Tracking Real-Time Mental Workload during Elementary Cognitive Process (UbiComp 2010, SSCI 2014, QoLT Center)

This project seeks to develop a sensor-based method for tracking variation in cognitive processing loads (Figure 6 left).

As a preliminary study, I have explored six elementary cognitive tasks (ECTs) to assess how cognitive load varies according to task difficulty. We recruited more than 70 participants (including 27 people age 60+) and studied mental processes associated with handling interruptions, dual-task processing (e.g., way-finding requiring spatial attention switching or cognitive mapping), and task integration (e.g., comparing an ambient display with a mental legend that indicates its meaning). In terms of human cognitive abilities, we focused on visual perception and cognitive speed and explored three major first-order factors: flexibility of closure, speed of closure, and perceptual speed. The ECTs were manipulated to induce either high or low cognitive load (Figure 6 right) and their differentiability was validated based on participants’ task performance and NASA-TLX-based subject rating results. The results showed that we can build a real-time cognitive load tracker that discriminates between the two levels of mental workloads at almost 80% accuracy on averaged by using our sensor data - approx. 79% for younger adults and 86% for older adults every second, with QDA.

Figure 6. Sensor-based assessment of real-time mental workloads during a set of elementary cognitive tasks in psychology and cognitive science.