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

dataset
posted on 2023-06-23, 15:49 authored by Christopher Wirth, Jake TothJake Toth, Mahnaz ArvanehMahnaz Arvaneh

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.

Funding

EPSRC Doctoral Training Partnership

History

Ethics

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Policy

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Sharing and access restrictions

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Data description

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Methodology, headings and units

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