Anticipation based Brain-Computer Interfacing (aBCI)

Anticipation increases the efficiency of daily tasks by partial advance activation of neural substrates involved in it. Previous off-line studies have shown the possibility of exploiting this activation for a Brain-Computer Interface (BCI) using electroencephalogram (EEG). In the current paper we report real-time and single trial recognition of this activation using a prototype of anticipation based BCI (aBCI). We report on-line classification accuracies with peak values of 85% and 80%, and with average values of 69.0±7.9% and 58.5±14.1% for subjects 1 and 2, respectively. Posterior off-line analysis showed improved accuracies for both subjects, with an average of 80.5±10.1% and 69.0 ± 10.5% with peak values of 95% and 85% respectively.

[1]  W. Walter,et al.  Contingent Negative Variation : An Electric Sign of Sensori-Motor Association and Expectancy in the Human Brain , 1964, Nature.

[2]  P. Vetter,et al.  Reliability and Stability of Contingent Negative Variation , 2000, Applied psychophysiology and biofeedback.

[3]  A. Buttfield,et al.  Towards a robust BCI: error potentials and online learning , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[4]  B. Rockstroh.  Slow cortical potentials and behavior , 1989 .

[5]  Ricardo Chavarriaga,et al.  Fast Recognition of Anticipation-Related Potentials , 2009, IEEE Transactions on Biomedical Engineering.

[6]  Ricardo Chavarriaga,et al.  Recognition of Anticipatory Behavior from Human EEG , 2008 .

[7]  M. Nuttin,et al.  A brain-actuated wheelchair: Asynchronous and non-invasive Brain–computer interfaces for continuous control of robots , 2008, Clinical Neurophysiology.

[8]  Stevo Bozinovski,et al.  Electroexpectogram: Experimental Design and Agorithms , 1992, Proceedings of the 1992 International Biomedical Engineering Days.

[9]  K. Böcker,et al.  Cortical Measures of Anticipation , 2004 .

[10]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.