Ronca Vincenzo, Castagneto Gissey Lidia, Bellini Maria Irene, Iodice Alessandra, Aricò Pietro, Di Flumeri Gianluca, Giorgi Andrea, Vozzi Alessia, Capotorto Rossella, Bonelli Stefano, Moens Laura, Babiloni Fabio, Casella Giovanni, Borghini Gianluca
Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Rome, Italy.
BrainSigns srl, Rome, Italy.
Front Netw Physiol. 2025 Sep 4;5:1608824. doi: 10.3389/fnetp.2025.1608824. eCollection 2025.
Teamwork involves intricate interactions among individuals or groups with shared goals. It necessitates effective communication, defined roles, decision-making processes, and the allocation of cognitive and emotional resources. Objective teamwork assessment demands a comprehensive set of metrics. Although subjective and behavioral metrics, such as self-evaluation and task completion time, are generally applied, they are prone to bias and a lack of objectivity, highlighting the inherent limitations of capturing the unconscious processes of human behavior.
To mitigate these limitations, the present study proposed a novel approach to teamwork evaluation based on neurophysiological signals (electroencephalograms, EEGs) compatible with real-world applications, i.e., surgical teams engaged in real-world surgeries. To the best of our knowledge, there is no scientific evidence of an objective teamwork measure performed among more than two members and relying on neurophysiological signals in real-world environments. Therefore, the present work aimed at i) developing and investigating the reliability of an objective EEG-based teamwork index using mutual information (MI) methods and ii) providing additional and objective insights for surgeons' supervisors in healthcare training.
The results demonstrated the capability of the EEG-based training index to provide additional and objective information, along with its added value and reliability compared to conventional measures (all R > 0.62, all < 0.002). Furthermore, the EEG-based teamwork index allowed the determination (all < 0.001) of surgeons' experience levels (expert vs novice) in terms of cooperative behavior.
The results pave the way for targeted interventions, adaptive training sessions, and optimizations in team dynamics and open up opportunities for applying neurophysiological measurements for teamwork evaluation in all operational fields, where proper and granular teamwork optimization could play a crucial role in terms of safety.
团队合作涉及具有共同目标的个人或群体之间复杂的互动。它需要有效的沟通、明确的角色、决策过程以及认知和情感资源的分配。客观的团队合作评估需要一套全面的指标。虽然通常会应用主观和行为指标，如自我评估和任务完成时间，但它们容易产生偏差且缺乏客观性，这凸显了捕捉人类行为无意识过程的内在局限性。
为了减轻这些局限性，本研究提出了一种基于神经生理信号（脑电图，EEG）的团队合作评估新方法，该方法适用于实际应用，即参与实际手术的外科团队。据我们所知，尚无科学证据表明在现实环境中，针对两个以上成员且基于神经生理信号进行的客观团队合作测量。因此，本研究旨在：i）使用互信息（MI）方法开发并研究基于脑电图的客观团队合作指数的可靠性；ii）为医疗培训中的外科医生主管提供额外的客观见解。
结果表明，基于脑电图的训练指数能够提供额外的客观信息，并且与传统测量方法相比具有附加值和可靠性（所有R>0.62，所有P<0.002）。此外，基于脑电图的团队合作指数能够确定（所有P<0.001）外科医生在合作行为方面的经验水平（专家与新手）。
这些结果为有针对性的干预、适应性训练课程以及团队动态优化铺平了道路，并为在所有操作领域应用神经生理测量进行团队合作评估创造了机会，在这些领域中，适当且细致的团队合作优化在安全性方面可能发挥关键作用。
