979 research outputs found

    A customizable game-inspired application for memory stimulation

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    Demographic changes are leading to a growing older population (>65 years), with repercussions on age-related conditions. From a Computer Science perspective, this also means that there will soon be a significant number of users with changes in perceptual and motor skill capacities. The goal of this work is to develop an environment to support the preservation of memory and functional capacities of the elderly. Health professionals will be able to set up and personalize immersive and realistic scenarios with high ecological validity composed of visual, auditory, and physical stimuli. Patients will navigate through and interact with these scenarios and stimulate memory functions by later recalling distinct aspects of the different exercises of the tool. The long-term goal is to build a behavioral model of how older users interact with technology.- (undefined

    Musiquence – Design, Implementation and Validation of a Customizable Music and Reminiscence Cognitive Stimulation Platform for People with Dementia

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    Dementia is a neurodegenerative disease that affects millions of individuals worldwide and is challenging to diagnose as symptoms may only perceivable decades later. The disease leads to a gradual loss of memory, learning, orientation, language, and comprehension skills, which compromises activities of daily living. Health-related costs caused by dementia will continue to increase over the next few years; between the years 2005 and 2009, an increase of 34% (from 315to315 to 422 billion worldwide) was observed in treating dementia-related issues. Pharmaceutical approaches have been developed to treat dementia symptoms; unfortunately, the risk of side effects is high. For this reason, nonpharmaceutical methods such as music and reminiscence therapies have gained acceptance as patients with dementia positively respond to such approaches even at later stages of the disease. Nevertheless, further research is needed to understand how music and reminiscence therapy should be used and to quantify their impact on individuals with dementia. The development of serious games has gained attention as an alternative approach to stimulate patients. However, the clinical impact that serious games have on individuals with dementia is still unclear. In this dissertation, we contribute with new knowledge regarding the usage of music and reminiscence approaches in people with dementia through a theoretical model. Based on Baddeley’s working memory model, our model aims to explain how the therapeutic properties of music and reminiscence can have a beneficial effect. To test our model, we developed a novel interactive platform called Musiquence, in which healthcare professionals can create music and reminiscence based cognitive activities to stimulate people with dementia. In this dissertation, we present the results from several studies about the usage and effects that music and reminiscence have on such a population. We performed two studies using Musiquence to study the feasibility of a novel learning method based on musical feedback to aid people with dementia during task performance in virtual reality settings. Results show that participants relied more on music-based feedback during the task performance of virtual reality activities than in other forms of feedback. Also, data suggest that the music-based feedback system can improve task performance, compensating for some dementia-related deficits. We also used Musiquence in a longitudinal one-month-long pilot study to assess its efficacy when used for a cognitive stimulation intervention in dementia patients. The results of the study are promising. The 3 participants showed improvements in terms of general cognition, quality of life, mood, and verbal fluency

    A new motion-based tool for occupation and monitoring of residents in nursing homes

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    Population ageing bring new challenges in healthcare and has raised issues concerning innovative solutions to optimize the management of elderly. As recommended, new interactive tools must be accessible to users, acceptable, easy to use, motivating and useful for both residents and staff. Virtual Reality is a good candidate to fulfill these specifications. Based on our expertise in Human Computer Interaction and Neuropsychology of ageing, we are developing a platform to offer interactive activities adapted to very-old and dependent people living in nursing homes. It is based on the use of a low-cost markerless RGB-D sensor (AstraTM, Orbbec) to track user body motion. Implemented activities were designed to involve various cognitive abilities, such as sorting game, search game, ball game. In addition, a module records several biomechanical data and generates reports for caregivers. This paper aims to discuss the special needs of research context and to present the designed interaction platform

