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Methodology

We adopt a multidisciplinary approach combining technological disciplines such as electrical engineering, machine learning, physiological and wearable computing, with human-centric fields like human-computer interaction, user-centred design, product design, and perception studies. Consortium partners have proven experience transferring research in multimodal interaction to creative industry domains such as music and video games.

BITalino

BITalino

BITalino is a low-cost toolkit to learn and prototype applications using body signals. It’s for students, teachers, makers, artists, researchers, corporate R&D… no electrical skills required. 

Repovizz

Repovizz

Repovizz is a cloud service for collaborative data-driven research projects on performance and body motion, supporting structural formatting, remote storage, browsing, exchange, annotation, and visualization of synchronous multimodal and time-aligned data.

MAVEN

MAVEN

Maven is a statistical modelling and machine-learning based framework that uses models of audiovisual attention derived from user’s eye tracking and EEG recordings. It supports the creation of context-aware features for information visualisation and audiovisual scene representation.

JUCE

JUCE

JUCE is a wide-ranging C++ class library for building rich cross-platform applications and plugins for all the major operating systems. It provides a complete set of fundamental classes covering GUI, containers, audio, midi, XML…