Classification of mental workload using brain connectivity and machine learning on electroencephalogram data

Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In this paper, we propose innovative methods to assess mental workload from EEG data that use effective brain connectivity for the purpose of extracting features, a hierarchical feature selection algorithm to select the most significant features, and finally machine learning models. We have used the Simultaneous Task EEG Workload (STEW) dataset, an open-access collection of raw EEG data from 48 subjects. We extracted brain-effective connectivities by the direct directed transfer function and then selected the top 30 connectivities for each standard frequency band. Then we applied three feature selection algorithms (forward feature selection, Relief-F, and minimum-redundancy-maximum-relevance) on the top 150 features from all frequencies. Finally, we applied sevenfold cross-validation on four machine learning models (support vector machine (SVM), linear discriminant analysis, random forest, and decision tree). The results revealed that SVM as the machine learning model and forward feature selection as the feature selection method work better than others and could classify the mental workload levels with accuracy equal to 89.53% (± 1.36).

Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment

Advancements in portable neuroimaging technologies open up new opportunities to gain insight into the neural dynamics and cognitive processes underlying day-to-day behaviors. In this study, we evaluated the relevance of a headphone- mounted electroencephalogram (EEG) system for monitoring mental workload. The participants (N = 12) were instructed to pay attention to auditory alarms presented sporadically while performing the Multi-Attribute Task Battery (MATB) whose difficulty was staged across three conditions to manipulate mental workload. The P300 Event-Related Potentials (ERP) elicited by the presentation of auditory alarms were used as probes of attentional resources available. The amplitude and latency of P300 ERPs were compared across experimental conditions. Our findings indicate that the P300 ERP component can be captured using a headphone-mounted EEG system. Moreover, neural responses to alarm could be used to classify mental workload with high accuracy (over 80%) at a single-trial level. Our analyses indicated that the signal-to-noise ratio acquired by the sponge-based sensors remained stable throughout the recordings. These results highlight the potential of portable neuroimaging technology for the development of neuroassistive applications while underscoring the current limitations and challenges associated with the integration of EEG sensors in everyday-life wearable technologies. Overall, our study contributes to the growing body of research exploring the feasibility and validity of wearable neuroimaging technologies for the study of human cognition and behavior in real-world settings.

Assessing mental demand in consecutive interpreting: Insights from an fNIRS study

Consecutive interpreting involves a demanding language task where mental workload (MWL) is crucial for assessing interpreters' performance. An elevated cognitive load in interpreters may lead to the interpretation failures. The widely used NASA-TLX questionnaire effectively measures MWL. However, a global score was employed in previous interpretation studies, overlooking the distinct contributions of MWL components to the interpreters' performance. Accordingly, we recruited twenty novice interpreters who were postgraduate students specializing in interpreting to complete the consecutive interpreting task. Throughout the process, we used functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in participants' brains. The NASA-TLX was used to measure the MWL during interpreting with six components, including mental demand, physical demand, temporal demand, performance, effort, and frustration. Five interpretation experts were invited to assess the interpretation quality. The Bayes factor approach was employed to explore the components that contributes the most to the interpretation quality. It indicated that mental demand strongly contributed to the interpretation quality. Moreover, the mediation analysis revealed a positive correlation between mental demand and brain activation in three brain areas, which, in turn, was negatively correlated with interpretation quality, indicating the predictive role of mental demand in interpretation quality through the mediating of brain activation. The functions of the mediating brain areas, including the inferior frontal gyrus, middle temporal gyrus, and inferior temporal gyrus, aligned with the three efforts proposed by Gile's effort model, which emphasizes the significance of three fundamental efforts in achieving successful interpreting. These findings have implications for interpreter learning and training.

Developing a novel energy-based approach for measuring mental workload

Minimal research has been conducted to develop non-invasive processes for quantifying and evaluating worker mental workload - a critical concern - at the task level in the construction industry. One reason for this gap in research is the complex and dynamic nature of the construction process, which makes construction work more complicated to measure and predict compared to work in other industries. This paper presents a novel approach and corresponding conceptual model to quantify and evaluate construction worker perception of mental workload at the task level using the energy concept. A conceptual process for assessing mental workload (MWL), i.e., the feeling of stress, pressure, and being overwhelmed due to the task nature, factors, conditions, and resources that accompany the performance of the task, was developed from extant research and interviews. The Delphi method was utilized to characterize the energy-based model and provide initial verification. The results from the literature review, expert insight, and four rounds of the Delphi survey revealed 14 constituents, 51 components, and one metric for each component to measure the level of MWL felt by a worker. These constituents, components, and metrics were used to develop a model for measuring construction worker MWL. This study contributes to knowledge by developing a novel non-invasive method for assessing potential task-level MWL using an energy-based model. The energy-based assessment model contributes to practice by providing a tool that could be used to measure the potential impact of construction tasks on workers perceived mental workload.

The effects of increased mental workload of air traffic controllers on time perception: Behavioral and physiological evidence

Research has shown that timing is modulated by mental workload, making duration judgments a measure of cognitive demand, alongside subjective assessments, and physiological measurements. Yet, it is unclear whether such findings can be extended in less controlled setups. By employing air traffic controllers in a real aviation environment, we tested whether tasks with different levels of cognitive load can affect their timing behavior. Participants completed temporal production, verbal estimation, and passage of time judgments, while actively engaging in real flight control sessions. Subjective assessments of task demands, as well as physiological responses (cardiac and electrodermal activity) were also measured. Accuracy of the produced intervals was measured at two distinct phases of the flight (during low-load cruising vs. high-load landing) and under two different task load manipulations (controlling one vs. two helicopters and speaking in native vs. non-native language). Analysis of interval production accuracy showed that during the high-load landing phase significant overproductions were made, compared to the low-load cruising phase, and landing two helicopters led to greater overproductions compared to landing only one. The duration of the two-helicopter sessions was significantly overestimated compared to the single-helicopter ones, and the passage of time was felt significantly faster. Subjective assessments of workload were positively correlated with the temporal estimations and passage of time judgments, and skin responses were positively correlated with the produced intervals. Overall, our results are consistent with past research, suggesting that mental workload modulates time perception in complex, real-world environments, thus making timing behavior a reliable index of the workload changes.

