The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials

Abstract

Interest in developing a new method of man-to-machine communication--a brain-computer interface (BCI)--has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.

Brain-Computer Interface (BCI) literature - a bibliometric study

“…We created a database of the BCI literature using Thomson Reuters's Institute for Scientific Information (ISI) Web of Knowledge 1 . The search, using the topic term 'BrainComputer Interface', was limited to the period from 1990 to 2008.…”

“…It shows that more than half (52.73%) of BCI publications is never cited, 12.77% cited between 3 and 10 times, 15.17% cited between 11 an 50 times, and that top BCI articles (1.3%) are cited more than 100 times. [18], [3], [13], [17], [2], [19], [14], [4], [10], [8], [16], [1], [11].…”

A comparison study of two P300 speller paradigms for brain–computer interface

“…An SVM model was trained for each subject with data collected during the calibration phase and was subsequently applied to online test. In the online test phase, the task was to input 32 predefined characters: CAT, DOG, FISH, BOWL, GLOVE, HAT, SHOES, and WATER, which were used in BCI competition 2003 by Blankertz et al (2004) (dataset IIb). Online result was provided directly on the GUI as a feedback to the subject.…”

Techniques and devices to restore cognition

“…Research on neuromotor EEG prosthetics has shown that people can learn to modulate oscillatory activity at a wide range of cortical locations and frequencies [14]. Possibilities for future research include the investigation of whether training people to increase oscillatory activity within the neural networks supporting memory function can significantly enhance learning or recall.…”