Measuring cognitive load: Heart-rate variability and pupillometry assessment

Abstract

Cognitive load covers a wide field of study that triggers the interest of many disciplines, such as neuroscience, psychology and computer science since decades. With the growing impact of human factor in robotics, many more are diving into the topic, looking, namely, for a way to adapt the control of an autonomous system to the cognitive load of its operator. Theoretically, this can be achieved from heart-rate variability measurements, brain waves monitoring, pupillometry or even skin conductivity. This work introduces some recent algorithms to analyze the data from the first two and assess some of their limitations.