Neurophysiological and biosignal data for investigating occupational mental fatigue: MEFAR dataset

The prevalence of mental fatigue is a noteworthy phenomenon that can affect individuals across diverse professions and working routines. This paper provides a comprehensive dataset of physiological signals obtained from 23 participants during their professional work and questionnaires to analyze mental fatigue. The questionnaires included demographic information and Chalder Fatigue Scale scores indicating mental and physical fatigue. Both physiological signal measurements and the Chalder Fatigue Scale were performed in two sessions, morning and evening. The present dataset encompasses diverse physiological signals, including electroencephalogram (EEG), blood volume pulse (BVP), electrodermal activity (EDA), heart rate (HR), skin temperature (TEMP), and 3-axis accelerometer (ACC) data. The NeuroSky MindWave EEG device was used for brain signals, and the Empatica E4 smart wristband was used for other signals. Measurements were carried out on individuals from four different occupational groups, such as academicians, technicians, computer engineers, and kitchen workers. The provision of comprehensive metadata supplements the dataset, thereby promoting inquiries about the neurophysiological concomitants of mental fatigue, autonomic activity patterns, and the repercussions of a cognitive burden on human proficiency in actual workplace settings. The accessibility of the aforementioned dataset serves to facilitate progress in the field of mental fatigue research while also laying the groundwork for the creation of customized fatigue evaluation techniques and interventions in diverse professional domains.

Assessing workload in using electromyography (EMG)-based prostheses

Using prosthetic devices requires a substantial cognitive workload. This study investigated classification models for assessing cognitive workload in electromyography (EMG)-based prosthetic devices with various types of input features including eye-tracking measures, task performance, and cognitive performance model (CPM) outcomes. Features selection algorithm, hyperparameter tuning with grid search, and k-fold cross-validation were applied to select the most important features and find the optimal models. Classification accuracy, the area under the receiver operation characteristic curve (AUC), precision, recall, and F1 scores were calculated to compare the models' performance. The findings suggested that task performance measures, pupillometry data, and CPM outcomes, combined with the naïve bayes (NB) and random forest (RF) algorithms, are most promising for classifying cognitive workload. The proposed algorithms can help manufacturers/clinicians predict the cognitive workload of future EMG-based prosthetic devices in early design phases.Practitioner summary: This study investigated the use of machine learning algorithms for classifying the cognitive workload of prosthetic devices. The findings suggested that the models could predict workload with high accuracy and low computational cost and could be used in assessing the usability of prosthetic devices in the early phases of the design process.Abbreviations: 3d: 3 dimensional; ADL: Activities for daily living; ANN: Artificial neural network; AUC: Area under the receiver operation characteristic curve; CC: Continuous control; CPM: Cognitive performance model; CPM-GOMS: Cognitive-Perceptual-Motor GOMS; CRT: Clothespin relocation test; CV: Cross validation; CW: Cognitive workload; DC: Direct control; DOF: Degrees of freedom; ECRL: Extensor carpi radialis longus; ED: Extensor digitorum; EEG: Electroencephalogram; EMG: Electromyography; FCR: Flexor carpi radialis; FD: Flexor digitorum; GOMS: Goals, Operations, Methods, and Selection Rules; LDA: Linear discriminant analysis; MAV: Mean absolute value; MCP: Metacarpophalangeal; ML: Machine learning; NASA-TLX: NASA task load index; NB: Naïve Bayes; PCPS: Percent change in pupil size; PPT: Purdue Pegboard Test; PR: Pattern recognition; PROS-TLX: Prosthesis task load index; RF: Random forest; RFE: Recursive feature selection; SHAP: Southampton hand assessment protocol; SFS: Sequential feature selection; SVC: Support vector classifier.

How a pilot's brain copes with stress and mental load? Insights from the executive control network

In aviation, mental workload and stress are two major factors that can considerably impact a pilot's flight performance and decisions. Their consequences can be even more dramatic in single-pilot aircraft or with the forthcoming single-pilot operations where the pilot will fly alone and will not be able to be assisted in case of difficulty. An accurate and automatic monitoring of the pilot's mental state could help to prevent the potentially dangerous effects of an excess mental workload and stress. For example, some tasks could be allocated to automation or to a ground-based flight crew if a mental overload or significant stress is detected. In the current study, the brain activity of 20 private pilots was recorded with a fNIRS device during two realistic flight simulator scenarios. The mental workload was manipulated with the added difficulty of a secondary task and stress was induced by a social stressor. Our results confirmed the sensitivity of the fNIRS readings to variations in the mental workload, with increased HbO2 concentration in regions of the executive control network (ECN), in particular in the dorsolateral prefrontal cortex and in lateral parietal regions, when the difficulty of the secondary task was high. The social stressor also triggered an HbO2 increase in the ECN, especially when it was combined with high mental workload. This latter result suggests that mental workload and stress together can have cumulative effects, and coping with both factors is possible at the expense of an extra recruitment of the ECN. Finally, results also revealed a time-on-task effect, with a progressive reduction of the HbO2 signal in the ECN during the flight scenario, suggesting that these regions are sensitive to short term habituation to the tasks. Overall, fNIRS efficiently indexed mental load, stress, and practice effects.

Investigation of eye movement measures of mental workload in healthcare: Can pupil dilations reflect fatigue or overload when it comes to health information system use?

The use of health information systems (HIS) can result in high workloads and, consequently, poor performance characterized by e.g. increased occurrence of errors among clinicians. Pupillometry offers a good possibility to measure mental workload in a dynamic work setting. Currently, there is a lack of empirical research in the context of healthcare settings. Therefore, the aim of the present study was to examine whether specific eye movement measures are suitable for measuring mental workload in the healthcare setting, especially when working with HIS. 49 persons participated in our simulation-lab study. They had to complete a system-related task as well as an increasing n-back task. Both tasks were modified regarding task difficulty. Results show significant differences for objective and subjective workload measures between increasing task levels. There are also hints for an overload/fatigue indicator in pupil data. Our results are limited in terms of external validity, causality and effects. Future work should focus on high-fidelity simulations and less time-consuming analysis approaches.

Correlation of Work Fatigue and Mental Workload in Train Drivers: A Cross-sectional Study

BACKGROUND

Evidence suggests that train drivers experience a high level of fatigue and mental workload. The present study aimed to assess overall, physical, and mental fatigue levels and their correlations with the mental workload in the metro train operation. Study Design: A cross-sectional study.

METHODS

This study was conducted on all 1194 train drivers in the Tehran Metro. The train drivers completed the Samn-Perelli Fatigue Scale and the Fatigue Assessment Scales at the beginning and end of the shift. In addition, they completed the National Aeronautics and Space Administration Task Load Index in the middle and at the end of the shift. Correlation and regression analyses were performed on the data to test the study hypothesis.

