Emotive computing may have a role in telecare

This brief paper sets out arguments for the introduction of new technologies into telecare and lifestyle monitoring that can detect and monitor the emotive state of patients. The significantly increased use of computers by older people will enable the elements of emotive computing to be integrated with features such as keyboards and webcams, to provide additional information on emotional state. When this is combined with other data, there will be significant opportunities for system enhancement and the identification of changes in user status, and hence of need. The ubiquity of home computing makes the keyboard a very attractive, economic and non-intrusive means of data collection and analysis

Linking recorded data with emotive and adaptive computing in an eHealth environment

Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development

Computer apology: The effect of the apologetic feedback on users in computerized environment

Apologizing or praising has various effects on people's motivation levels. One way to employ emotions in computerized environments is to present humanized messages like apologetic statements. In this study, a game offering apologetic statements for a group of subjects was used to understand the effect of apologetic statements in computerized environment. Findings have shown that the apologetic feedbacks made the subjects feel more respected, more comfortable, and more sensitive to their feelings. These findings confirm the legitimacy of the claim that computers' offering apologetic statements to the users can realize the real user-centered design

Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation

Craft histories, textile futures: the emotional affectivity of a ‘future quilt’…

When Bart Simpson’s dog shredded up the Bouvier family quilt, his mother Marge (née Bouvier) was more than upset. “Six generations, ruined!” she screamed… That old quilt covered ‘historyground’, so why Marge’s trauma

Moods and Their Relevance to Systems Usage Models within Organizations: An Extended Framework

Traditionally, information systems (IS) usage models have examined user behavior within a cognitive framework, that is, these models suggest that a user’s cognition influences his/her IS usage behavior. Research over the past three decades has shown that mood, one’s global feeling state at a given time, can significantly impact a person’s cognitive processes. Mood effects on cognition are particularly relevant to organizational settings. Because moods are pervasive, they provide a stable context for cognitive processes that influence behavior at work; therefore, the inclusion of mood in individual IS usage models that support organizational tasks is both relevant and necessary. Because positive mood can enhance performance under certain circumstances, mood management is also relevant to IS usage models. Thus, we highlight how moods can be managed via IS and propose a model that takes into account users’ moods at the time they work with a system. This model provides an extended framework for incorporating relevant mood literature into current IS usage behavioral models. With this model, researchers can examine certain aspects of the model (such as how IS design can influence user feeling states or how users’ moods can impact their behavior), or conduct more comprehensive research using the entire model. This model can contribute to theory by providing a more complete picture of user behavior, and contribute to practice by helping mangers plan for desired outcomes

Computing emotion awareness through galvanic skin response and facial electromyography

To improve human-computer interaction (HCI), computers need to recognize and respond properly to their user’s emotional state. This is a fundamental application of affective computing, which relates to, arises from, or deliberately influences emotion. As a first step to a system that recognizes emotions of individual users, this research focuses on how emotional experiences are expressed in six parameters (i.e., mean, absolute deviation, standard deviation, variance, skewness, and kurtosis) of not baseline-corrected physiological measurements of the galvanic skin response (GSR) and of three electromyography signals: frontalis (EMG1), corrugator supercilii (EMG2), and zygomaticus major (EMG3). The 24 participants were asked to watch film scenes of 120 seconds, which they rated afterward. These ratings enabled us to distinguish four categories of emotions: negative, positive, mixed, and neutral. The skewness and kurtosis of the GSR, the skewness of the EMG2, and four parameters of EMG3, discriminate between the four emotion categories. This, despite the coarse time windows that were used. Moreover, rapid processing of the signals proved to be possible. This enables tailored HCI facilitated by an emotional awareness of systems

Evaluation of Etiquette Strategies to Adapt Feedback In Affect-Aware Tutoring

The purpose of this research is to investigate how to mitigate user frustration and improve task performancein the context of human-computer interaction (HCI). Even though user frustration plays a role in manyaspects of HCI and studies have looked into the consequences of frustration in various fields, the ways tomitigate frustration are less deeply examined. Once the system has the ability to understand and includeuser emotions as factors in HCI, the interaction between the user and the computer system could be adaptedif the computers are able to modify its behavior with users in appropriate ways to further joint performance.Specifically, a preliminary study was conducted to explore the task performance, motivation, andconfidence implications of changing the interaction between the human and the computer via differentetiquette strategies. Participants solved a total of twenty mathematics problems under different frustrationcondition with feedback given in different styles of etiquette. Changing etiquette strategies in tutoring ledto changes in performance, motivation, and confidence. The most effective etiquette strategies changedwhen users were frustrated. This work provides the foundation for the design of adaptive intelligenttutoring system based on etiquette strategies.Copyright Human Factors and Ergonomics Society 2016. Posted with permission.</div