A New Method for the Objective Registration of Mental Workload

Complex and highly automated systems impose high demands on employees with respect to cognitive capacity and the ability to cope with workload. Prevention of over-and underload at workplaces with high cognitive demands can be achieved by objectively registering mental workload. Hence, the goal of this work is the development of such an objective method. We briefly introduce the so-called Dual Frequency Head Maps (DFHM) for registering mental workload by means of the electroencephalogram (EEG). Based on them, we obtain an index of mental state every 5 s ranging between the classes low, moderate, and high workload. Finally, we present results from a sample set of 54 people who executed cognitive tasks like switching and AOSPAN in a laboratory setting. We then verify the integrity of the new method by comparing the results with further workload relevant biosignal data, performance data, and the NASA-TLX questionnaire.