People with disabilities are challenged every day by barriers to communication and independent living. By analyzing the signals produced due to brain activities, Brain Computer Interfaces (BCIs) can provide an alternative channel that does not depend on peripheral nerves and muscles, between human and environment for communication and control. Both projects aimed to enhance the performance of Steady State Visual Evoked (SSVEP)-based BCIs, which are comparatively mature and widely used as spellers or to control a wheel chair due to their good usability and high information transfer rate. With an online performance measure proposed and patterned visual stimuli designed, Janir's project concentrates on developing and implementing a high performance user adaptive SSVEP-based BCIs, while, Kevin's project is in an effort to improve and extend the Canonical Correlation Analysis (CCA) algorithm, the best available method in SSVEP-based BCIs, for a better classification accuracy and wider applicability.
competition was held in Macau University of Science and Technology on 25 May
2013. This year’s competition attracted 10 teams from Hong Kong and Macau.
Aiming at promoting science and technology, the competition provided a good
opportunity for knowledge and experience exchange among students from different
Release on 2013-07-25 10:22