Title :
Progress in P300-based brain-computer interfacing
Author :
Kaper, Matthias ; Ritter, Helge
Author_Institution :
Neuroinformatics Group, Bielefeld Univ., Germany
Abstract :
This paper gives a review about the progress in EEG-based brain-computer interfacing using the P300 speller paradigm in our group. Mainly, we worked on increasing the speed of this device by enhancing classification accuracy of the data. We developed a classification scheme based on the machine-learning technique support vector machines and achieved up to 97.57 bits/min.
Keywords :
electroencephalography; handicapped aids; learning (artificial intelligence); medical signal processing; reviews; signal classification; support vector machines; EEG; P300 speller paradigm; P300-based brain-computer interfacing; classification accuracy; machine learning; review; support vector machines; Brain computer interfaces; Computer interfaces; Data analysis; Electroencephalography; Humans; Signal to noise ratio; Spatial resolution; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Biomedical Circuits and Systems, 2004 IEEE International Workshop on
Print_ISBN :
0-7803-8665-5
DOI :
10.1109/BIOCAS.2004.1454154
