Using affective avatars and rich multimedia content for education of children with autism

Autism is a communication disorder that mandates early and continuous educational interventions on various levels like the everyday social, communication and reasoning skills. Computer-aided education has recently been considered as a likely intervention method for such cases, and therefore different systems have been proposed and developed worldwide. In more recent years, affective computing applications for the aforementioned interventions have also been proposed to shed light on this problem. In this paper, we examine the technological and educational needs of affective interventions for autistic persons. Enabling affective technologies are visited and a number of possible exploitation scenarios are illustrated. Emphasis is placed in covering the continuous and long term needs of autistic persons by unobtrusive and ubiquitous technologies with the engagement of an affective speaking avatar. A personalised prototype system facilitating these scenarios is described. In addition the feedback from educators for autistic persons is provided for the system in terms of its usefulness, efficiency and the envisaged reaction of the autistic persons, collected by means of an anonymous questionnaire. Results illustrate the clear potential of this effort in facilitating a very promising autism intervention

Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Personalising the user experience of a mobile health application towards Patient Engagement

Stuttering is a multifactorial speech disorder that usually has several impacts on daily life, especially regarding loss of confidence in social situations and increased anxiety levels. BroiStu is a mobile health application that was developed to address the impacts of stuttering on people who stutter, allowing them to be more aware of their speech disorder in their everyday life. The personalisation of the user experience may be particularly important to maintain the patient engaged with the application towards a long-term use to take full advantage of the application’s features. This paper presents the implementation of personalisation aspects in BroiStu, introducing the model that is being followed, describing the features used, and presenting the results obtained with a preliminary experiment. The personalisation mechanisms are provided by a cloud-based platform that is designed to serve different applications. Interesting findings and further work are presented.info:eu-repo/semantics/publishedVersio

Personalised, multi-modal, affective state detection for hybrid brain-computer music interfacing

Brain-computer music interfaces (BCMIs) may be used to modulate affective states, with applications in music therapy, composition, and entertainment. However, for such systems to work they need to be able to reliably detect their user's current affective state. We present a method for personalised affective state detection for use in BCMI. We compare it to a population-based detection method trained on 17 users and demonstrate that personalised affective state detection is significantly ( $p<0.01$p<0.01 ) more accurate, with average improvements in accuracy of 10.2 percent for valence and 9.3 percent for arousal. We also compare a hybrid BCMI (a BCMI that combines physiological signals with neurological signals) to a conventional BCMI design (one based upon the use of only EEG features) and demonstrate that the hybrid design results in a significant ( $p<0.01$p<0.01 ) 6.2 percent improvement in performance for arousal classification and a significant ( $p<0.01$p<0.01 ) 5.9 percent improvement for valence classification