RESULTS

Overall, physical, and mental fatigue levels increased significantly at the end of the shift compared to the onset of the shift (P<0.001). The mental workload and related dimensions were significantly increased at the end of the shift compared to the middle of the shift (P<0.001). Mental demand was the most important workload problem among the train drivers. The highest correlation was found between overall workload and time pressure (R=0.68, P<0.001).

CONCLUSION

The mental workload had a significant correlation with work fatigue in the train drivers. Control measures should be focused on the mental workload and related dimensions, especially mental demand and time pressure.

Task-independent auditory probes reveal changes in mental workload during simulated quadrotor UAV training

Objective

The event-related potential (ERP) methods based on laboratory control scenes have been widely used to measure the level of mental workload during operational tasks. In this study, both task difficulty and test time were considered. Auditory probes (ignored task-irrelevant background sounds) were used to explore the changes in mental workload of unmanned aerial vehicle (UAV) operators during task execution and their ERP representations.

Approach

51 students participated in a 10-day training and test of simulated quadrotor UAV. During the experiment, background sound was played to induce ERP according to the requirements of oddball paradigm, and the relationship between mental workload and the amplitudes of N200 and P300 in ERP was explored.

Main results

Our study shows that the mental workload during operational task training is multi-dimensional, and its changes are affected by bottom-up perception and top-down cognition. The N200 component of the ERP evoked by the auditory probe corresponds to the bottom-up perceptual part; while the P300 component corresponds to the top-down cognitive part, which is positively correlated with the improvement of skill level.

Significance

This paper describes the relationship between ERP induced by auditory probes and mental workload from the perspective of multi-resource theory and human information processing. This suggests that the auditory probe can be used to reveal the mental workload during the training of operational tasks, which not only provides a possible reference for measuring the mental workload, but also provides a possibility for identifying the development of the operator's skill level and evaluating the training effect.

The mediating effect of personality on mental workload and perceived professional benefits of nurses in East China

BACKGROUND

Nursing work is a work with high-stress load, and nurses with different personality may have different subjective feelings about their workload. Therefore, it is particularly necessary to comprehend the perceived professional benefits of nurses engaged in nursing work under high-pressure background, especially during the epidemic period. This study explored the relationship between mental workload, personality, and perceived professional benefits of nurses, and offer advices for the intervention of nurses with different personality to improve their perceived professional benefits.

MATERIALS AND METHODS

In this study, we used a cross-sectional study with a convenient sampling. 473 in-service nurses in Class A tertiary hospitals of Zhejiang Province were recruited by using the NASA Mission Load Index scale of nurses, the brief version of China's Big Five Personality Questionnaire, and the Nurses' perceived professional benefits questionnaire from July 2020 to March 2021. Sample size is 54.91%, and the response rate is 100%. Cronbach's alpha method was used to evaluate the reliability of the instruments. Descriptive statistical analysis was used to describe the socio-demographic data of the subject, and scores for research variables. The Mann-Whitney U-test, and Kruskal-Wallis H rank-sum test were used to compare the scores of perceived professional benefits with different demographic characteristics. Correlation analysis results were presented as the Spearman correlation coefficient. The plug-in v2.16.3 provided by SPSS software was used for linear regression analysis, and the deviation-corrected percentile Bootstrap method was used to examine the mediating role of personality (neuroticism, conscientiousness, agreeableness, openness and extroversion).

RESULTS

Age, length of service in nursing, and record of formal schooling can affect nurses' perceived professional benefits. Mental workload, and perceived professional benefits were all above the median value. The mental workload was negatively correlated with perceived professional benefits (r= -0.129, P < 0.01), positively correlated with neuroticism (r = 0.242, P < 0.01), negatively correlated with agreeableness, openness, extroversion (r=-0.229~-0.221, P < 0.01), and negatively correlated with conscientiousness, but the differences were not significant. Nurses' perceived professional benefits were negatively correlated neuroticism (r=-0.109, P < 0.05), but positively associated with conscientiousness, agreeableness, openness, and extroversion (r = 0.098 ~ 0.326, P < 0.05). The mental workload can directly affect the perceived professional benefits in the direct effects, and can also affect the it through the mediating effect of agreeableness, extroversion, neuroticism, and openness.

CONCLUSIONS

Age, length of service in nursing, and record of formal schooling could affect nurses' perceived professional benefits, and personality played a partial mediating role in the influence of mental workload on the perceived professional benefits. The results of this study can provide strategies for nurses' human resource management. According to different demographic factors, and personality, various measures should be taken to guide nurses to evaluate the mental workload correctly, reduce their emotional pressure, increase job resources, and improve their perceived professional benefits.

Assessing subjective workload for live captioners

Live captioning is a challenging task that requires intense concentration to convert audio to text in real-time. Despite the importance of live captioning for accessibility, little is known about the subjective workload of captioners in this context. This study aimed to measure the subjective workload of live captioners using the NASA-TLX and to explore the factors that contribute to their mental workload. Thirty live captioners participated in the study, completing questionnaires and interviews. Results showed that the subjective mental workload of live captioners is high, similar to that of neurosurgeons. The mental workload was found to be associated with caption paraphrasing and employment status. The challenges of the job, such as the speed of speaking in live content, cognitive tasks involved in paraphrasing, the concern about poor performance, the impact on audiences, and the lack of control over job scheduling contribute to this high workload. These findings suggest the need for modulating the scheduling of the workers, having longer breaks, and working in teams rather than independently. Introducing paradigm changes for live captioning workflow, such as reducing the human effort of typing by adopting auto-generated captions, so that captioners become decision-makers or managers of generational AI systems should also be considered. By addressing these issues, we can help improve the well-being of live captioners and the quality of captions, ultimately enhancing accessibility for all.

The 'invisible gorilla' during pedestrian-AV interaction: Effects of secondary tasks on pedestrians' reaction to eHMIs

In road traffic, mental overload often leads to a failure to notice new and distinctive stimuli. Such phenomenon is known as 'inattentional blindness'. Safe and efficient interaction between automated vehicles (AVs) and pedestrians is expected to rely heavily on external human-machine interfaces (eHMIs), a tool AVs are equipped with to communicate their intentions to pedestrians. This study seeks to explore the phenomenon of 'inattentional blindness' in the context of pedestrian-AV interactions. Specifically, the aim is to understand the effects of a warning eHMI on pedestrians' crossing decisions when they are engaged in a secondary task. In an experiment study with videos of pedestrian crossing scenarios filmed from the perspective of the crossing pedestrian, participants had to decide the latest point at which they would be willing to cross the road in front of an AV with an eHMI vs. an AV without an eHMI. Participants were also asked to predict the future behavior of the AV. 125 female and 9 male participants aged between 18 and 25 completed the experiment and a follow-up questionnaire. It was found that the presence of a warning eHMI on AVs contributes to a clearer understanding of pedestrians' inferences about the intention of AVs and helps deter late and dangerous crossing decisions made by pedestrians. However, the eHMI fail to help pedestrians avoid such decisions when they face a high mental workload induced by secondary task engagement.

