This study aims at investigating the possibility to employ neurophysiological measures to assess the humanmachine 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. In 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 (aircrafts) had the same amplification factor. In the 'Augmented' modality, the amplification factor of the sound sources located along 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.

Human-Machine Interaction Assessment by Neurophysiological Measures: A Study on Professional Air Traffic Controllers / Arico, Pietro; Reynal, Maxime; Imbert, Jean-Paul; Hurter, Christophe; Borghini, Gianluca; Di Flumeri, Gianluca; Sciaraffa, Nicolina; DI FLORIO, Antonio; Terenzi, Michela; Ferreira, Ana; Pozzi, Simone; Betti, Viviana; Marucci, Matteo; Pavone, Enea; Telea, Alexandru C.; Babiloni, Fabio. - 2018-:(2018), pp. 4619-4622. (Intervento presentato al convegno 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 tenutosi a Honolulu, Hawaii; USA) [10.1109/EMBC.2018.8513212].

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

Arico, Pietro;Borghini, Gianluca;Di Flumeri, Gianluca
;
Sciaraffa, Nicolina;DI FLORIO, ANTONIO;TERENZI, MICHELA;Pozzi, Simone;Betti, Viviana;Marucci, Matteo;Pavone, Enea;Babiloni, Fabio
2018

Abstract

This study aims at investigating the possibility to employ neurophysiological measures to assess the humanmachine 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. In 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 (aircrafts) had the same amplification factor. In the 'Augmented' modality, the amplification factor of the sound sources located along 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.
2018
40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Signal Processing; Biomedical Engineering; 1707; Health Informatics
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Human-Machine Interaction Assessment by Neurophysiological Measures: A Study on Professional Air Traffic Controllers / Arico, Pietro; Reynal, Maxime; Imbert, Jean-Paul; Hurter, Christophe; Borghini, Gianluca; Di Flumeri, Gianluca; Sciaraffa, Nicolina; DI FLORIO, Antonio; Terenzi, Michela; Ferreira, Ana; Pozzi, Simone; Betti, Viviana; Marucci, Matteo; Pavone, Enea; Telea, Alexandru C.; Babiloni, Fabio. - 2018-:(2018), pp. 4619-4622. (Intervento presentato al convegno 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 tenutosi a Honolulu, Hawaii; USA) [10.1109/EMBC.2018.8513212].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1225188
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