Sathishkumar S, B.Optom

Research Fellow, Sankara Nethralaya, Chennai, India

 

In today’s fast paced work settings, stress and fatigue are challenges that impact our work performance and overall well-being. It is important to understand how these factors influence us to create better work environments and enhance productivity. Eye tracking technology and pupillometry have become tools in these different work settings.(1) They track eye movements, pupil dilation and blinking patterns. By analysing these data points, we can gain insights into an individual’s workload, cognitive strain, and stress levels.(2)

Eye tracking devices can detect signs of cognitive stress and work fatigue. For example, a rapid blink rate often signifies fatigue. Pupillometry, which measures changes in pupil size can indicate the level of effort being exerted by the brain. Large pupils may suggest increased cognitive strain or stress.(2)

Parameters such as gaze entropy and gaze pattern analysis help in understanding our concentration levels and information processing techniques. Gaze entropy assesses the predictability of eye movements; lower entropy suggests attention while higher entropy indicates distraction. Gaze pattern analysis analyses how we visually scan our surroundings, providing information, into our cognitive strategies.(3)

In a recent research study, surgeons were observed using eye trackers while performing surgeries. The goal was to investigate the impact of cognitive strain and stress during the surgery.(4) Surgeons wore advanced glasses equipped with eye tracking technology to track their eye movements and pupil changes in time. Throughout phases of the procedures the eye trackers gathered information on the surgeon’s gaze patterns, duration of focus on specific regions and changes in their pupil size and their ability to perform the task over a long duration. Subsequently this data was analysed to assess the levels of cognitive strain and stress experienced by the surgeons.(4)

Figure 1 (a and b): Different complex procedures during surgeries
https://www.shutterstock.com/search/robotic-surgeon

During complex surgery, surgeons were observed to focus intently with longer fixations, on critical areas indicating deep concentration and increased cognitive strain (Figure 1). The size of pupils increased notably during these complex procedures confirming higher stress, cognitive strain, and fatigue.

Surgeons who experience higher levels of cognitive strain and fatigue tend to blink more frequently and make minor errors, unlike those with lower cognitive strain. This highlights the importance of managing cognitive strain to ensure better performance and safety in demanding professions like surgery. By understanding how cognitive strain impacts surgeries, hospitals can implement strategies to reduce stress, including scheduling, regular breaks, and ergonomic improvements, in operating rooms. Adjusting lighting conditions, optimising the arrangement of instruments, and incorporating breaks can help reduce cognitive strain and fatigue.(5)

Eye tracking tools and pupillometry provide insights into our processes and show the impact of cognitive stress, fatigue, and workload on us.(6) With the progress of technology, eye tracking technology is becoming increasingly advanced. Potential future technology could include implementing real time feedback mechanisms that show employees of any indications of stress or tiredness.

 

References:

  1. Durugbo, C. M. (2021). Eye tracking for work-related visual search: a cognitive task analysis. Ergonomics, 64(2), 225-240.
  2. Holmqvist, K., Nyström, M., & Mulvey, F. (2012, March). Eye tracker data quality: What it is and how to measure it. In Proceedings of the symposium on eye tracking research and applications (pp. 45-52).
  3. Marshall, S. P. (2007). Identifying cognitive state from eye metrics. Aviation, space, and environmental medicine, 78(5), B165-B175.
  4. Chetwood, A. S., Kwok, K. W., Sun, L. W., Mylonas, G. P., Clark, J., Darzi, A., & Yang, G. Z. (2012). Collaborative eye tracking: a potential training tool in laparoscopic surgery. Surgical endoscopy, 26, 2003-2009.
  5. Wu, C., Cha, J., Sulek, J., Zhou, T., Sundaram, C. P., Wachs, J., & Yu, D. (2020). Eye-tracking metrics predict perceived workload in robotic surgical skills training. Human factors, 62(8), 1365-1386.
  6. Radhakrishnan, V., Louw, T., Gonçalves, R. C., Torrao, G., Lenné, M. G., & Merat, N. (2023). Using pupillometry and gaze-based metrics for understanding drivers’ mental workload during automated driving. Transportation research part F: traffic psychology and behaviour, 94, 254-267.