A Hierarchical Model of Finger Coordination

A scalable scatternet-based system for parallel Electroencephalography (EEG) recordings from multiple users over Bluetooth is developed. EEG has been widely used in the clinical and research settings to non-invasively measure the neural activities of healthy and diseased individuals. The typical EEG measurements require extensive wiring and preparation procedures which limited its usability for multi-subjects measurement in real-world interactive activities. In this project, we develop a novel parallel EEG recording and analysis system using mobile EEG headset as the measuring component. Each EEG headset has a single channel sensor collecting brain activity from the user. The communication and data management software we are going to develop for the system would allow simultaneous recording and processing of a significant volume of EEG data from multiple users. The developed system provides an innovative approach for integrating brain activity in the interaction with environment, which will bring radical changes in education and entertainment business (e.g. gaming and interactive media).

This is a collaborative project with an EEG headset manufacturer, NeuroSky, and the Hong Kong Institute of Education. We have developed a platform to collect EEG data from multiple subjects. The system provided an innovative approach for integrating brain activity in the interaction with environment, which would bring radical changes in education.

Motor task familiarity increased gradually after repeated practice over trials.

Average percentage change in EEG power spectral density of all participants in each trial compared to baseline.