Objective: We demonstrate and discuss the use of mobile electroencephalogram (EEG) for neuroergonomics. Both technical state of the art as well as measures and cognitive concepts are systematically addressed. Background: Modern work is increasingly characterized by information processing. Therefore, the examination of mental states, mental load, or cognitive processing during work is becoming increasingly important for ergonomics. Results: Mobile EEG allows to measure mental states and processes under real live conditions. It can be used for various research questions in cognitive neuroergonomics. Besides measures in the frequency domain that have a long tradition in the investigation of mental fatigue, task load, and task engagement, new approaches—like blink-evoked potentials—render event-related analyses of the EEG possible also during unrestricted behavior. Conclusion: Mobile EEG has become a valuable tool for evaluating mental states and mental processes on a highly objective level during work. The main advantage of this technique is that working environments don’t have to be changed while systematically measuring brain functions at work. Moreover, the workflow is unaffected by such neuroergonomic approaches.

The phenomenon of mental fatigue has recently been investigated extensively by means of the EEG. Studies deploying spectral analysis consistently reported an increase of spectral power in the lower frequencies with increasing time‐on‐task, whereas event‐related studies observed decreases in various measures related to task engagement and attentional resources. The results from these two lines of research cannot be aligned easily. (Frontal) theta power has been linked to cognitive control and was found to increase with time‐on‐task. In contrast, theoretical frameworks on mental fatigue suggest a decline in task‐engagement as causal for the performance decline observed in mental fatigue. The goal of the present study was to investigate mental fatigue in time–frequency space using linear regression on single‐trial data in order to obtain a better understanding about how time‐on‐task affects theta oscillatory activity. A data‐driven analysis approach indicated an increase of alpha and theta power during the intertrial interval. In contrast, task‐related theta activity declined. This reduction of stimulus‐locked theta power may be interpreted as a reduction of task engagement with increasing mental fatigue. The increase of theta spectral power in the intertrial interval, moreover, could possibly be explained by an increased idling of cognitive control networks. Alternatively, it might be the case that the increase of theta power with time‐on‐task is a by‐product an alpha power increase. As alpha peak frequency systematically decreases with time‐on‐task, the theta band might be affected as well.

Adaptively changing between different tasks while in locomotion is a fundamental prerequisite of modern daily life. The cognitive processes underlying dual tasking have been investigated extensively using EEG. Due to technological restrictions, however, this was not possible for dual‐task scenarios including locomotion. With new technological opportunities, this became possible and cognitive‐motor interference can be studied, even in outside‐the‐lab environments. In the present study, participants carried out a cognitive‐motor interference task as they responded to cued, auditory task‐switch stimuli while performing locomotive tasks with increasing complexity (standing, walking, traversing an obstacle course). We observed increased subjective workload ratings as well as decreased behavioural performance for increased movement complexity and cognitive task difficulty. A higher movement load went along with a decrease of parietal P2, N2 and P3 amplitudes and frontal Theta power. A higher cognitive load, on the other hand, was reflected by decreased frontal CNV amplitudes. Additionally, a connectivity analysis using inter‐site phase coherence revealed that higher movement as well as cognitive task difficulty had an impairing effect on fronto‐parietal connectivity. In conclusion, subjective ratings, behavioural performance and electrophysiological results indicate that less cognitive resources were available to be deployed towards the execution of the cognitive task when in locomotion compared to standing still. Connectivity results also show a scarcity of attentional resources when switching a task during the highest movement complexity condition. Summarized, all findings indicate a central role of attentional control regarding cognitive‐motor dual tasking and an inherent limitation of cognitive resources.

Mind wandering during ongoing tasks can impede task performance and increase the risk of failure in the laboratory as well as in daily‐life tasks and work environments. Neurocognitive measures like the electroencephalography (EEG) offer the opportunity to assess mind wandering non‐invasively without interfering with the primary task. However, the literature on electrophysiological correlates of mind wandering is rather inconsistent. The present study aims toward clarifying this picture by breaking down the temporal dynamics of mind wandering encounters using a cluster‐based permutation approach. Participants performed a switching task during which mind wandering was occasionally assessed via thought probes applied after trial completion at random time points. In line with previous studies, response accuracy was reduced during mind wandering. Moreover, alpha power during the inter‐trial interval was a significantly increased on those trials on which participants reported that they had been mind‐wandering. This spatially widely distributed effect is theoretically well in line with recent findings linking an increased alpha power to an internally oriented state of attention. Measurements of alpha power may, therefore, be used to detect mind wandering online during critical tasks in traffic and industry in order to prevent failures.