No Arabic abstract
Neurofeedback games are an effective and playful approach to enhance certain social and attentional capabilities in children with autism, which are promising to become widely accessible along with the commercialization of mobile EEG modules. However, little industry-based experiences are shared, regarding how to better design neurofeedback games to fine-tune their playability and user experiences for autistic children. In this paper, we review the experiences we gained from industry practice, in which a series of mobile EEG neurofeedback games have been developed for preschool autistic children. We briefly describe our design and development in a one-year collaboration with a special education center involving a group of stakeholders: children with autism and their caregivers and parents. We then summarize four concrete implications we learnt concerning the design of game characters, game narratives, as well as gameplay elements, which aim to support future work in creating better neurofeedback games for preschool children with autism.
Product Data Management (PDM) desktop and web based systems maintain the organizational technical and managerial data to increase the quality of products by improving the processes of development, business process flows, change management, product structure management, project tracking and resource planning. Though PDM is heavily benefiting industry but PDM community is facing a very serious unresolved issue in PDM system development with flexible and user friendly graphical user interface for efficient human machine communication. PDM systems offer different services and functionalities at a time but the graphical user interfaces of most of the PDM systems are not designed in a way that a user (especially a new user) can easily learn and use them. Targeting this issue, a thorough research was conducted in field of Human Computer Interaction; resultant data provides the information about graphical user interface development using rich internet applications. The accomplished goal of this research was to support the field of PDM with a proposition of a conceptual model for the implementation of a flexible web based graphical user interface. The proposed conceptual model was successfully designed into implementation model and a resultant prototype putting values to the field is now available. Describing the proposition in detail the main concept, implementation designs and developed prototype is also discussed in this paper. Moreover in the end, prototype is compared with respective functions of existing PDM systems .i.e., Windchill and CIM to evaluate its effectiveness against targeted challenge
Autism spectrum disorder (ASD) is a developmental disorder that influences the communication and social behavior of a person in a way that those in the spectrum have difficulty in perceiving other peoples facial expressions, as well as presenting and communicating emotions and affect via their own faces and bodies. Some efforts have been made to predict and improve children with ASDs affect states in play therapy, a common method to improve childrens social skills via play and games. However, many previous works only used pre-trained models on benchmark emotion datasets and failed to consider the distinction in emotion between typically developing children and children with autism. In this paper, we present an open-source two-stage multi-modal approach leveraging acoustic and visual cues to predict three main affect states of children with ASDs affect states (positive, negative, and neutral) in real-world play therapy scenarios, and achieved an overall accuracy of 72:40%. This work presents a novel way to combine human expertise and machine intelligence for ASD affect recognition by proposing a two-stage schema.
Advances in artificial intelligence have renewed interest in conversational agents. Additionally to software developers, today all kinds of employees show interest in new technologies and their possible applications for customers. German insurance companies generally are interested in improving their customer service and digitizing their business processes. In this work we investigate the potential use of conversational agents in insurance companies theoretically by determining which classes of agents exist which are of interest to insurance companies, finding relevant use cases and requirements. We add two practical parts: First we develop a showcase prototype for an exemplary insurance scenario in claim management. Additionally in a second step, we create a prototype focusing on customer service in a chatbot hackathon, fostering innovation in interdisciplinary teams. In this work, we describe the results of both prototypes in detail. We evaluate both chatbots defining criteria for both settings in detail and compare the results and draw conclusions for the maturity of chatbot technology for practical use, describing the opportunities and challenges companies, especially small and medium enterprises, face.
We present the design of an online social skills development interface for teenagers with autism spectrum disorder (ASD). The interface is intended to enable private conversation practice anywhere, anytime using a web-browser. Users converse informally with a virtual agent, receiving feedback on nonverbal cues in real-time, and summary feedback. The prototype was developed in consultation with an expert UX designer, two psychologists, and a pediatrician. Using the data from 47 individuals, feedback and dialogue generation were automated using a hidden Markov model and a schema-driven dialogue manager capable of handling multi-topic conversations. We conducted a study with nine high-functioning ASD teenagers. Through a thematic analysis of post-experiment interviews, identified several key design considerations, notably: 1) Users should be fully briefed at the outset about the purpose and limitations of the system, to avoid unrealistic expectations. 2) An interface should incorporate positive acknowledgment of behavior change. 3) Realistic appearance of a virtual agent and responsiveness are important in engaging users. 4) Conversation personalization, for instance in prompting laconic users for more input and reciprocal questions, would help the teenagers engage for longer terms and increase the systems utility.
Robot Assisted Therapy is a new paradigm in many therapies such as the therapy of children with autism spectrum disorder. In this paper we present the use of a parrot-like robot as an assistive tool in turn taking therapy. The therapy is designed in the form of a card game between a child with autism and a therapist or the robot. The intervention was implemented in a single subject study format and the effect sizes for different turn taking variables are calculated. The results show that the child robot interaction had larger effect size than the child trainer effect size in most of the turn taking variables. Furthermore the therapist point of view on the proposed Robot Assisted Therapy is evaluated using a questionnaire. The therapist believes that the robot is appealing to children which may ease the therapy process. The therapist suggested to add other functionalities and games to let children with autism to learn more turn taking tasks and better generalize the learned tasks