Teamwork objective assessment through neurophysiological data analysis: a preliminary multimodal data validation
Abstract
Teamwork efficiency and safety are inextricably linked. The capability of having online insights and access to objective information regarding cognitive and emotional aspects of the team members using neurophysiological measures (brain activity, skin conductance, heart rate) will endow a tool which can support Instructors during the assessment and management of teams. Such neurophysiological measures can be seen as the physical interface that will enable for gathering insights about all the aspects relating to Human Factors (HFs) of the operators. The study aimed at developing and validating a methodology able to objectively measure the teamwork dynamics and efficiency. This objective has been performed in a real surgery-related context. A data-driven approach based on machine - learning (ML) and multivariate autoregressive (MVAR) models has been employed to develop the Neurometrics - based teamwork model. Such a model considered the co-variations both within each HF (e.g., Low vs High Stress) and between different HFs (e.g., Attention vs Workload) to consider their simultaneous coexistence. The results of this preliminary study demonstrated that it is possible to quantify the teamwork of operators while dealing with real tasks and endow additional information for a more accurate teams assessment and management.
Keywords: Teamwork Assessment, Neurophysiological Data Processing, Human Factors, Neuroergonomics
DOI: 10.54941/ahfe1003010
Cite this paper
More from this volume
- Applying Smart Assistants in Express Decision for Insurance Choices
- Application of Systemic Structural Activity Theory to Web Design
- Self-Regulation Problem Solving for Sufficient Risk Reduction
- Probabilistic predictive modeling in the critical human-in-the-loop (HITL) ergonomics engineering problems
- Validity and rationality of using neuroergonomics concept in exploring worker mental issues in systemic-activity theoretical research
- The contribution of Gregory Bedny's systemic-structural activity theory to the science of activity
- Limitations on the use of eye-tracking data to understand operator awareness
- Cognitive Engineering in Training: Monitoring and Pilot-Automation Coordination in Complex Environments
- Multimodal Learnability Assessment of a Touch-based Large Area Display with Eye Tracking and Optical Brain Imaging
- Guidelines for Artificial Intelligence in Air Traffic Management: a contribution to EASA strategy
- Multimodal characterization of mental fatigue on professional drivers
- EEG assessment of driving cognitive distraction caused by central control information


AHFE Open Access