A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces

Three datasets were used to conduct an open competition for evaluating the performance of various machine-learning algorithms used in brain-computer interfaces for tasks that included detecting explicit left/right (L/R) button press.

Abstract

We present three datasets that were used to conduct an open competition for evaluating the performance of various machine-learning algorithms used in brain-computer interfaces. The datasets were collected for tasks that included: 1) detecting explicit left/right (L/R) button press; 2) predicting imagined L/R button press; and 3) vertical cursor control. A total of ten entries were submitted to the competition, with winning results reported for two of the three datasets.