10,511 research outputs found

    A Toolkit for Exploring Affective Interface Adaptation in Videogames

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    From its humble beginnings back in the early 1960’s the videogame has become one of the most successful form of HCI to date. However if we look more closely at the interactions between the game and gamer it becomes evident little has changed since the advent of SpaceWar back in 1961. These interactions are for the most part static and thus predictable, given a particular set of circumstances a game will always react in one particular manner despite anything the player may actually do. Because of this the expected lifespan of a videogame is inherently dependant on the choices the videogame provides; once all possible avenues have been explored the game loses its appeal. In this paper we focus on adapting techniques used in the field of Affective Computing to solve this stagnation in the videogames market. We describe the development of a software development kit (SDK) that allows the interactions between man and machine to become dynamic entities during play by means of monitoring the player’s physiological condition

    Neurophysiological Assessment of Affective Experience

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    In the field of Affective Computing the affective experience (AX) of the user during the interaction with computers is of great interest. The automatic recognition of the affective state, or emotion, of the user is one of the big challenges. In this proposal I focus on the affect recognition via physiological and neurophysiological signals. Long‐standing evidence from psychophysiological research and more recently from research in affective neuroscience suggests that both, body and brain physiology, are able to indicate the current affective state of a subject. However, regarding the classification of AX several questions are still unanswered. The principal possibility of AX classification was repeatedly shown, but its generalisation over different task contexts, elicitating stimuli modalities, subjects or time is seldom addressed. In this proposal I will discuss a possible agenda for the further exploration of physiological and neurophysiological correlates of AX over different elicitation modalities and task contexts

    Exploring the Affective Loop

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    Research in psychology and neurology shows that both body and mind are involved when experiencing emotions (Damasio 1994, Davidson et al. 2003). People are also very physical when they try to communicate their emotions. Somewhere in between beings consciously and unconsciously aware of it ourselves, we produce both verbal and physical signs to make other people understand how we feel. Simultaneously, this production of signs involves us in a stronger personal experience of the emotions we express. Emotions are also communicated in the digital world, but there is little focus on users' personal as well as physical experience of emotions in the available digital media. In order to explore whether and how we can expand existing media, we have designed, implemented and evaluated /eMoto/, a mobile service for sending affective messages to others. With eMoto, we explicitly aim to address both cognitive and physical experiences of human emotions. Through combining affective gestures for input with affective expressions that make use of colors, shapes and animations for the background of messages, the interaction "pulls" the user into an /affective loop/. In this thesis we define what we mean by affective loop and present a user-centered design approach expressed through four design principles inspired by previous work within Human Computer Interaction (HCI) but adjusted to our purposes; /embodiment/ (Dourish 2001) as a means to address how people communicate emotions in real life, /flow/ (Csikszentmihalyi 1990) to reach a state of involvement that goes further than the current context, /ambiguity/ of the designed expressions (Gaver et al. 2003) to allow for open-ended interpretation by the end-users instead of simplistic, one-emotion one-expression pairs and /natural but designed expressions/ to address people's natural couplings between cognitively and physically experienced emotions. We also present results from an end-user study of eMoto that indicates that subjects got both physically and emotionally involved in the interaction and that the designed "openness" and ambiguity of the expressions, was appreciated and understood by our subjects. Through the user study, we identified four potential design problems that have to be tackled in order to achieve an affective loop effect; the extent to which users' /feel in control/ of the interaction, /harmony and coherence/ between cognitive and physical expressions/,/ /timing/ of expressions and feedback in a communicational setting, and effects of users' /personality/ on their emotional expressions and experiences of the interaction

    Assessing the impact of affective feedback on end-user security awareness

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    A lack of awareness regarding online security behaviour can leave users and their devices vulnerable to compromise. This paper highlights potential areas where users may fall victim to online attacks, and reviews existing tools developed to raise users’ awareness of security behaviour. An ongoing research project is described, which provides a combined monitoring solution and affective feedback system, designed to provide affective feedback on automatic detection of risky security behaviour within a web browser. Results gained from the research conclude an affective feedback mechanism in a browser-based environment, can promote general awareness of online security

    Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

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    Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial
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