da Cantina Social de Vila Verde. A utilização de algoritmos de machine learning permitirá perceber como pode ser feita a conexão entre os alimentos e os requisitos dos pacientes, tornando possível esta tarefa, que é complexa devido ao largo domínio associado à mesma. Esta plataforma será utilizada para a geração de planos de refeições da cozinha, sendo estes produzidos utilizando os algoritmos desenvolvidos após um estudo bibliográfico e uma investigação ao trabalho existente com o objetivo de perceber como poderão ser implementados e quais os mais adequados ao sistema de recomendações nutricional

Manuel de Terán Alvarez (1904-1984).

Sin resume

Computing wildfire behaviour metrics from CFD simulation data

In this article, we demonstrate a new post-processing methodology which can be used to analyse CFD wildfire simulation outputs in a model-independent manner. CFD models produce a great deal of quantitative output but require additional post-processing to calculate commonly used wildfire behaviour metrics. Such post-processing has so far been model specific. Our method takes advantage of the 3D renderings that are a common output from such models and provides a means of calculating important fire metrics such as rate of spread and flame height using image processing techniques. This approach can be applied similarly to different models and to real world fire behaviour datasets, thus providing a new framework for model validation. Furthermore, obtained information is not limited to average values over the complete domain but spatially and temporally explicit metric distributions are provided. This feature supports posterior statistical analyses, ultimately contributing to more detailed and rigorous fire behaviour studies.Peer ReviewedPostprint (published version

Main specifications of CFD codes for WUIVIEW activities

CFD simulations will be the core activity of the WUVIEW performance based fire safety analysis. The purpose of this document is to provide WUIVIEW partners with a general overview of the CFD codes to be used in the Action. The general simulation framework is described, particularly highlighting data inputs and scenario description requirements, to be developed in subsequent WUIVIEW WPs. This TN provides the technical foundations and main specifications of the databases to be designed within the WUIVIEW working program (ongoing action by UPC).Postprint (updated version

Problemática socio-económica de la mano de obra en explotaciones radicadas en zonas marginales de la provincia de Córdoba

Se estudia la cifra de ventas por UTII en cuatro diferentes acllvidadcs que se realizan en las zonas marginales de la provincia de Córdoba, éstas son, cría de ovinos, caprinos, cotos de caza menor y cotos de cala mayor. Asimismo se considera el coste social de las actividades pastor, cabrero y g11arda

Performance analysis of a self-protection system for vehicles in case of WUI fire entrapment

Sheltering inside a civilian vehicle has proved to be a high risk strategy in case of wildfire entrapment. Survival is by no means guaranteed, especially in moderate to high-intensity wildfires. However, vehicles do offer a certain degree of fire protection, which can be reinforced by ad-hoc fire resistant technology. In this paper, we present the experimental performance analysis of a self-protection system that has been designed to protect people’s life in case of fire entrapment. Similar to a firefighter fire shelter, the designed system can be quickly deployed covering the whole vehicle. In case of fire exposure, this fabric provides additional heat protection to the occupants and the vehicle itself. An experimental burning was designed in order to simulate real fire exposure conditions in case of vehicle entrapment in a rural road. An ex-situ 2-m high fuel bed composed of Pinus halepensis fine logging slash was arranged in a 13 m long x 6 m wide area. Fire was ignited at one end of the fuel bed and spread driven by an induced constant air flow (3 m/s midflame wind speed). 2.8 m away from the other fuel bed end, a car covered with the fire protection fabric was placed, parallel to the fire. Data analysis provided mean values of fire rate of spread (2 m/s), fireline intensity (1800 kW/m), flame height (6.5 m), flame tilt angle (30º), flame depth (2 m), flame temperature (800 ºC) and flame emissive power (47.5 kW/m2 ). Maximum air temperatures inside the vehicle ranged around 41-42.5 ºC during a period between 20 min and 35 min after ignition. A thermocouple in contact with the internal side of the driver’s window registered a maximum value of 47.3 ºC. These results evidenced the good performance of the fabric when protecting eventual vehicle occupants against thermal exposure from wildfires of moderate intensity.Peer ReviewedPostprint (author's final draft