Electrodermal activity as a measure of cognitive load: a methodological approach

Electrodermal activity (EDA) is commonly utilized as a tool for validating psychological constructs such as emotions, affect, or cognitive load. The assumptions underlying EDA signal usefulness for psychological research is still being debated. There is a need of one, coherent methodological framework which convincingly explains the correspondence between the outcomes expected by the theory, and the actual features of the signal obtained from experiments. Thus, the scope of our work was to estimate what signal analysis workflow, and which signal features are the most appropriate for studying psychological and/or cognitive factors. We designed an experiment to detect the presence of the cognitive load during performing a task (as compared to no-task condition). The obtained data represented one of the three cognitive states: 1) baseline rest (listening to the sounds of the forest); 2) faster breathing (cognitively easy, but forcing EDA response); and 3) playing a video game (a demanding task which should elicit EDA signal increase). The analysis revealed that EDA may be successfully adapted to indirect estimation of cognitive load for given psychological state, however, further research is required in order to exactly estimate which signal features most accurately differentiate between task vs. no-task conditions.