Combined Optimization of Spatial and Temporal Filters for Improving Brain-Computer Interfacing
Citations Over TimeTop 10% of 2006 papers
Abstract
Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability rates of multichannel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.
Related Papers
- → Ultra-constrained sensor platform interfacing(2012)6 cited
- Development of Underwater Interfacing System(2002)
- → Interfacing Microcomputers: Back to the Future(2002)1 cited
- → The underwater automatic interfacing system(2002)1 cited
- Susquehanna Chorale Spring Concert "Roots and Wings"(2017)