Title :
Information transfer of an EEG-based brain computer interface
Author :
Schlögl, A. ; Keinrath, C. ; Scherer, R. ; Furtscheller, P.
Author_Institution :
Inst. of Biomed. Eng., Univ. of Technol. Graz, Austria
Abstract :
The idea of an EEG-based brain computer interface is to support the communication of locked-in-patients. Thus, it is important to quantify the information transfer. Wolpaw et al. (2000) proposed a measure which is derived from the classification error rate. We propose an alternative measure. Both measures are compared and the advantages and disadvantages of both are discussed.
Keywords :
autoregressive processes; electroencephalography; medical signal processing; signal classification; user interfaces; EEG-based brain computer interface; adaptive autoregressive parameters; classification error rate; communication theory; information transfer; locked-in-patients; mutual information; quadratic classifier; Biomedical informatics; Biomedical measurements; Bit rate; Brain computer interfaces; Entropy; Error analysis; Mutual information; Signal processing; Signal to noise ratio; Stochastic processes;
Conference_Titel :
Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on
Print_ISBN :
0-7803-7579-3
DOI :
10.1109/CNE.2003.1196910
