Alreshidi, IbrahimMoulitsas, IreneJenkins, Karl2024-06-032024-06-032023-09-18Alreshidi, Ibrahim; Moulitsas, Irene; Jenkins, Karl (2023). Supporting code and data for 'Miscellaneous EEG Preprocessing and Machine Learning for Pilots' Mental States Classification: Implications'. Cranfield Online Research Data (CORD). Software. https://doi.org/10.17862/cranfield.rd.24156249https://dspace.lib.cranfield.ac.uk/handle/1826/21792Data: This folder contains: - A dataset called Pilot_5_CA_raw.fif, which contains the EEG data of a pilot when he was experiencing the channelised attention state in a non-flight environment. - A dataset called Pilot_5_DA_raw.fif, which contains the EEG data of a pilot when he was experiencing the diverted attention state in a non-flight environment. - A dataset called Pilot_5_SS_raw.fif, which contains the EEG data of a pilot when he was experiencing the startle/surprise state in a non-flight environment. - A dataset called Pilot_5_LOFT_raw.fif, which contains the EEG data of a pilot when he was experiencing the channelised attention, diverted attention, and startle/surprise state in a flight simulator environment. Source code: This folder contains: - A jupyter notebook called ICAAI_Conference.ipynb which was used to generate the results of the study. - A python file called cf_matrix which was used to plot the confusion matrixMITartificial intelligence''EEG''pilot mental states'Software10.17862/cranfield.rd.24156249