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Abstract
International audience; This study aims at investigating the possibility to employ neurophysiological measures to assess the human - machine interaction effectiveness . Such a measure can be used to compare new technologies or solutions, with the final purpose to enhance operator’s experience and increase safety. I n the present work, two different interaction modalities (Normal and Augmented) related to Air Traffic Management field have been compared , by involving 10 professional air traffic controllers in a control tower simulated environment . Experimental task consisted in locating aircrafts in different airspace positions by using the sense of hearing. In one modality (i.e. “Normal”), all the sound sources (aircraft s ) had the same amplification factor . I n the “Augmented” modality , the amplification factor of the sound sources located al ong the participant head sagittal axis was increased, while the intensity of sound sources located outside this axis decreased . In other words, when the user oriented his head toward the aircraft position, the related sound was amplified. Performance data , subjective questionnaires (i.e. NASA - TLX) and neurophysiological measures (i.e. EEG - based) related to the experienced workload have been collected. Results showed higher significant performance achieved by the users during the “Augmented” modality with respect to the “Normal” one, supported by a significant decreasing in experienced workload, evaluated by using EEG - based index. In addition, Performance and EEG - based workload index showed a significant negative correlation. On the contrary , subjective workload analysis did not show any significant trend. This result is a demonstration of the higher effectiveness of neurophysiological measures with respect to subjective ones for Human - Computer Interaction assessment.
Original document
The different versions of the original document can be found in:
- https://www.ncbi.nlm.nih.gov/pubmed/30441381,
- https://hal-enac.archives-ouvertes.fr/hal-01843724,
- https://hal-enac.archives-ouvertes.fr/hal-01843724/document,
- https://moh-it.pure.elsevier.com/en/publications/human-machine-interaction-assessment-by-neurophysiological-measur,
- https://agliotilab.org/publications/human-machine-interaction-assessment-by-neurophysiological-measures-a-study-on-professional-air-traffic-controllers,
- https://academic.microsoft.com/#/detail/2898888872
Document information
Published on 01/01/2018
Volume 2018, 2018
DOI: 10.1109/embc.2018.8513212
Licence: CC BY-NC-SA license
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