Blink-related EEG activity measures cognitive load during proactive and reactive driving.

Assessing drivers' cognitive load is crucial for driving safety in challenging situations. This research employed the occurrence of drivers' natural eye blinks as cues in continuously recorded EEG data to assess the cognitive workload while reactive or proactive driving. Twenty-eight participants performed either a lane-keeping task with varying levels of crosswind (reactive) or curve road (proactive). The blink event-related potentials (bERPs) and spectral perturbations (bERSPs) were analyzed to assess cognitive load variations. The study found that task load during reactive driving did not significantly impact bERPs or bERSPs, possibly due to enduring alertness for vehicle control. The proactive driving revealed significant differences in the occipital N1 component with task load, indicating the necessity to adapt the attentional resources allocation based on road demands. Also, increased steering complexity led to decreased frontal N2, parietal P3, occipital P2 amplitudes, and alpha power, requiring more cognitive resources for processing relevant information. Interestingly, the proactive and reactive driving scenarios demonstrated a significant interaction at the parietal P2 and occipital N1 for three difficulty levels. The study reveals that EEG measures related to natural eye blink behavior provide insights into the effect of cognitive load on different driving tasks, with implications for driver safety.

Decoding Eye Blink and Related EEG Activity in Realistic Working Environments.

Accurately evaluating cognitive load during work-related tasks in complex real-world environments is challenging, leading researchers to investigate the use of eye blinking as a fundamental pacing mechanism for segmenting EEG data and understanding the neural mechanisms associated with cognitive workload. Yet, little is known about the temporal dynamics of eye blinks and related visual processing in relation to the representation of task-specific information. Therefore, we analyzed EEG responses from two experiments involving simulated driving (re-active and pro-active) with three levels of task load for each, as well as operating a steam engine (active vs. passive), to decode the temporal dynamics of eye blink activity and the subsequent neural activity that follows blinking. As a result, we successfully decoded the binary representation of difficulty levels for pro-active driving using multivariate pattern analysis. However, the decoding level varied for different re-active driving conditions, which could be attributed to the required level of alertness. Furthermore, our study revealed that it was possible to decode both driving types as well as steam engine operating conditions, with the most significant decoding activity observed approximately 200 ms after a blink. Additionally, our findings suggest that eye blinks have considerable potential for decoding various cognitive states that may not be discernible through neural activity, particularly near the peak of the blink. The findings demonstrate the potential of blink-related measures alongside EEG data to decode cognitive states during complex tasks, with implications for improving evaluations of cognitive and behavioral states during tasks, such as driving and operating machinery.

Tracking drivers' minds: Continuous evaluation of mental load and cognitive processing in a realistic driving simulator scenario by means of the EEG.

Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states.

Operator State in a Workplace Simulation Modulates Eye-Blink Related EEG Activity.

Evaluating and understanding the cognitive demands of natural activities has been difficult using neurocognitive approaches like mobile EEG. While task-unrelated stimuli are commonly added to a workplace simulation to estimate event-related cognitive processes, using eyeblink activity poses an alternative as it is inherent to human behavior. This study aimed to investigate the eye blink event-related EEG activity of fourteen subjects while working in a power-plant operator simulation - actively operating (active condition) or observing (passive condition) a real-world steam engine. The changes in event-related potentials, event-related spectral perturbations, and functional connectivity under both conditions were analyzed. Our results indicated several cognitive changes in relation to task manipulation. Posterior N1 and P3 amplitudes revealed alterations associated with task complexity, with increased N1 and P3 amplitudes for the active condition, indicating greater cognitive effort than the passive condition. Increased frontal theta power and suppressed parietal alpha power were observed during the active condition reflecting high cognitive engagement. Additionally, higher theta connectivity was seen in fronto-parieto-centro-temporo-occipital regions as task demands increased, showing increased communication between brain regions. All of these results suggest using eye blink-related EEG activity to acquire a comprehensive understanding of neuro-cognitive processing while working in realistic environments.

ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons.

