In this paper the development of an electromyogram (EMG) based interface for hand gesture recognition is presented. To recognize control signs in the gestures, we used a single channel EMG sensor positioned on the inside of the forearm. In addition to common statistical features such as variance, mean value, and standard deviation, we also calculated features from the time and frequency domain including Fourier variance, region length, zerocrosses, occurrences, etc. For realizing real-time classification assuring acceptable recognition accuracy, we combined two simple linear classifiers (k-NN and Bayes) in decision level fusion. Overall, a recognition accuracy of 94% was achieved by using the combined classifier with a selected feature set. The performance of the interfacing system was evaluated through 40 test sessions with 30 subjects using an RC Car. Instead of using a remote control unit, the car was controlled by four different gestures performed with one hand. In addition, we conducted a study to investigate the controllability and ease of use of the interface and the employed gestures.

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Recently, a number of research projects have been started to create virtual agents that do not just serve as assistants to which tasks may be delegated, but that may even take on the role of a companion. Such agents require a great deal of social intelligence, such as the ability to detect the user's affective state and to respond to it in an empathic manner. The objective of our work is to create an empathetic listener that is capable to react on affective and attentive input cues of the user. In particular, we discuss various forms of empathy and how they may be realized based on these cues.

Providing fun, engaging child-centric approaches to interaction is challenging. The Pictorial Interaction Language was developed for children to communicate and interact with virtual characters in a serious game, MIXER. The design and development of the Pictorial Interaction Language is briefly outlined. Results highlight that children found interacting fun and were highly positive about the Pictorial Interaction Language.

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