For many, the pursuit and enjoyment of musical performance goes hand-in-hand with collaborative creativity, whether in a choir, jazz combo, orchestra, or rock band. However, few musical interfaces use the affordances of ...

Synchronisation is an important part of collaborative music systems, and with such systems implemented on mobile devices, the implementation of algorithms for synchronisation without central control becomes increasingly ...

We present Funky Sole Music, a musical interface employing a sole embedded with three force sensitive resistors in combination with a novel algorithm for continuous movement classification. A heuristics-based music engine ...

Our research on music-related actions is based on the conviction that sensations of both sound and body motion are inseparable in the production and perception of music. The expression "musicrelated actions" is here used ...

We consider the issue of how a flexible musical space can be manipulated by users of an active music system. The musical space is navigated within by selecting transitions between different sections of the space. We take ...

In this paper, we present an open source partial reconfiguration (PR) system which is designed for portability and usability serving as a reference for engineers and students interested in using the advanced reconfiguration ...

This paper describes the process of developing a standstill performance work using the Myo gesture control armband and the Bela embedded computing platform. The combination of Myo and Bela allows a portable and extensible ...

A robot moving in the home is a new experience for most people. Classifying the different ways that humans and robots move together can help in designing interactions. In this paper, we first put robots’ movements into two ...

For robots to handle the numerous factors that can afect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of these issues by automatically optimizing a ...

A significant problem of using deep learning techniques is the limited amount of data available for training. There are some datasets available for the popular problems like item recognition and classification or self-driving ...