Mental workload profile and its relationship with presenteeism, absenteeism and job performance among surgeons: The mediating role of occupational fatigue

Introduction

Surgeons are one of the most significant jobs in the health care system that plays an important role in the patients' health promotion and their treatment. In the current study, the effect of mental workload on the work performance of surgeons was tested by considering the mediating effect of fatigue on this relationship.

Method

This study was done analytically on 165 surgeons working in the operating rooms of hospitals in Iran. To determine of mental workload, the SURG-TLX method was used. The job performance was measured using the short version of the job performance questionnaire provided by the World Health Organization (WHO-HPQ), and accordingly relative presenteeism, relative absenteeism and job performance variables were calculated. The Swedish Occupational Fatigue Inventory (SOFI) questionnaire was used to determine occupational fatigue. A conceptual model was built to determine the direct and indirect relationship between mental workload and job performance, and the mediating effect of occupational fatigue on the relationship between mental workload and job performance was tested using structural equation modeling (SEM).

Results

Out of 165 distributed questionnaires, 140 questionnaires were completed and delivered to the researchers (85% response rate). The mean ± standard deviations of mental workload, fatigue, and work performance were 16.57 ± 5.83, 6.32 ± 2.86, and 0.65 ± 0.28, respectively. The results of model fit indexes revealed that all indexes are within the acceptable range. Regarding this model, the direct effect of mental workload on job performance was not significant (β = -0.21; p = 0.072). A significant positive relationship was observed between mental workload and fatigue (β = 0.36; p < 0.001). The direct effect of fatigue on job performance was also the opposite and statistically significant (β = -0.39; p < 0.001). Finally, results indicated that the effect of mental workload on work performance mediated by occupational fatigue.

Conclusion

Surgeons suffer a high level of mental workload during their work, and this factor can have a negative effect on surgeons' job performance. The effect of mental workload on job performance in surgeons can be detected, directly and indirectly, through the mediating effect of occupational fatigue. Improving the mental and physical conditions of the work environment can reduce occupational fatigue and improve surgeons' job performance.

A study on predictive factors

INTRODUCTION

Mental workload refers to the cognitive or intellectual requirements that a worker is subjected to in a workday. The objective of the present work was to discover the subjective mental workload of nursing staff at Hospital Emergency Units, and its relationship with sociodemographic, work, environmental factors at the workplace, and personality variables.

METHOD

A quantitative, descriptive, observational, and crosssectional study was conducted with 201 emergency nurses from 13 different provinces in Spain. Each participant completed 5 questionnaires (sociodemographic, work conditions, environmental conditions, personality, and subjective mental workload). Descriptive statistics were obtained, and Pearson's correlations and multivariate models (multiple linear regression) were performed.

RESULTS

The nurses had medium to high levels of mental workload. The environmental conditions had a direct relationship with the mental workload, especially with respect to noise and lighting. The participants obtained high scores in kindness, responsibility, openness/intellect, and extraversion. Positive and statistically significant relations were found between neuroticism and mental workload. Being female, older, and having stable employment or a permanent contract were associated with a greater mental workload of emergency nurses.

CONCLUSION

The domain of neuroticism personality, and the hygienic conditions in the workplace were the predictors with the most weight in the model. This study could be useful for defining aspects that need to be considered for the well-being of emergency nurses, such as lighting conditions or environmental noise in the workplace. It also invites reflection on the influence of personal factors (age, gender, personality) and work factors (type of contract, professional experience) on the mental workload of emergency nurses.

Multimodal Approach to Assess a Virtual Reality-based Surgical Training Platform

Virtual reality (VR) can bring numerous benefits to the learning process. Combining a VR environment with physiological sensors can be beneficial in skill assessment. We aim to investigate trainees' physiological (ECG) and behavioral differences during the virtual reality-based surgical training environment. Our finding showed a significant association between the VR-Score and all participants' total NASA-TLX workload score. The extent of the NASA-TLX workload score was negatively correlated with VR-Score (R2 =0.15, P < 0.03). In time-domain ECG analysis, we found that RMSSD (R2 =0.16, P < 0.05) and pNN50 (R2 =0.15, P < 0.05) scores correlated with significantly higher VR-score of all participants. In this study, we used SVM (linear kernel) and Logistic Regression classification techniques to classify the participants as gamers and non-gamers using data from VR headsets. Both SVM and Logistic Regression accurately classified the participants as gamers and non-gamers with 83% accuracy. For both SVM and Linear Regression, precision was noted as 88%, recall as 83%, and f1-score as 83%. There is increasing interest in characterizing trainees' physiological and behavioral activity profiles in a VR environment, aiming to develop better training and assessment methodologies.

A mental workload and biomechanical assessment during split-belt locomotor adaptation with and without optic flow

Adaptive human performance relies on the central nervous system to regulate the engagement of cognitive-motor resources as task demands vary. Despite numerous studies which employed a split-belt induced perturbation to examine biomechanical outcomes during locomotor adaptation, none concurrently examined the cerebral cortical dynamics to assess changes in mental workload. Additionally, while prior work suggests that optic flow provides critical information for walking regulation, a few studies have manipulated visual inputs during adaption to split-belt walking. This study aimed to examine the concurrent modulation of gait and Electroencephalography (EEG) cortical dynamics underlying mental workload during split-belt locomotor adaptation, with and without optic flow. Thirteen uninjured participants with minimal inherent walking asymmetries at baseline underwent adaptation, while temporal-spatial gait and EEG spectral metrics were recorded. The results revealed a reduction in step length and time asymmetry from early to late adaptation, accompanied by an elevated frontal and temporal theta power; the former being well corelated to biomechanical changes. While the absence of optic flow during adaptation did not affect temporal-spatial gait metrics, it led to an increase of theta and low-alpha power. Thus, as individuals adapt their locomotor patterns, the cognitive-motor resources underlying the encoding and consolidation processes of the procedural memory were recruited to acquire a new internal model of the perturbation. Also, when adaption occurs without optic flow, a further reduction of arousal is accompanied with an elevation of attentional engagement due to enhanced neurocognitive resources likely to maintain adaptive walking patterns.