    Digital fabrication of custom interactive objects with rich materials

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    As ubiquitous computing is becoming reality, people interact with an increasing number of computer interfaces embedded in physical objects. Today, interaction with those objects largely relies on integrated touchscreens. In contrast, humans are capable of rich interaction with physical objects and their materials through sensory feedback and dexterous manipulation skills. However, developing physical user interfaces that offer versatile interaction and leverage these capabilities is challenging. It requires novel technologies for prototyping interfaces with custom interactivity that support rich materials of everyday objects. Moreover, such technologies need to be accessible to empower a wide audience of researchers, makers, and users. This thesis investigates digital fabrication as a key technology to address these challenges. It contributes four novel design and fabrication approaches for interactive objects with rich materials. The contributions enable easy, accessible, and versatile design and fabrication of interactive objects with custom stretchability, input and output on complex geometries and diverse materials, tactile output on 3D-object geometries, and capabilities of changing their shape and material properties. Together, the contributions of this thesis advance the fields of digital fabrication, rapid prototyping, and ubiquitous computing towards the bigger goal of exploring interactive objects with rich materials as a new generation of physical interfaces.Computer werden zunehmend in Geräten integriert, mit welchen Menschen im Alltag interagieren. Heutzutage basiert diese Interaktion weitgehend auf Touchscreens. Im Kontrast dazu steht die reichhaltige Interaktion mit physischen Objekten und Materialien durch sensorisches Feedback und geschickte Manipulation. Interfaces zu entwerfen, die diese Fähigkeiten nutzen, ist allerdings problematisch. Hierfür sind Technologien zum Prototyping neuer Interfaces mit benutzerdefinierter Interaktivität und Kompatibilität mit vielfältigen Materialien erforderlich. Zudem sollten solche Technologien zugänglich sein, um ein breites Publikum zu erreichen. Diese Dissertation erforscht die digitale Fabrikation als Schlüsseltechnologie, um diese Probleme zu adressieren. Sie trägt vier neue Design- und Fabrikationsansätze für das Prototyping interaktiver Objekte mit reichhaltigen Materialien bei. Diese ermöglichen einfaches, zugängliches und vielseitiges Design und Fabrikation von interaktiven Objekten mit individueller Dehnbarkeit, Ein- und Ausgabe auf komplexen Geometrien und vielfältigen Materialien, taktiler Ausgabe auf 3D-Objektgeometrien und der Fähigkeit ihre Form und Materialeigenschaften zu ändern. Insgesamt trägt diese Dissertation zum Fortschritt der Bereiche der digitalen Fabrikation, des Rapid Prototyping und des Ubiquitous Computing in Richtung des größeren Ziels, der Exploration interaktiver Objekte mit reichhaltigen Materialien als eine neue Generation von physischen Interfaces, bei

    Robotic ubiquitous cognitive ecology for smart homes

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    Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

    Designing interactive virtual environments with feedback in health applications.

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    One of the most important factors to influence user experience in human-computer interaction is the user emotional reaction. Interactive environments including serious games that are responsive to user emotions improve their effectiveness and user satisfactions. Testing and training for user emotional competence is meaningful in healthcare field, which has motivated us to analyze immersive affective games using emotional feedbacks. In this dissertation, a systematic model of designing interactive environment is presented, which consists of three essential modules: affect modeling, affect recognition, and affect control. In order to collect data for analysis and construct these modules, a series of experiments were conducted using virtual reality (VR) to evoke user emotional reactions and monitoring the reactions by physiological data. The analysis results lead to the novel approach of a framework to design affective gaming in virtual reality, including the descriptions on the aspects of interaction mechanism, graph-based structure, and user modeling. Oculus Rift was used in the experiments to provide immersive virtual reality with affective scenarios, and a sample application was implemented as cross-platform VR physical training serious game for elderly people to demonstrate the essential parts of the framework. The measurements of playability and effectiveness are discussed. The introduced framework should be used as a guiding principle for designing affective VR serious games. Possible healthcare applications include emotion competence training, educational softwares, as well as therapy methods

    Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

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    Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

    CGAMES'2009

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    Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

    Get PDF
    Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications
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