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Air Force Pilot Expertise Assessment with Regard to Mental Effort Requested during Unusual Attitude Recovery Flight Training Simulations. SAFETY 2022. [DOI: 10.3390/safety8020038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Pilot training and expertise are key aspects in aviation. A traditional way of evaluating pilot expertise is to measure performance output. However, this approach provides a narrow view of the pilot’s capacity, especially with regard to mental and emotional profile. The aim of this study is hence to investigate whether neurophysiological data can be employed as an additional objective measure to assess the expertise of pilots. In this regard, it has been demonstrated that mental effort can be used as an indirect measure of operator expertise and capacity. An increase in mental effort, for instance, can automatically result in a decrease in the remaining capacity of the operator. To better investigate this aspect, we ask two groups of Italian Air Force pilots, experienced (Experts) and unexperienced (Novices), to undergo unusual attitude recovery flight training simulations. Their behavioral (unusual attitude recovery time), subjective (mental effort demand perception) and neurophysiological data (Electroencephalogram, EEG; Electrocardiogram, ECG) are collected during the entire flight simulations. Although the two groups do not exhibit differences in terms of unusual attitude recovery time and mental effort demand perception, the EEG-based mental effort index shows how Novices request significantly higher mental effort during unusual conditions.
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Mehta RK, Moats J, Karthikeyan R, Gabbard JL, Srinivasan D, Du EJ, Leonessa A, Burks G, Stephenson A, Fernandes R. Human‐centered intelligent training for emergency responders. AI MAG 2022. [DOI: 10.1002/aaai.12041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Sciaraffa N, Di Flumeri G, Germano D, Giorgi A, Di Florio A, Borghini G, Vozzi A, Ronca V, Varga R, van Gasteren M, Babiloni F, Aricò P. Validation of a Light EEG-Based Measure for Real-Time Stress Monitoring during Realistic Driving. Brain Sci 2022; 12:brainsci12030304. [PMID: 35326261 PMCID: PMC8946850 DOI: 10.3390/brainsci12030304] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/11/2022] [Accepted: 02/22/2022] [Indexed: 01/27/2023] Open
Abstract
Driver’s stress affects decision-making and the probability of risk occurrence, and it is therefore a key factor in road safety. This suggests the need for continuous stress monitoring. This work aims at validating a stress neurophysiological measure—a Neurometric—for out-of-the-lab use obtained from lightweight EEG relying on two wet sensors, in real-time, and without calibration. The Neurometric was tested during a multitasking experiment and validated with a realistic driving simulator. Twenty subjects participated in the experiment, and the resulting stress Neurometric was compared with the Random Forest (RF) model, calibrated by using EEG features and both intra-subject and cross-task approaches. The Neurometric was also compared with a measure based on skin conductance level (SCL), representing one of the physiological parameters investigated in the literature mostly correlated with stress variations. We found that during both multitasking and realistic driving experiments, the Neurometric was able to discriminate between low and high levels of stress with an average Area Under Curve (AUC) value higher than 0.9. Furthermore, the stress Neurometric showed higher AUC and stability than both the SCL measure and the RF calibrated with a cross-task approach. In conclusion, the Neurometric proposed in this work proved to be suitable for out-of-the-lab monitoring of stress levels.
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Affiliation(s)
- Nicolina Sciaraffa
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Correspondence:
| | - Gianluca Di Flumeri
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Daniele Germano
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
| | - Andrea Giorgi
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Antonio Di Florio
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
| | - Gianluca Borghini
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Alessia Vozzi
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Vincenzo Ronca
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Rodrigo Varga
- ITCL Technology Centre, C. López Bravo, 70, 09001 Burgos, Spain; (R.V.); (M.v.G.)
| | - Marteyn van Gasteren
- ITCL Technology Centre, C. López Bravo, 70, 09001 Burgos, Spain; (R.V.); (M.v.G.)
| | - Fabio Babiloni
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
- College of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310005, China
| | - Pietro Aricò
- BrainSigns Srl, Lungotevere Michelangelo 9, 00192 Rome, Italy; (G.D.F.); (D.G.); (A.G.); (A.D.F.); (G.B.); (A.V.); (V.R.); (F.B.); (P.A.)
- Department of Molecular Medicine, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
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