Raw and processed data for "Bayesian Learning from Multi-Way EEG Feedback for Robot Navigation and Target Identification"
The contents of each file is described in README.txt and below:
- easy.zip - Raw EEG recordings.
- concatNumStepsToCTI - Concatenated data showing all numbers of steps to Correct Target Identifications.
- multiwayMultifiltClassified_CV_p*.mat - Classified movement action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
- GClassified_CV_p*.mat - Classified target identification action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
- full_MTCI_MNS_tables.mat -Tables containing average PTCI and MNS results for each participant at each stringency level of the Bayesian Inference strategy.
- rand_react_B0pt1_B0pt9_tables.mat - 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.
- stepCountData.zip - Zipped directory containing step counts for all runs of all participants on small and large grids using all strategies.
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.
EPSRC Doctoral Training Partnership
- The project has ethical approval and the number is included in the description field
- The data complies with the institution and funders' policies on access and sharing
Sharing and access restrictions
- The data can be shared openly
- The file formats are open or commonly used
Methodology, headings and units
- There is a file including methodology, headings and units, such as a readme.txt