201 research outputs found

    Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

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    In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices

    A review and framework for designing interactive technologies for emotion regulation training

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    Emotion regulation is foundational to mental health and well-being. In the last ten years there has been an increasing focus on the use of interactive technologies to support emotion regulation training in a variety of contexts. However, research has been done in diverse fields, and no cohesive framework exists that explicates what features of such system are important to consider, guidance on how to design these features, and what remains unknown, which should be explored in future design research. To address this gap, this thesis presents the results of a descriptive review of 54 peer-reviewed papers. Through qualitative and frequency analysis I analyzed previous technologies, reviewed their theoretical foundations, the opportunities where they appear to provide unique benefits, and their conceptual and usability challenges. Based on the findings I synthesized a design framework that presents the main concepts and design considerations that researchers and designers may find useful in designing future technologies in the context of emotion regulation training

    Odhad emocí a duševní koncentrace pomocí technik Deep Learningu

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    The purpose of this work is to evaluate the brain waves of humans with deep learn- ing methods and evolutionary computation techniques, and to verify the performance of applied techniques. In this thesis, we apply well–known metaheuristics and Artificial Neural Networks for classifying human mental activities using electroencephalographic signals. We developed a Brain–Computer Interface system that is able to process elec- troencephalographic signals and classify mental concentration versus relaxation. The system is able to automatically extract and learn representation of the given data. Based on scientific protocols we designed the Brain–Computer Interface experiments and we created an original and relevant data for the industrial and academic community. Our experimental data is available to the scientific community. In the experiments we used an electroencephalographic based device for collecting brain information form the subjects during specific activities. The collected data represents brain waves of subjects who was stimulated by writing tasks. Furthermore, we selected the best combination of the input features (brain waves information) using the following two metaheuristic techniques: Simulated Annealing and Geometric Particle Swarm Optimization. We applied a specific type of Artificial Neural Network, named Echo State Network, for solving the mapping between brain information and subject activities. The results indicate that it is possible to estimate the human con- centration using few electroencephalographic signals. In addition, the proposed system is developed with a fast and robust learning technique that can be easily adapted accord- ing to each subject. Moreover, this approach does not require powerful computational resources. As a consequence, the proposed system can be used in environments which are computationally limited and/or where the computational time is an important issue.Cílem práce je ohodnocení lidských mozkových vln s využitím metod hlubokého učení (deep learning) a evolučních výpočetních technik a pro ověření výkonu aplikovaných technik. V diplomové práci jsou využity dobře známé metaheuristiky a umělé neuronové sítě pro klasifikaci lidských mentálních aktivit za použití elektroencefalografických signálů. Bylo vyvinuto rozhraní mozek-počítač, které je schopno zpracovat elektroencefalografické signály a klasifikovat mentální soustředění v porovnání s relaxací. Systém je schopen automaticky extrahovat a naučit se reprezentaci daných dat. Na základě vědeckých protokolů byl navržen experiment pro rozhraní mozek-počítač a byla vytvořena původní a relevantní data pro průmyslovou a akademickou komunitu. Vygenerovaná pokusná data jsou přístupné pro vědeckou komunitu. V rámci experimentů bylo využito zařízení založené na encefalografii pro sběr mozkových signálů subjektu během specifických aktivit. Nasbíraná data reprezentují mozkové vlny subjektu, který byl stimulován psaním úloh. Dále byla vybrána nejlepší kombinace vstupních vlastností (informace o mozkové vlně) s využitím následujících dvou metaheuristických metod: simulovaného žíhání a geometrické optimalizace hejnem částic. Umělá neuronová síť, která se nazývá Echo State síť, byla aplikována pro řešení mapování mezi informacemi z mozku a aktivitami subjektu. Výsledky ukazují, že je možné odhadnout lidskou aktivitu pomocí několika encefalografických signálů. Kromě toho, navrhovaný systém je vyvinut s využitím rychlých a robustních učících technik, které mohou být jednoduše přizpůsobeny podle jednotlivých subjektů. Tento přístup navíc nevyžaduje výkonné výpočetní prostředky. V důsledku toho může být systém využit v prostředí, které jsou výpočetně omezeny a/nebo v případech, kdy výpočetní čas je důležitým hlediskem.460 - Katedra informatikyvýborn

