Abstract
Human observation and memory are not reliable enough to provide accurate and objective information from athletes in high-performance environments. In this context analysis tools constitute an important instrument for professional coaches, as they provide information on player's behavior statistically compiled. Most of the tools presented for the soccer universe, offer non-real time information and, with the hardware devices being quite costly. In many cases these systems (specially camera based solutions) also present some technical issues mainly in what concerns occlusion and computational demands. This research work presents a real time soccer analysis system based on a Wi-Fi location approach that can be used by a soccer coach in a training session or even a match. Using a Wi-Fi network, inexpensive tags and a positioning engine on top of it, this portable system provides a visualization tool for such data on a real time basis. The results are quite satisfactory, because this system was able to track the players during a training exercise and display this data on a real time bases and it was also able to provide information on players' movements and their interaction all over the exercise.

Abstract
Both the academic and industrial worlds have increased investment and dedication to the affective computing area in the past years. At the same time, immersive environments have become more and more a reliable domain, with progressively cheaper hardware and software solutions. With this in mind, the authors used biometric readings to perform real-time user emotion assessment in an immersive environment. In the example used in this paper, the environment consisted in a flight simulation, and biometric readings were based on galvanic skin response, respiration rate and amplitude, and phalanx temperature. The detected user emotional states were also used to modify some simulation variables, such as flight plan, weather and maneuver smoothness. The emotion assessment results were consistent with user-described emotions, achieving an overall success rate of 78%.

Abstract
Affective computing and multichannel multimedia distribution have gathered the time and investment of industry and academics. The proposed system merges such domains so that ubiquitous system can be enhanced through online user emotion assessment based on user's biosignals. It was used IAPS as a emotional library for controlled visual stimuli and biosignals were collected in real-time - heartbeat rate and skin conductance - in order to online assess the user's emotional state through Russell's Circumplex Model of Affect. In order to improve usability and session setup, a distributed architecture was used so that software models might be physically detached. The conducted experimental sessions and the validation interviews supported the system's efficiency not only in real-time discrete emotional state assessment but also considering the emotion inducing process. The next logic step consists in replicating the achieved success in multi-format multimedia contents without the need of pre-defined restricted emotional metadata.

Abstract
Recently topics such as affective computing and multichannel multimedia distribution have gained the attention and investment of both industry and academics. The proposed system joins these domains so that ubiquitous system can be potentiated by means of online user emotion assessment based on real-time user's biosignals. It was used IAPS as a emotional library for controlled visual stimuli and biosignals were collected in real-time - heartbeat rate and skin conductance - in order to online assess the user's emotional state through Russell's Circumplex Model of Affect. To improve usability and session setup, a distributed architecture was used so that software models might be physically detached. The conducted experimental sessions and the validation interviews supported the system's efficiency not only in real-time discrete emotional state assessment but also considering the emotion inducing process. The future work consists in replicating the success in multi-format multimedia contents without pre-defined emotional metadata.

Abstract
Emotion's definition, identification, systematic induction and efficient and reliable classification have been themes to which several complementary knowledge areas such as psychology, medicine and computer science have been dedicating serious investments. This project consists in developing an automatic tool for emotion assessment based on a dynamic biometric data acquisition set as galvanic skin response and electroencephalography arc practical examples. The output of standard emotional induction methods is the support for classification based on data analysis and processing. The conducted experimental sessions, alongside with the developed support tools, allowed the extraction on conclusions such as the capability of effectively performing automatic classification of the subject's predominant emotional state. Self assessment interviews validated the developed tool's success rate of approximately 75%. It was also experimentally strongly suggested that female subjects are emotionally more active and easily induced than mates.

Abstract
The identification and assessment of human being emotional states belongs to one of the primordial objectives of the scientific research in disparate areas such as artificial intelligence, medicine or psychology. The main objective of this project is related to automatic assessment of a subject's basic emotional states by using electroencephalography as a source for biometric data acquisition. This evaluation is based on predefined mechanisms of emotional induction, as well as specific methods and tools capable of data analysis and processing. From the experimental results attained in several experimental sessions and through the support tools developed, the most pertinent conclusion extracted from this work refers to the capability of effectively performing automatic classification of the subject's predominant emotional state. The emotional conditions were induced through the presentation of specific visual multimedia contents. The success rate of this tool, compared against the self assessment interviews carried out immediately after the experimental session, was approximately 75%. It was also experimentally concluded that female subjects are emotionally more demonstrative than the male ones.