Situation awareness is a term that is widely used in the human factors community. The term is used to denote one’s comprehension or understanding of the environment in which one is working. Studying this construct is important because loss of situation awareness is considered responsible for performance failures in several safety-critical domains. For example, air traffic controllers who are unaware that a loss of separation is happening is more likely to be involved in more severe operational errors.
Various techniques to measure situation awareness exist. For example, objective measures uses accuracy and time to respond to queries as a way of inferring operator situation awareness. Subjective measures rely on feedback from an expert or self-ratings to determine situation awareness. Finally, implicit performance measures are also used and that involves embedding events into scenarios that would require operators to exhibit specific behaviors.
More recently, Dr. Frank Durso and colleagues published an article in the Journal of Human Factors, wherein they discuss how facial EMG can be used to detect loss of situation awareness (or confusion).
The experimental set up was such that the participants in the experimental condition listened to a passage and were asked to raise their index finder when they heard something that did not make sense to them. Participants in the control condition raised their finger when they heard an animal being mentioned. Four facial muscles (near the left and right and left eyebrows, the mandiable, and the cheek) were recorded using EMG while participants listened to the passages.
Key takeaways from the article:
- EMG traces detected confusion in all the participants who reported that they were confused and also in 6 participants who did not report any confusion. This shows that facial EMG is a better detector of loss of situation awareness than self-report measures.
- The facial muscles near the eyebrows were the most effective in detecting confusion.
Photo credit: FASTILY via Wikimedia Commons.