On the analysis of EEG power, frequency and asymmetry in Parkinson's disease during emotion processing

Objective: While Parkinson’s disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing. Method: EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli. Results: Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli. Conclusion: These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients

A Framework for Students Profile Detection

Some of the biggest problems tackling Higher Education Institutions are students’ drop-out and academic disengagement. Physical or psychological disabilities, social-economic or academic marginalization, and emotional and affective problems, are some of the factors that can lead to it. This problematic is worsened by the shortage of educational resources, that can bridge the communication gap between the faculty staff and the affective needs of these students. This dissertation focus in the development of a framework, capable of collecting analytic data, from an array of emotions, affects and behaviours, acquired either by human observations, like a teacher in a classroom or a psychologist, or by electronic sensors and automatic analysis software, such as eye tracking devices, emotion detection through facial expression recognition software, automatic gait and posture detection, and others. The framework establishes the guidance to compile the gathered data in an ontology, to enable the extraction of patterns outliers via machine learning, which assist the profiling of students in critical situations, like disengagement, attention deficit, drop-out, and other sociological issues. Consequently, it is possible to set real-time alerts when these profiles conditions are detected, so that appropriate experts could verify the situation and employ effective procedures. The goal is that, by providing insightful real-time cognitive data and facilitating the profiling of the students’ problems, a faster personalized response to help the student is enabled, allowing academic performance improvements

Efeito na variabilidade da frequência cardíaca e no humor do trabalhador durante jogo de educação

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Filosofia e Ciências Humanas, Programa de Pós-Graduação em Psicologia, Florianópolis, 2014.O objetivo desta pesquisa foi verificar o efeito que as alterações no estado de humor e na variabilidade da frequência cardíaca (VFC) exercem sobre o desempenho do trabalhador num jogo de educação profissional. Participaram da pesquisa 35 trabalhadores de indústria que responderam antes e após a prática do jogo educativo a escala de humor de Brunel. Enquanto jogavam eram monitorados fisiologicamente com um frequencímetro cardíaco. Os resultados demonstraram que o desempenho dos trabalhadores não foi influenciado por categorias como faixa etária, escolaridade e tempo de indústria, sendo sensível apenas ao sexo. Percebeu-se melhora significativa em 5 dos 6 indicadores de humor quando comparados os momentos pré e pós jogo. O humor pré-jogo apresentou poucas e moderadas correlações com o desempenho dos sujeitos, o indicador tensão apresentou a maior delas (r= -0,36). A VFC foi sensível às diferentes tarefas do jogo eletrônico, indicando que a passagem da tarefa de animação para a leitura proporcionou aumento da estimulação simpática e parassimpática, enquanto a passagem da tarefa de leitura para a de mini-game produziu aumento na estimulação parassimpática. Poucas e moderadas correlações foram encontradas entre os indicadores de VFC e desempenho, para os homens o indicador LF durante a linha de base apresentou correlação de 0,51, enquanto para as mulheres o indicador D2 durante a linha de base apresentou correlação de 0,68. Chegou-se à conclusão de que o jogo foi desenhado de uma forma a respeitar diferenças de contextos, permitindo que diferentes categorias de indivíduos atingissem desempenhos similares. Constatou-se também que o jogo obteve sucesso em melhorar o humor dos participantes, diminuindo tensão e fadiga. Por fim, observou-se que as alterações no estado de humor e VFC apresentaram correlações moderadas com o desempenho dos mesmos, e sugere-se que a monitoração com feedbacks em tempo real possa no futuro aumentar o desempenho dos trabalhadores.Abstract : The objective of this research was to determine the effect that changes in mood and heart rate variability (HRV) have on a worker?s performance during a professional educational game. The study was conducted with 35 industrial workers who answered the Brunel?s mood scale before and after participating on the educational game. While playing, they were physiologically monitored with a heart rate monitor. The results showed that the workers performance was not influenced by categories such as age, education and industrial work period, being only sensitive to gender. Significant improvement in 5 of the 6 indicators of humor was noticed, when pre and post game moments were compared. The pre-game mood showed few and moderate correlations with the subjects' performance; the tension indicator showed the largest one (r = -0.36). HRV was sensitive to the different tasks of the electronic game, indicating that the transition from animation to the task of reading led to an increase in sympathetic and parasympathetic stimulation, while the transition of the reading assignment to the mini-game generated an increase in parasympathetic stimulation. Few and moderate correlations were noticed between HRV and performance indicators, for men the LF indicator during baseline correlated in 0.51, while for women the D2 indicator during baseline correlated in 0.68 . The research concluded that the game was designed in a way to respect differences of contexts, enabling different categories of individuals to reach similar performance. It was also found that the game was successful in improving participants' mood, reducing stress and fatigue. Finally, changes in mood and HRV showed moderate correlations with their performance, and it is suggested that monitoring and giving real-time feedback in the future might workers performance

