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. 2024 Sep 17:18:1409322.
doi: 10.3389/fninf.2024.1409322. eCollection 2024.

Cooperation objective evaluation in aviation: validation and comparison of two novel approaches in simulated environment

Rossella Capotorto #  1 , Vincenzo Ronca #  2   3 , Nicolina Sciaraffa  2 , Gianluca Borghini  2   4 , Gianluca Di Flumeri  2   4 , Lorenzo Mezzadri  5 , Alessia Vozzi  2 , Andrea Giorgi  2 , Daniele Germano  3   4 , Fabio Babiloni  2   6   7 , Pietro Aricò  2   3
Affiliations

Cooperation objective evaluation in aviation: validation and comparison of two novel approaches in simulated environment

Rossella Capotorto et al. Front Neuroinform. .

Abstract

Introduction: In operational environments, human interaction and cooperation between individuals are critical to efficiency and safety. These states are influenced by individuals' cognitive and emotional states. Human factor research aims to objectively quantify these states to prevent human error and maintain constant performances, particularly in high-risk settings such as aviation, where human error and performance account for a significant portion of accidents.

Methods: Thus, this study aimed to evaluate and validate two novel methods for assessing the degree of cooperation among professional pilots engaged in real-flight simulation tasks. In addition, the study aimed to assess the ability of the proposed metrics to differentiate between the expertise levels of operating crews based on their levels of cooperation. Eight crews were involved in the experiments, consisting of four crews of Unexperienced pilots and four crews of Experienced pilots. An expert trainer, simulating air traffic management communication on one side and acting as a subject matter expert on the other, provided external evaluations of the pilots' mental states during the simulation. The two novel approaches introduced in this study were formulated based on circular correlation and mutual information techniques.

Results and discussion: The findings demonstrated the possibility of quantifying cooperation levels among pilots during realistic flight simulations. In addition, cooperation time is found to be significantly higher (p < 0.05) among Experienced pilots compared to Unexperienced ones. Furthermore, these preliminary results exhibited significant correlations (p < 0.05) with subjective and behavioral measures collected every 30 s during the task, confirming their reliability.

Keywords: approach-withdrawal; circular correlation; cooperation; electroencephalography; human factors; mental workload; mutual information; neurophysiological.

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Conflict of interest statement

VR, NS, GB, GD, AV, AG, FB, and PA were employed by BrainSigns srl. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
On the right is shown the experimental setting in the Mechtronix simulator and on the left the Mindtooth Touch EEG headset (BrainSigns srl, Rome, Italy). The system has been designed to be wearable, comfortable for a long use, easy to wear, and fully compatible with aviation tools (e.g., headphones and glasses).
Figure 2
Figure 2
Overview of the preprocessing steps and analytical methods applied to EEG signal analysis, including noise reduction, artifact removal, feature extraction, and cooperation index evaluation. Cooperation indexes are highlighted by a green framework.
Figure 3
Figure 3
Percentage of cooperation time evaluated through MICI and trainer performance assessment between EXP and UNEXP pilots. *Indicates the statistical differences between experimental groups (both p < 0.05).
Figure 4
Figure 4
Pearson's correlation between cooperation time and trainer performance assessment (R = 0.78, p < 0.05).
Figure 5
Figure 5
ANOVA comparison of MICI through different experimental phases in real and simulated crews. **Indicates the statistical difference in the behavior during the experimental phases between real and simulated crews (both p < 0.001).
Figure 6
Figure 6
Raincloud of CCI through different experimental phases on the frontal electrodes. *Indicates the statistical difference between the cooperation condition and the solo ones (i.e., Low and High diff; p < 0.010).
Figure 7
Figure 7
Raincloud plot of percentage of cooperation time between the experimental groups on frontal electrodes. *Indicates the statistical difference between the EXP and UNEXP condition (p = 0.029).
Figure 8
Figure 8
ANOVA comparison of CCI through different experimental phases in real and simulated crews. *Indicates the statistical difference in the behavior during the experimental phases between real and simulated crews (p = 0.022).
See this image and copyright information in PMC

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