Raw and processed data for "Bayesian Learning from Multi-Way EEG Feedback for Robot Navigation and Target Identification"

<p>The contents of each file is described in README.txt and below:</p> <ul> <li><em>easy.zip</em> - Raw EEG recordings.</li> <li><em>concatNumStepsToCTI</em> - Concatenated data showing all numbers of steps to Correct Target Identifications.</li> <li><em>multiwayMultifiltClassified_CV_p*.mat - </em>Classified movement action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.</li> <li><em>GClassified_CV_p*.mat</em> - Classified target identification action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.</li> <li><em>full_MTCI_MNS_tables.mat -</em>Tables containing average PTCI and MNS results for each participant at each stringency level of the Bayesian Inference strategy.</li> <li><em>rand_react_B0pt1_B0pt9_tables.mat - </em>Tables containing average PTCI and MNS results for the random strategy, and each participant with the react strategy and Bayesian Inference at stringency of 0.1 and 0.9.</li> <li><em>stepCountData.zip - </em>Zipped directory containing step counts for all runs of all participants on small and large grids using all strategies.</li> </ul> <p><br></p> <p>This work has been approved by the Automatic Control and Systems Engineering ethics committee, ethics reference number: 022698. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral training partnership.</p>