Cognitive Workload Analysis in Visual and Auditory task using EEG signals

Abstract

Cognitive workload can affect the number of errors one makes during a task. Measuring the cognitive load can be beneficial for understanding the factors effecting the performance of an individual. There is a lot of research about the measurement of cognitive workload, however a standard metric for cognitive workload estimation, applicable to multiple situations does not exist. In this study a task is designed to induce variable mental workload. This task varies not only the intrinsic workload by changing the difficulty level of task, but also the extraneous workload by varying the input methods (i.e. visual and auditory). Brain waves of participants were recorded during the task using a commercially available single channel EEG device having dry electrode at Fp1 location. Participants were also asked to give the subjective feedback about the tasks using NASA-TLX questionnaire. Power spectral densities of brainwaves are used for the estimation of mental workload and results are verified using subjective feedback. The results from experiments and power spectral densities of different brainwaves are analyzed while comparing the relaxed and working state of participants. It helps us conclude that single channel EEG device is able to differentiate between relaxed and working state of brain. Similarly, while using the already available metrics of mental workload, we observed that auditory task demands less mental resources as compared to visual tasks. Still, those metrics are not sensitive enough to differentiate among the different difficulty levels of a same task.