Neurometrics INdicators for ATM (NINA)

  • ENAC

NINA is a 27 month project co-funded in the SESAR WPE framework, started in September 2013. It will bring together three highly qualified partners with complementary competencies coming from academia, research institution and SME: DeepBlue, Sapienza Università di Roma and ENAC.
NINA intends to exploit these results and innovations to monitor the cognitive state of ATM operators and identify appropriate actions to support their activity, using sensors and a combination of neurometrics (measures of the brain’s electrical activity) and other neurophysiologic measures. These measure, regarding eye movements, blink frequency and their duration recorded in electrooculogram (EOG), electrocardiographic data (EKG) and Galvanic Skin Response data (GSR), will be collected through a non-invasive bonnet equipped with sensors, that in an industrial version of the device could be substituted with a cap connected through a wi-fi link.

The objectives

Monitor the level of cognitive workload of ATM operators in a realistic ATC context, through a combination of neurometrics and physiologic measures, characterizing the relation between the measured variables and the work performances.

Verify the existence of identifiable neurophysiologic conditionsassociated to the levels of cognitive control (e.g. Skills-Rules-Knowledge) defined by well-established cognitive models, using a combination of neurometrics and neurophysiologic measures.

Identify, prototype and evaluate the main elements of a simple adaptive interface in which adaptation is triggered by the described measures, and based on the key principles of an ecological interface (at the Skills, Rules and Knowledge levels of the cognitive control).

Validate the above results in realistic conditions through real ATM simulation facilities.