Proposta de uso de estado emocional do indivíduo na automação de ambiente inteligente

A questão de pesquisa que este estudo pretende abordar visa melhorar a qualidade de vida dos usuários, especialmente os portadores de necessidades especiais, adaptando o ambiente ao seu conforto emocional. Nesse contexto, o objetivo da presente pesquisa é a elaboração de um ambiente inteligente controlado passivamente através do estado emocional do usuário, utilizando interface cérebro computador. De forma geral, espera-se com este estudo ser capaz de adaptar um sistema inteligente de acordo com a emoção objetivo, visando o aumentando do rendimento do indivíduo numa dada tarefa, auxiliando em tratamentos terapêuticos ou aumentando o seu conforto. Para validação do trabalho foi utilizada a interface cérebrocomputador da empresa Emotiv com o sistema de automação predial-residencial da empresa Home Systems, utilizando algoritmo genético para buscar a configuração adequada do ambiente tendo o nível de atenção como emoção objetivo. Os resultados preliminares dos nove testes realizados com seis indivíduos comprovam que é viável o controle de ambientes baseado no estado emocional dos usuários. Este trabalho situa-se na interdisciplinaridade de áreas como engenharia elétrica, computação, psicologia comportamental e tecnologias assistivas.The research question that this study aims to approach is to improve the quality of life of individuals with or without special needs, by adapting the environment to their emotional comfort. In this context, the goal of this research is to develop an intelligent system passively controlled trough brain-computer interface. In general, it is expected with this study to be able to adapt a smart environment according to the emotional target, aiming to increase the yield of a given individual task, assisting in therapeutics or increasing the individual’s comfort. In order to validate the experiment, Emotiv’s brain computer interface was used with Home Systems’ home automation system, using genetic algorithm to find the appropriate configuration of the environment and attention level as the emotional target. Preliminary results of the nine tests conducted on six subjects indicate that it is feasible to control a smart environment based on the emotional state of the user. This is an interdisciplinary work in areas such as electrical engineering, computer science, behavioral psychology and assistive technologies

Enhancing electronic intelligent tutoring systems by responding to affective states

The overall aim of this research is the exploration mechanisms which allow an understanding of the emotional state of students and the selection of an appropriate cognitive and affective feedback for students on the basis of students' emotional state and cognitive state in an affective learning environment. The learning environment in which this research is based is one in which students learn by watching an instructional video. The main contributions in the thesis include: - A video study was carried out to gather data in order to construct the emotional models in this research. This video study adopted a methodology in qualitative research called “Quick and Dirty Ethnography”(Hughes et al., 1995). In the video study, the emotional states, including boredom, frustration, confusion, flow, happiness, interest, were identified as being the most important to a learner in learning. The results of the video study indicates that blink frequencies can reflect the learner's emotional states and it is necessary to intervene when students are in self-learning through watching an instructional video in order to ensure that attention levels do not decrease. - A novel emotional analysis model for modeling student’s cognitive and emotional state in an affective learning system was constructed. It is an appraisal model which is on the basis of an instructional theory called Gagne’s theory (Gagne, 1965). - A novel emotion feedback model for producing appropriate feedback tactics in affective learning system was developed by Ontology and Influence Diagram ii approach. On the basis of the tutor-remediation hypothesis and the self-remediation hypothesis (Hausmann et al., 2013), two feedback tactic selection algorithms were designed and implemented. The evaluation results show: the emotion analysis model can be used to classify negative emotion and hence deduce the learner’s cognitive state; the degree of satisfaction with the feedback based on the tutor-remediation hypothesis is higher than the feedback based on self-remediation hypothesis; the results indicated a higher degree of satisfaction with the combined cognitive and emotional feedback than cognitive feedback on its own

Innovación disruptiva para la educación superior. Implementación en América Latina

La cuarta revolución industrial plantea cambios y transformaciones en todos los ámbitos de la sociedad y la educación no es la excepción; problemáticas tradicionales que enfrenta la educación superior como la deserción, el comportamiento y la diversidad estudiantil, son analizadas desde enfoques fisiológicos y emocionales, ante ello, se plantean diversas iniciativas de soluciones con base en tecnologías disruptivas como la Inteligencia Artificial, la computación afectiva y la web semántica denominadas en el libro como estudios de casos donde se describen las innovaciones con tecnologías disruptivas. Finalmente, y ante la gran interrogante y preocupación de académicos y científicos; por el desarrollo de la robótica, las inteligencias artificiales y de software en general se abordan las cuestiones y el impacto ético