At the end of February, Deep Blue, ENAC and Sapienza have carried out the second and last recording session planned for the validation activity of the NINA project. NINA explores the use of neurophysiological measures in Air Traffic Management.
Data analysis is in progress to verify the reliability of the State Classifier algorithm developed within NINA. The algorithm provides a real time evaluation of the level of cognitive workload of Air Traffic Controllers. It also contributes to assess the level of proficiency achieved during training sessions.
These results will be preparatory for the next phase of the project. NINA will use these real time information from the Mental State Classifier algorithm to trigger new prototypal adaptive automated solutions.
In a similar way, NINA had carried out a first EEG recording session to fine tune the selected neurophysiological measures. This also helped characterise the cognitive state of the ATCOs in the execution of their tasks, both in laboratory and in ATM settings.