BACKGROUND: Numerous wearables are used in a research context to record cardiac activity although their validity and usability has not been fully investigated. The objectives of this study is the cross-model comparison of data quality at different realistic use cases (cognitive and physical tasks). The recording quality is expressed by the ability to accurately detect the QRS complex, the amount of noise in the data, and the quality of RR intervals. METHODS: Five ECG devices (eMotion Faros 360°, Hexoskin Hx1, NeXus-10 MKII, Polar RS800 Multi and SOMNOtouch NIBP) were attached and simultaneously tested in 13 participants. Used test conditions included: measurements during rest, treadmill walking/running, and a cognitive 2-back task. Signal quality was assessed by a new local morphological quality parameter morphSQ which is defined as a weighted peak noise-to-signal ratio on percentage scale. The QRS detection performance was evaluated with eplimited on synchronized data by comparison to ground truth annotations. A modification of the Smith-Waterman algorithm has been used to assess the RR interval quality and to classify incorrect beat annotations. Evaluation metrics includes the positive predictive value, false negative rates, and F1 scores for beat detection performance. RESULTS: All used devices achieved sufficient signal quality in non-movement conditions. Over all experimental phases, insufficient quality expressed by morphSQ values below 10% was only found in 1.22% of the recorded beats using eMotion Faros 360°whereas the rate was 8.67% with Hexoskin Hx1. Nevertheless, QRS detection performed well across all used devices with positive predictive values between 0.985 and 1.000. False negative rates are ranging between 0.003 and 0.017. eMotion Faros 360°achieved the most stable results among the tested devices with only 5 false positive and 19 misplaced beats across all recordings identified by the Smith-Waterman approach. CONCLUSION: Data quality was assessed by two new approaches: analyzing the noise-to-signal ratio using morphSQ, and RR interval quality using Smith-Waterman. Both methods deliver comparable results. However the Smith-Waterman approach allows the direct comparison of RR intervals without the need for signal synchronization whereas morphSQ can be computed locally.

Did you even see that? visual sensory processing of single stimuli under different locomotor loads.

Modern living and working environments are more and more interspersed with the concurrent execution of locomotion and sensory processing, most often in the visual domain. Many job profiles involve the presentation of visual information while walking, for example in warehouse logistics work, where a worker has to manage walking to the correct aisle to pick up a package while being presented with visual information over data-glasses concerning the next order. Similar use-cases can be found in manufacturing jobs, for example in car montage assembly lines where next steps are presented via augmented reality headsets while walking at a slow pace. Considering the overall scarcity of cognitive resources available to be deployed to either the cognitive or motor processes, task performance decrements were found when increasing load in either domain. Interestingly, the walking motion also had beneficial effects on peripheral contrast detection and the inhibition of visual stream information. Taking these findings into account, we conducted a study that comprised the detection of single visual targets (Landolt Cs) within a broad range of the visual field (-40° to +40° visual angle) while either standing, walking, or walking with concurrent perturbations. We used questionnaire (NASA-TLX), behavioral (response times and accuracy), and neurophysiological data (ERPs and ERSPs) to quantify the effects of cognitive-motor interference. The study was conducted in a Gait Real-time Analysis Interactive Laboratory (GRAIL), using a 180° projection screen and a swayable and tiltable dual-belt treadmill. Questionnaire and behavioral measures showed common patterns. We found increasing subjective physical workload and behavioral decrements with increasing stimulus eccentricity and motor complexity. Electrophysiological results also indicated decrements in stimulus processing with higher stimulus eccentricity and movement complexity (P3, Theta), but highlighted a beneficial role when walking without perturbations and processing more peripheral stimuli regarding earlier sensory components (N1pc/N2pc, N2). These findings suggest that walking without impediments can enhance the visual processing of peripheral information and therefore help with perceiving non-foveal sensory content. Also, our results could help with re-evaluating previous findings in the context of cognitive-motor interference, as increased motor complexity might not always impede cognitive processing and performance.

[Intralogistics in the age of digital change: Job demands and mental strain in order picking using the example of a company from the e-commerce sector]. / Intralogistik im Zeitalter des digitalen Wandels: Arbeitsanforderungen und psychische Beanspruchung in der Kommissionierung am Beispiel eines Unternehmens aus dem E-Commerce-Bereich.

The e­commerce sector is experiencing a continuous boom in logistics due to digitization. Along with mostly manual activities, people remain a decisive resource in the warehouse, which must be retained and integrated with a particular view to demographic change. In the article, the survey results of a field study with focus on the area of order picking, which was conducted at a large mail-order company, are described as an example and compared with survey results from other companies. Based on the job demand resources model, stressors, challenges and resources are examined in addition to the target variables of work ability, job satisfaction and health. The results indicate that stressors and work resources roughly keep the balance, even if, for example, job satisfaction and health are only at a medium level. Above all, there is still a need of action regarding autonomy of employees. The digital transformation is seen as an opportunity to expand the scope for action and decision-making.Practical Relevance: Due to the manual nature of the activities and the predefined processes, operational logistics involves a large number of work demands that can lead to mental strain and, in the long term, to disorders or illnesses. The expansion of work-related resources is necessary to compensate for the stressors. Digitization is seen as an opportunity to expand these resources.