    Investigando Natural User Interfaces (NUIs) : tecnologias e interação em contexto de acessibilidade

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    Orientador: Maria Cecília Calani BaranauskasTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Natural User Interfaces (NUIs) representam um novo paradigma de interação, com a promessa de ser mais intuitivo e fácil de usar do que seu antecessor, que utiliza mouse e teclado. Em um contexto no qual as tecnologias estão cada vez mais invisíveis e pervasivas, não só a quantidade mas também a diversidade de pessoas que participam deste contexto é crescente. Nesse caso, é preciso estudar como esse novo paradigma de interação de fato consegue ser acessível a todas as pessoas que podem utilizá-lo no dia-a-dia. Ademais, é preciso também caracterizar o paradigma em si, para entender o que o torna, de fato, natural. Portanto, nesta tese apresentamos o caminho que percorremos em busca dessas duas respostas: como caracterizar NUIs, no atual contexto tecnológico, e como tornar NUIs acessíveis para todos. Para tanto, primeiro apresentamos uma revisão sistemática de literatura com o estado da arte. Depois, mostramos um conjunto de heurísticas para o design e a avaliação de NUIs, que foram aplicadas em estudos de caso práticos. Em seguida, estruturamos as ideias desta pesquisa dentro dos artefatos da Semiótica Organizacional, e obtivemos esclarecimentos sobre como fazer o design de NUIs com Acessibilidade, seja por meio de Design Universal, seja para propor Tecnologias Assistivas. Depois, apresentamos três estudos de caso com sistemas NUI cujo design foi feito por nós. A partir desses estudos de caso, expandimos nosso referencial teórico e conseguimos, por fim, encontrar três elementos que resumem a nossa caracterização de NUI: diferenças, affordances e enaçãoAbstract: Natural User Interfaces (NUIs) represent a new interaction paradigm, with the promise of being more intuitive and easy to use than its predecessor, that utilizes mouse and keyboard. In a context where technology is becoming each time more invisible and pervasive, not only the amount but also the diversity of people who participate in this context is increasing. In this case, it must be studied how this new interaction paradigm can, in fact, be accessible to all the people who may use it on their daily routine. Furthermore, it is also necessary to characterize the paradigm itself, to understand what makes it, in fact, natural. Therefore, in this thesis we present the path we took in search of these two answers: how to characterize NUIs in the current technological context, and how to make NUIs accessible to all. To do so, first we present a systematic literature review with the state of the art. Then, we show a set of heuristics for the design and evaluation of NUIs, which were applied in practical study cases. Afterwards, we structure the ideas of this research into the Organizational Semiotics artifacts, and we obtain insights into how to design NUIs with Accessibility, be it through Universal Design, be it to propose Assistive Technologies. Then, we present three case studies with NUI systems which we designed. From these case studies, we expanded our theoretical references were able to, finally, find three elements that sum up our characterization of NUI: differences, affordances and enactionDoutoradoCiência da ComputaçãoDoutora em Ciência da Computação160911/2015-0CAPESCNP

    Practical, appropriate, empirically-validated guidelines for designing educational games

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    There has recently been a great deal of interest in the potential of computer games to function as innovative educational tools. However, there is very little evidence of games fulfilling that potential. Indeed, the process of merging the disparate goals of education and games design appears problematic, and there are currently no practical guidelines for how to do so in a coherent manner. In this paper, we describe the successful, empirically validated teaching methods developed by behavioural psychologists and point out how they are uniquely suited to take advantage of the benefits that games offer to education. We conclude by proposing some practical steps for designing educational games, based on the techniques of Applied Behaviour Analysis. It is intended that this paper can both focus educational games designers on the features of games that are genuinely useful for education, and also introduce a successful form of teaching that this audience may not yet be familiar with

    Brain Computer Interface on Track to Home.

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    The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users' home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life
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