Evaluation of Cognitive Test Results Using Concentration Estimation from Facial Videos

In this paper, we propose a method of discriminating between concentration and non-concentration on the basis of facial videos, and we confirm the usefulness of excluding cognitive test results when a user has not been concentrating. In a preliminary experiment, we have confirmed that level of concentration has a strong impact on correct answer rates in memory tests. Our proposed concentration/non-concentration discrimination method uses 15 features extracted from facial videos, including blinking, gazing, and facial expressions (Action Units), and discriminates between concentration and non-concentration, which are reflected in terms of a binary correct answer label set based on subjectively rated concentration levels. In the preliminary experiment, memory test scores during non-concentration states were lower than those during concentration states by an average of 18%. This has usually been included as measurement error, and, by excluding scores during non-concentration states using the proposed method, measurement error was reduced to 4%. The proposed method is shown to be capable of obtaining test results that indicate true cognitive functions when people are concentrating, making possible a more accurate understanding of cognitive functions.