Evaluating Mental Load During Realistic Driving Simulations by Means of Round the Ear Electrodes.

Film based round the ear electrodes (cEEGrids) provide both, the accessibility of unobtrusive mobile EEG as well as a rapid EEG application in stationary settings when extended measurements are not possible. In a large-scale evaluation of driving abilities of older adults (N > 350) in a realistic driving simulation, we evaluated to what extent mental demands can be measured using cEEGrids in a completely unrestricted environment. For a first frequency-based analysis, the driving scenario was subdivided into different street segments with respect to their task loads (low, medium, high) that was a priori rated by an expert. Theta activity increased with task load but no change in Alpha power was found. Effects gained clarity after removing pink noise effects, that were potentially high in this data set due to motion artifacts. Theta fraction increased with task load and Alpha fraction decreased. We mapped this effect to specific street segments by applying a track-frequency analysis. Whilst participants drove with constant speed and without high steering wheel activity, Alpha was high and theta low. The reverse was the case in sections that required either high activity or increased attentional allocation to the driving context. When calculating mental demands for different street segments based on EEG, this measure is highly significant correlated with the experts' rating of task load. Deviances can be explained by specific features within the segments. Thus, modulations in spectral power of the EEG were validly reflected in the cEEGrids data. All findings were in line with the prominent literature in the field. The results clearly demonstrate the usability of this low-density EEG method for application in real-world settings where an increase in ecological validity might outweigh the loss of certain aspects of internal validity.

Recording mobile EEG in an outdoor environment reveals cognitive-motor interference dependent on movement complexity.

Oftentimes we find ourselves in situations in which we need to perform concurrent motor and cognitive tasks like simple locomotion while being cognitively involved. In the present study, we investigated in how far cognitive and motor functioning interfere in an outdoor environment. Our participants performed an auditory oddball task while concurrently completing various motor tasks on the outside premises of our institute. Beside behavioural responses and subjective workload ratings, we also analysed electrophysiological data recorded with a 30-channel mobile EEG montage. We observed an increase of subjective workload and decrease of performance with increasing movement complexity. Accordingly, we also found a decrease in the parietal P3 amplitude as well as in frontal midline Theta power with higher motor load. These results indicate that an increased movement complexity imposes a higher workload to the cognitive system, which, in turn, effectively reduces the availability of cognitive resources for the cognitive task. Overall this experiment demonstrates the feasibility of transferring classical paradigms of cognitive research to real-world settings. The findings support the notion of shared resources for motor and cognitive functions by demonstrating distinct modulations of correlates of cognitive processes across different motor tasks.

Age-Related Differences in Pro-active Driving Behavior Revealed by EEG Measures.

Healthy aging is associated with a decline in cognitive functions. This may become an issue when complex tasks have to be performed like driving a car in a demanding traffic situation. On the other hand, older people are able to compensate for age-related deficits, e.g., by deploying extra mental effort and other compensatory strategies. The present study investigated the interplay of age, task workload, and mental effort using EEG measures and a proactive driving task, in which 16 younger and 16 older participants had to keep a virtual car on track on a curvy road. Total oscillatory power and relative power in Theta and Alpha bands were analyzed, as well as event-related potentials (ERPs) to task-irrelevant regular and irregular sound stimuli. Steering variability and Theta power increased with increasing task load (i.e., with shaper bends of the road), while Alpha power decreased. This pattern of workload and mental effort was found in both age groups. However, only in the older group a relationship between steering variability and Theta power occurred: better steering performance was associated with higher Theta power, reflecting higher mental effort. Higher Theta power while driving was also associated with a stronger increase in reported subjective fatigue in the older group. In the younger group, lower steering variability came along with lower ERP responses to deviant sound stimuli, reflecting reduced processing of task-irrelevant environmental stimuli. In sum, better performance in proactive driving (i.e., more alert steering behavior) was associated with increased mental effort in the older group, and higher attentional focus on the task in the younger group, indicating age-specific strategies in the way younger and older drivers manage demanding (driving) tasks.