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Human-Machine Interaction Assessment by Neurophysiological Measures: A Study on Professional Air Traffic Controllers

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Maxime Reynal
Jean-Paul Imbert
Ana Ferreira
Simone Pozzi
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  • PersonId : 958163
Matteo Marucci
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Enea Pavone
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Alexandru C Telea
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Résumé

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.
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Dates et versions

hal-01843724 , version 1 (18-07-2018)

Identifiants

Citer

Pietro Aricò, Maxime Reynal, Jean-Paul Imbert, Christophe Hurter, Gianluca Borghini, et al.. Human-Machine Interaction Assessment by Neurophysiological Measures: A Study on Professional Air Traffic Controllers. EBMC 2018, 40th International Engineering in Medicine and Biology Conference, Jul 2018, Honolulu, United States. ⟨10.1109/EMBC.2018.8513212⟩. ⟨hal-01843724⟩

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