Video game experience affects performance, cognitive load, and brain activity in laparoscopic surgery training

Objectives

Video games can be a valuable tool for surgery training. Individuals who interact or play video games tend to have a better visuospatial ability when compared to non-gamers. Numerous studies suggest that video game experience is associated with faster acquisition, greater sharpening, and longer retention of laparoscopic skills. Given the neurocognitive complexity of surgery skill, multimodal approaches are required to understand how video game playing enhances laparoscopy skill.

Material and Methods

Twenty-seven students with no laparoscopy experience and varying levels of video game experience performed standard laparoscopic training tasks. Their performance, subjective cognitive loading, and prefrontal cortical activity were recorded and analyzed. As a reference point to use in comparing the two novice groups, we also included data from 13 surgeons with varying levels of laparoscopy experience and no video game experience.

Results

Results indicated that video game experience was correlated with higher performance (R2 = 0.22, p <0.01) and lower cognitive load (R2 = 0.21, p <0.001), and the prefrontal cortical activation of students with gaming experience was relatively lower than those without gaming experience. In terms of these variables, gaming experience in novices tended to produce effects similar to those of laparoscopy experience in surgeons.

Conclusion

Our results suggest that along the dimensions of performance, cognitive load, and brain activity, the effects of video gaming experience on novice laparoscopy trainees are similar to those of real-world laparoscopy experience on surgeons. We believe that the neural underpinnings of surgery skill and its links with gaming experience need to be investigated further using wearable functional brain imaging.

Mental workload variations during different cognitive office tasks with social media interruptions

Interruption at work by social media (SM) is a pervasive phenomenon. This study investigated the impact of SM interruptions and task cognitive levels on mental workload (MWL) and physiological indexes. Each subject performed six simulated computer tasks differentiated by two factors: task cognitive level and performing condition. MWL was reflected through three categories of data: perceived mental workload, physiological indexes, and primary task performance. The results revealed significant effects of SM interruptions on heart rate, low-frequency/high-frequency (LF/HF) ratio, and skin conductance. ANOVA results showed there were main effects of task cognitive level on LF/HF and skin conductance. These effects during interrupted tasks were more profound. In addition, participants experienced higher MWL and recorded lower primary task performance in the knowledge-based task than the rule- and skill-based tasks. Our findings can guide managers and employees regarding appropriate use of SM in the workplace and better managing interruption and workload.Practitioner Summary: Office workers suffer from increased overall mental workload due to unpredictable interruptions while working. This study shows that participants' mental workload increased when receiving SM interruptions, which was more profound during complex tasks. This highlights the importance of SM interruptions management for employees' health, performance, and mobile application developers.Abbreviations: ANOVA: analysis of variance; DSSQ: dundee stress state questionnaire; ECG: electrocardiographic; EDA: electrodermal activity; EEG: electroencephalographic; HPA: hypothalamus-pituitaryadrenocortical; HR: heart rate; HRV: heart rate variability; LF/HF: low frequency/high frequency; MSDs: musculoskeletal disorders; MWL: mental workload; NN: normal to normal; RMS: root means square; RR: time duration between two successive R peaks; RT: response time; SC: skin conductance; SDNN: standard deviation of normal to normal; SM: social media; TCL: task cognitive level; TPC: task performing condition; WMC: working memory capacity.

Determining the effect of selected mental factors on turnover intention through two modulators - stress and resilience over COVID-19 period

INTRODUCTION

Turnover intention among nurses has risen in an alarming rate since the onset of the pandemic. There are various underlying factors to turnover intention. The present study aims to determine the effect of a number of mental factors on nurses' professional-turnover intention through two modulators of stress and resilience over COVID-19 period.

METHODS

The current cross-sectional study was conducted at three hospitals in Khuzestan Province, southern Iran, during the winter of 2021. To collect the data, given the restrictions in place during COVID-19 period, the web link of electronic self-reported questionnaires (including general health, mental workload, work-family conflict, resilience, job stress, corona fear, and turnover intention) were sent to 350 nurses through e-mail and other social media (WhatsApp and Telegram). Accordingly, they were asked to complete the questionnaire during rest periods within two weeks. Totally, 300 people (85% participation) filled out the questionnaires. Finally, a model was constructed in the Amos software.

RESULTS

The results showed that the four independent parameters of decreasing general health, increasing mental workload, increasing WFCs and fear of COVID-19 can indirectly increase nurses' turnover intention by increasing job stress. Among these variables, the highest indirect effect coefficient on turnover intention was related to the general health parameter (-0.141). The results also demonstrated a negative correlation between job stress and resilience, with lower resilience raising job stress and, consequently, increasing intention to quit the job.

CONCLUSION

Mental factors affecting turnover intension were identified in this study through path analysis. Therefore, it is recommended that the required resilience-enhancing measures to be taken by hospitals and nursing administrations to reduce psychological pressures caused by mentioned variables with the aim of minimizing job-related stress and fostering nurse retention.

Mental workload level assessment based on compounded hysteresis effect

In the domain of neuroergonomics, cognitive workload estimation has taken a significant concern among the researchers. This is because the knowledge gathered from its estimation is useful for distributing tasks among the operators, understanding human capability and intervening operators at times of havoc. Brain signals give a promising prospective for understanding cognitive workload. For this, electroencephalography (EEG) is by far the most efficient modality in interpreting the covert information arising in the brain. The present work explores the feasibility of EEG rhythms for monitoring continuous change occurring in a person's cognitive workload. This continuous monitoring is achieved by graphicallyinterpreting the cumulative effect of changes in EEG rhythms observed in the current instance and the former instance based on the hysteresis effect. In this work, classification is done to predict the data class label using an artificial neural network (ANN) architecture. The proposed model gives a classification accuracy of 98.66%.

Presence and simulator sickness predict the usability of a virtual reality attention task

Attention is the ability to actively process specific information within one's environment over longer periods of time while disregarding other details. Attention is an important process that contributes to overall cognitive performance from performing every day basic tasks to complex work activities. The use of virtual reality (VR) allows study of the attention processes in realistic environments using ecological tasks. To date, research has focused on the efficacy of VR attention tasks in detecting attention impairment, while the impact of the combination of variables such as mental workload, presence and simulator sickness on both self-reported usability and objective attention task performance in immersive VR has not been examined. The current study tested 87 participants on an attention task in a virtual aquarium using a cross-sectional design. The VR task followed the continuous performance test paradigm where participants had to respond to correct targets and ignore non-targets over 18 min. Performance was measured using three outcomes: omission (failing to respond to correct targets), commission errors (incorrect responses to targets) and reaction time to correct targets. Measures of self-reported usability, mental workload, presence and simulator sickness were collected. The results showed that only presence and simulator sickness had a significant impact on usability. For performance outcomes, simulator sickness was significantly and weakly associated with omission errors, but not with reaction time and commission errors. Mental workload and presence did not significantly predict performance. Our results suggest that usability is more likely to be negatively impacted by simulator sickness and lack of presence than performance and that usability and attention performance are linked. They highlight the importance of considering factors such as presence and simulator sickness in attention tasks as these variables can impact usability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10055-023-00782-3.

