Evaluating a Camera-Based Approach to Assess Cognitive Load During Manufacturing Computer Tasks

Suboptimal levels of cognitive load have been shown to lead to distractions, stress, and physical injuries in work environments. Yet, traditional methods for measuring cognitive load present known logistical and methodological issues: while self-reported measures suffer from poor construct validity, physiological measures often require expensive instruments and time-consuming calibration. In recent years, research has linked blink rate (i.e., the number of eye blinks per minute) with cognitive load, showing a higher blink rate with increased load. Despite this, scientific-grade eye trackers are usually expensive and invasive, making them unsuitable for work environments. In this study, we aimed to evaluate the accuracy of a camera-based approach to measure blink rate using a widely available generic webcam. To test this, we employed two tasks that resemble computer tasks common in office and manufacturing settings. Our results showed that the camera-based approach measured cognitive load as accurately as a scientific-grade eye tracker. These findings are crucial as they provide an affordable alternative to expensive and invasive instruments for measuring cognitive load in the workplace.