MAGI - Mind Augmented Gesture Interaction
The aim of MAGI project is to study always-available gesture recognition using physiological sensors and, in particular, sEMG (i.e., electrical activity of muscles) and EEG (i.e., electrical activity of the brain). In order to make the interaction “always-available”, this work is mainly based on three research axes: 1) Recognition of subtle (i.e., non-tiring, private, etc.) gestures; 2) Gesture segmentation (Recognizing when a gesture starts and ends, Understanding when a gesture is a command gesture directed to the machine or a non-command gesture, such as gesticulation, that the machine has to ignore); 3) Activity recognition (understanding the user’s current activity could allow adapting the interface following his/her needs).
gesture recognition, context awareness, multimodal interaction, human-computer interaction, human-environment interaction, psycho-physiological sensors, eletroencephalography, electromyography, machine learning techniques.
Demonstrators following main axes of the project were developed within the framework of related projects: Virtual Move, GERBIL, MUDACO, Emotiv & Aphrodite. More information on the demonstrators and related projects can be found on the website of the project in the sections "Demo
" and "Related Projects
Website of the project
Ongoing project, PhD thesis, duration 3 years (2009 - 2012).