In high-pressure professions like air traffic control, managing workload and stress is critical to ensuring safety and optimizing performance. Understanding how operators respond to stress can help improve training, operational procedures, and ultimately reduce risks associated with cognitive overload. At Smart Eye, we specialize in using eye tracking technology to decode human behavior in mission-critical environments. Recently, in collaboration with LFV (Swedish Air Navigation Services) and Linköping University (LIU), we hosted the organization to talk more about their groundbreaking study to investigate the stress responses of air traffic controllers using eye tracking from Smart Eye and EEG (electroencephalography) data.
During this presentation, we showcased this study’s insights and discussed how the integration of biometric data can help predict workload levels and improve air traffic management. This blog post dives into the methodology, findings, and implications of using eye tracking and EEG for workload prediction, providing a glimpse into the future of stress management in high-stakes environments.
Air traffic controllers (ATCOs) operate in a complex and dynamic environment where workload levels can fluctuate rapidly. The ability to predict when an ATCO is approaching cognitive overload is essential for maintaining safety standards and preventing human error. Traditionally, workload assessment relied on self-reported measures, which can be inaccurate, especially during high-stress situations. This study aimed to overcome these limitations by using non-intrusive eye tracking and EEG technologies to provide a real-time understanding of workload levels.
The study used Smart Eye’s advanced eye tracking system, which captures precise data on eye movements, pupil dilation, and blink rates. The system was paired with EEG to measure brain activity, allowing for a comprehensive assessment of physiological responses to stress. During the experiment, licensed air traffic controllers participated in simulated tasks that mimicked real-world en route air traffic control scenarios. These tasks were designed to represent varying levels of workload, from light to high, allowing researchers to collect data across different conditions.
The combination of eye tracking and EEG provided a multimodal approach to understanding workload, as the two technologies measure different aspects of cognitive and physiological responses. Eye tracking data reflected visual attention and eye movement patterns, while EEG captured neurophysiological indicators of stress, such as changes in brain wave activity. Together, these data points enabled researchers to predict workload levels with remarkable accuracy.
The study revealed several key insights into how biometric data can predict workload. One of the most significant findings was the role of pupil dilation as a consistent indicator of increased cognitive effort. Despite initial concerns that lighting conditions could interfere with measurements, pupil dilation proved to be one of the most reliable predictors of workload across all tested scenarios. This finding highlights the potential for eye tracking to provide real-time, non-invasive monitoring of stress levels.
The accuracy of workload prediction was further enhanced by integrating EEG data. The combination of eye tracking and EEG allowed the research team to predict workload levels with up to 96% accuracy when using binary classification (low vs. high workload). This suggests that multimodal biometric approaches offer a more robust solution for monitoring human performance compared to using a single modality alone.
The findings of this study have far-reaching implications not only for air traffic control but also for other high-stress professions. In air traffic management, real-time workload monitoring could help supervisors make informed decisions about sector management, staffing, and task delegation. For example, biometric data could be used to trigger alerts when an ATCO’s workload reaches a critical threshold, prompting the assignment of additional staff or adjustments to task distribution to alleviate cognitive strain.
Beyond aviation, industries such as healthcare, military operations, and emergency response could benefit from incorporating biometric monitoring into their safety protocols. By understanding how stress and workload impact performance, organizations can better train personnel, optimize work environments, and develop technologies that support human operators.
The success of this study underscores the potential of using multimodal biometric data to monitor and predict workload in complex environments. While eye tracking and EEG have proven to be valuable tools for assessing cognitive load, future research could explore the integration of additional biometric measures, such as heart rate variability or skin conductance, to further enhance prediction accuracy.
For Smart Eye, the findings reinforce our commitment to advancing eye tracking technology and expanding its applications across various fields. Our research instruments division continues to develop cutting-edge solutions that offer researchers, safety professionals, and industry leaders the tools they need to understand human behavior and improve operational outcomes.
As the study demonstrated, eye tracking and EEG can provide a detailed picture of how workload impacts human performance, offering a path forward for real-time stress management in air traffic control and other high-pressure settings. By leveraging the predictive power of biometric data, organizations can take proactive steps to enhance safety, optimize performance, and support human operators in demanding roles.
Stay tuned for more insights on the future of human performance monitoring, as we continue to explore new ways to leverage biometric data for improving safety and efficiency. Our next blog series installments will delve deeper into the science behind the study and discuss the broader applications of eye tracking technology.
Want to learn more? Download the full webinar presentation here, or contact us to schedule a demo!