Workflow interruption and nurses' mental workload in electronic health record tasks: An observational study

BACKGROUND

Workflow interruptions are common in modern work systems. Electronic health record (EHR) tasks are typical tasks involving human-machine interactions in nursing care, but few studies have examined interruptions and nurses' mental workload in the tasks. Therefore, this study aims to investigate how frequent interruptions and multilevel factors affect nurses' mental workload and performance in EHR tasks.

METHODS

A prospective observational study was conducted in a tertiary hospital providing specialist and sub-specialist care from June 1^st to October 31^st, 2021. An observer documented nurses' EHR task interruptions, reactions and performance (errors and near errors) during one-shift observation sessions. Questionnaires were administered at the end of the electronic health record task observation to measure nurses' mental workload for the electronic health record tasks, task difficulty, system usability, professional experience, professional competency, and self-efficacy. Path analysis was used to test a hypothetical model.

RESULTS

In 145 shift observations, 2871 interruptions occurred, and the mean task duration was 84.69 (SD 56.68) minutes per shift. The incidence of error or near error was 158, while 68.35% of errors were self-corrected. The total mean mental workload level was 44.57 (SD 14.08). A path analysis model with adequate fit indices is presented. There was a relationship among concurrent multitasking, task switching and task time. Task time, task difficulty and system usability had direct effects on mental workload. Task performance was influenced by mental workload and professional title. Negative affect mediated the path from task performance to mental workload.

CONCLUSIONS

Nursing interruptions occur frequently in EHR tasks, come from different sources and may lead to elevated mental workload and negative outcomes. By exploring the variables related to mental workload and performance, we offer a new perspective on quality improvement strategies. Reducing harmful interruptions to decrease task time can avoid negative outcomes. Training nurses to cope with interruptions and improve competency in EHR implementation and task operation has the potential to decrease nurses' mental workload and improve task performance. Moreover, improving system usability is beneficial to nurses to mitigate mental workload.

Impeded frontal-occipital communications during Go/Nogo tasks in humans owing to mental workload

Human brains rely on oscillatory coupling mechanisms for regulating access to prefrontal cognitive resources, dynamically communicating between the frontal and remote cortex. We worry that communications across cortical regions will be impeded when humans in extreme space environments travel with mental load work, affecting the successful completion of missions. Here, we monitored crews of workers performing a Go/Nogo task in space travel, accompanied by acquisitions of electroencephalography (EEG) signals. These data demonstrated that when the target stimulus suddenly changed to the non-target stimulus, an instantaneous communication mechanism between the frontal and occipital cortex was established by theta-gamma phase-amplitude coupling (PAC). However, this frontal-occipital communication was impeded because of the mental workload of space travel. 86 healthy volunteers who participated in the ground imitation further indicated that mental workload caused decoupled theta-gamma PAC during the Go/Nogo task, impeding frontal-occipital communications and behavioral performance. We also found that the degree of theta-gamma PAC coupling in space was significantly lower than on the ground, indicating that mental workload and other hazards worsen the impeded frontal-occipital communications of humans. These results could guide countermeasures for the inadaptability of humans working in spaceflight.

Quantitative indicators of street lighting with mood, fatigue, mental workload and sleepiness in car drivers: Using generalized structural equation modeling

Inadequate lighting will be associated with some degree of perceptual error such as sleepiness. The main purpose of this study was to investigate the interactions between mood, fatigue, mental workload, and sleepiness and their relationship with quantitative indicators of street lighting in passenger car drivers. The present study was a cross-sectional study that was performed on 270 drivers of passenger cars. The quantitative indices of lighting studied were illuminance, luminance, uniformity, and disability glare which were calculated using the Hagner device (EC1-L) and according to EN 13201 standard. Alertness and mood indices, fatigue scale (SAMN-PERELLI), mental workload (NASA-TLX), positive and negative affect schedule (PANAS) were used. Generalized structural equation modeling (GSEM) was used to investigate the relationship between mood, fatigue, mental workload, and drivers' sleepiness. Data analysis was performed in version 26 of SPSS software and version 14 of Stata software There is a significant relationship between illuminance and mood (P < 0.001). There is a significant relationship between the degree of disability glare on the streets and the mood (P = 0.006). There is a significant relationship between fatigue score and mood (P < 0.001) so that with increasing one unit in fatigue scale, mood score decreases by 0.669 units (P < 0.001). Finally, it can be assured that lighting interventions can be done as an effective way to increase alertness and reduce fatigue and the mental workload of drivers with the aim of reducing night traffic accidents.

The influence of physical and mental workload on the safe behavior of employees in the automobile industry

This study aimed to investigate the influence of physical and mental workload on safe behavior of employees in the automobile industry. The 150 workers of the two industries of machining and foundry of an automobile parts manufacturer participated in this correlational study. Safety behavior, NASA-TLX, and Borg scale questionnaires were used to collect data. Independent t-test, analysis of variance and Pearson correlation coefficient applied to the analysis of data. The NASA-TLX showed that the dimensions of physical and mental demand had the highest score and the performance had the lowest score. Excessive physical pressure was also reported among workers. The Score of safety observance, safety participation, and safety behavior were at a moderate level. There was a significant difference in the physical workload of employees who had an accident and did not have an accident (P = 0.001). The results showed that if the same mental workload had been imposed on workers and simultaneously more physical workload had been experienced, the probability of an accident increased. The overall mental workload and physical pressure among workers were reported at a high level. Safe behaviors were moderate among employees. Therefore, the implementation of effective intervention programs to adjust workload, participatory ergonomics, provide workload balance to improve job satisfaction, eliminate inappropriate working conditions and increase the number of operators, management programs such as job rotation between Machining and Foundry and other workshops, increase rest time and creation of a strong teamwork safety climate can reduce physical and mental workload and prevent accident among workers, improve their performance and wellbeing.

Identification of human mental workload levels in a language comprehension task with imbalance neurophysiological data

BACKGROUND AND OBJECTIVE

Operator's capability for accurately comprehending verbal commands is critically important to maintain the performance of human-machine interaction. It can be evaluated by human mental workload measured with electroencephalography (EEG). However, the time duration of different workload conditions within a task session is unequal due to varied psychophysiological processes across individuals. It leads to data imbalance of the EEG for training workload classifiers.

METHODS

In this study, we propose an EEG feature oversampling technique, Gaussian-SMOTE based feature ensemble (GSMOTE-FE), for workload recognition with imbalanced classes. First, artificial EEG instances are drawn from a Gaussian distribution in the margin between the minority and majority workload classes. Tomek links are detected as clues to remove redundant feature vectors. Then, we embed a feature selection module based on the GINI importance while an ensemble classifier committee with bootstrap aggregating is used to further enhance classification performance.

RESULTS

We validate the GSMOTE-FE framework based on an experiment that simulates operators to understand the correct meaning of the instructions in the Chinese language. Participants' EEG signals and reaction time data were both recorded to validate the proposed workload classifier. Workload classification accuracy and Macro-F1 values are 0.6553 and 0.5862, respectively. Corresponding G-mean and AUC achieve at 0.5757 and 0.5958, respectively.

CONCLUSIONS

The performance of the GSMOTE-FE is demonstrated to be comparable with the advanced oversampling techniques. The workload classifier has the capability to indicate low and high levels of the task demand of the Chinese language understanding task.

Augmented reality on industrial assembly line: Impact on effectiveness and mental workload

Studies examining the potential of augmented reality (AR) to improve assembly tasks are often unrepresentative of real assembly line conditions and assess mental workload only through subjective measurements and leads to conflicting results. We proposed a study directly carried out in industrial settings, to compare the impact of AR-based instructions to computerized instructions, on assembly effectiveness (completion time and errors) and mental workload using objective (eye tracking), subjective (NASA-TLX) and behavioral measurements (dual task paradigm). According to our results, AR did not improve effectiveness (increased assembly times and no decrease in assembly errors). Two out of three measurements indicated that AR led to more mental workload for simple assembly workstation, but equated computer instructions for complex workstation. Our data also suggest that, AR users were less able to detect external events (danger, alert), which may play an important role in the occurrence of work accidents.

The Measurement of Cognitive Workload in Surgery Using Pupil Metrics: A Systematic Review and Narrative Analysis

INTRODUCTION

Increased cognitive workload (CWL) is a well-established entity that can impair surgical performance and increase the likelihood of surgical error. The use of pupil and gaze tracking data is increasingly being used to measure CWL objectively in surgery. The aim of this review is to summarize and synthesize the existing evidence that surrounds this.

METHODS

A systematic review was undertaken in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A search of OVID MEDLINE, IEEE Xplore, Web of Science, Google Scholar, APA PsychINFO, and EMBASE was conducted for articles published in English between 1990 and January 2021. In total, 6791 articles were screened and 32 full-text articles were selected based on the inclusion criteria. A narrative analysis was undertaken in view of the heterogeneity of studies.

RESULTS

Seventy-eight percent of selected studies were deemed high quality. The most frequent surgical environment and task studied was surgical simulation (75%) and performance of laparoscopic skills (56%) respectively. The results demonstrated that the current literature can be broadly categorized into pupil, blink, and gaze metrics used in the assessment of CWL. These can be further categorized according to their use in the context of CWL: (1) direct measurement of CWL (n = 16), (2) determination of expertise level (n = 14), and (3) predictors of performance (n = 2).

CONCLUSIONS

Eye-tracking data provide a wealth of information; however, there is marked study heterogeneity. Pupil diameter and gaze entropy demonstrate promise in CWL assessment. Future work will entail the use of artificial intelligence in the form of deep learning and the use of a multisensor platform to accurately measure CWL.

Cognitive performance and electroencephalographic variations in air traffic controllers under various mental workload and time of day

The aim of this study was to investigate the effects of mental workload (MWL) and time of day on cognitive performance and electroencephalographic (EEG) parameters of air traffic controllers. EEG signals recorded while 20 professional air traffic controllers performed cognitive tasks [A-X Continuous Performance Test (AX-CPT) and 3-back working memory task] after they were exposed to two levels of task difficulty (high and low MWL) in the morning and afternoon. Significant decreases in cognitive performance were found when the levels of task difficulty increased in both tasks. The results confirmed the sensitivity of the theta and beta activities to levels of task difficulty in the 3-back task, while they were not affected in the AX-CPT. Theta and beta activities were influenced by time of day in the AX-CPT. The findings provide guidance for application of changes in EEG parameters when MWL level is manipulated during the day that could be implemented in future for the development of real-time monitoring systems to improve aviation safety.

Using IoT devices for sensor-based monitoring of employees' mental workload: Investigating managers' expectations and concerns

Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers' willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.

A field study of mental workload: conventional bus drivers versus bus rapid transit drivers

Road traffic accidents are increasing worldwide and cause a high number of fatalities and injuries. Mental Work Load (MWL) is a contributing factor in road safety. The primary aim of this work was to study important MWL factors and then compare conventional and BRT (Bus Rapid Transit) drivers' MWL. This study evaluated bus drivers' MWL using the Driving Activity Load Index (DALI) questionnaire conducted with 123 bus drivers in Tehran. The results revealed significant differences between conventional and BRT drivers' mental workload. Moreover, data modelling showed that some organisational and environmental factors such as bus type, working hours per day, road maze, and route traffic volume contribute to drivers' mental workload. These findings suggest some essential customised factors that may help measure and offer practical solutions for decreasing the level of bus drivers' MWL in real-world road driving. Practitioner summaryMental workload is affected by several contributing factors. Depending on the working context, some of these contributing factors have a more significant influence on the level of the experienced MWL. Therefore, the main factors influencing the MWL of BRT and conventional bus drivers were assessed in their real-life environment.Abbreviations: MWL: mental work load; BRT: bus rapid transit; CB: conventional bus; DALI: driving activity load index; NASA-TLX: NASA task load index; SWAT: subjective workload assessment technique; EEG: electroencephalography electrocardiogram; fNIRS: functional magnetic resonance imaging; ITS: intelligent transportation systems; AVL: automated vehicle location.

Investigation of electroencephalography variations of mental workload in the exposure of the psychoacoustic in both male and female groups

Most studies have examined the effect of the physical aspects of noise while the effect of exposure to psychoacoustic parameters at different task difficulty levels has been less evaluated. Therefore, this study was performed with the aim of investigating the brainwave in the face of psychoacoustic and the change of difficulty level of task. 120 persons were exposed to 16 psychoacoustic parameters (loudness, sharpness, roughness and fluctuation strength). Each person was asked to complete the three N-Back task difficulty levels. At the same time, brain waves were recorded and the subject completed the NASA-TLX questionnaire. Finally, brain indices including alpha1, alpha2, PrTeta, PrAlpha and EI were examined. With increasing loudness, sharpness and fluctuation, the alpha-1 and alpha-2 index (mental fatigue (increased. Loudness and roughness also increased the PrTeta and PrAlpha (annoyance). For the EI (Engagement Index), increasing fluctuation caused a decrease in the level of consciousness and engagement. In addition, exposure to psychoacoustic parameters at high and medium difficulty levels caused a greater effect on alpha, alpha2, PrTeta and PrAlpha indices. High level of difficulty task reduce the accuracy rate and increase the reaction time to stimuli in the N-Back task, and increase the mean of dimensions of the NASA-TLX questionnaire in the exposure of all psychoacoustic aspect.With increasing loudness, sharpness and fluctuation, the alpha-1 and alpha-2 index (mental fatigue (increased. Loudness and roughness also increased the PrTeta and PrAlpha (annoyance). For the EI (Engagement Index), increasing fluctuation caused a decrease in the level of consciousness and engagement. In addition, exposure to psychoacoustic parameters at high and medium difficulty levels caused a greater effect on alpha, alpha2, PrTeta and PrAlpha indices. High level of difficulty task reduce the accuracy rate and increase the reaction time to stimuli in the N-Back task, and increase the mean of dimensions of the NASA-TLX questionnaire in the exposure of all psychoacoustic aspect. Considering the effect of psychoacoustic at different levels of task difficulty on the mental load and cognitive function is essential to prevent damage to the person and his performance.

Investigation of the optimal time interval between task-irrelevant auditory probes for evaluating mental workload in the shortest possible time

Event-related brain potentials (ERPs) elicited by auditory stimuli unrelated to a current visual-cognitive task (i.e., task-irrelevant auditory probes) can be used to evaluate the level of mental workload. Towards the evaluation of workload in the shortest possible time, the present study with a multiple-stimulus paradigm (Takeda and Kimura, 2014, Int. J. Psychophysiol.) examined whether manipulating time intervals between probes could improve the temporal resolution in evaluating workload. Probes were presented in four interval conditions as a combination of two mean interval lengths [long (600 ms) vs. short (300 ms)] and two interval variabilities [variable (five levels) vs. fixed], while participants were performing a driving game at slow and fast speeds (i.e., imposing low and high workload, respectively). For each interval condition, the minimum data length required to obtain a significant difference in the amplitude of ERPs (i.e., auditory N1 and P2) between the slow and fast driving tasks was estimated. The N1 difference was significant in all four interval conditions but the required minimum data lengths to observe this difference did not greatly differ across the interval conditions (about 60-90 s). The P2 difference was significant only in the long-variable condition and the required minimum data length was about 120 s. These results suggest that, at least with a multiple-stimulus paradigm, manipulations of time intervals between probes did not greatly improve the temporal resolution in evaluating mental workload; at present, long-variable intervals would be optimal for evaluating mental workload in detail.

Assessment of the mental workload of trainee pilots of remotely operated aircraft using functional near-infrared spectroscopy

Background

Operating an aircraft is associated with a large mental workload; however, knowledge of the mental workload of ROV operators is limited. The purpose of this study was to establish a digital system for assessing the mental workload of remotely operated vehicle (ROV) operators using hemodynamic parameters, and compare results of different groups with different experience levels.

Method

Forty-one trainee pilots performed flight tasks once daily for 5 consecutive days in a flight simulation. Forty-five pilots experienced pilots and 68 experienced drivers were also included. Hemodynamic responses were measured by functional near-infrared spectroscopy (fNIRS).

Results

The median duration of peak oxyhemoglobin was 147.13 s (interquartile range [IQR] 21.97, 401.70 s) in the left brain and 180.74 s (IQR 34.37, 432.01 s) in the right brain in the experienced pilot group, and 184.42 s (IQR 3.41, 451.81 s) on day 5 in the left brain and 160.30 s (IQR 2.62, 528.20 s) in the right brain in the trainee group.

Conclusion

Navigation training reduces peak oxyhemoglobin duration, and may potentially be used as a surrogate marker for mental workload of ROV operators. Peak oxyhemoglobin concentration during s task may allow development of a simplified scheme for optimizing flight performance based on the mental workload of a pilot.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02683-5.

[Design and validation of a computer-based task for the induction of a mental workload spectrum]

As part of the driver's cab 4.0 project funded by the BMBF, an adaptive human-machine interface for agricultural machinery, which detects the current level of mental workload by analysing physiological data is being developed. For this purpose, an experimental task is designed and evaluated, which can induce a mental workload spectrum from little to very strenuous in humans. In three laboratory studies, mental workload is generated by a monitoring activity, with varying difficulty levels. The complexity of the activity is increased by a visual and/or an auditory secondary task. Subjectively perceived mental workload is evaluated by using the Rating Scale Mental Effort, collecting reaction times and error rates. The studies with N = 17, N = 8 and N = 21 participants show that a dynamic combination of main and secondary tasks can induce significantly different degrees of workload (F (2.40) = 54,834, p < 0.001).Practical Relevance: The experimental task developed in this paper will be used to design a measuring system for mental workload based on physiological indicators for combine harvesters. In low-workload situations (e.g. automated harvesting) additional recommendations for action should be proposed by the system. During high workload sections excessive demands on the user should be avoided by only showing the information necessary to carry out the task at hand.

Optimized electroencephalogram and functional near-infrared spectroscopy-based mental workload detection method for practical applications

Background

Mental workload is a critical consideration in complex man–machine systems design. Among various mental workload detection techniques, multimodal detection techniques integrating electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals have attracted considerable attention. However, existing EEG–fNIRS-based mental workload detection methods have certain defects, such as complex signal acquisition channels and low detection accuracy, which restrict their practical application.

Methods

The signal acquisition configuration was optimized by analyzing the feature importance in mental workload recognition model and a more accurate and convenient EEG–fNIRS-based mental workload detection method was constructed. A classical Multi-Task Attribute Battery (MATB) task was conducted with 20 participating volunteers. Subjective scale data, 64-channel EEG data, and two-channel fNIRS data were collected.

Results

A higher number of EEG channels correspond to higher detection accuracy. However, there is no obvious improvement in accuracy once the number of EEG channels reaches 26, with a four-level mental workload detection accuracy of 76.25 ± 5.21%. Partial results of physiological analysis verify the results of previous studies, such as that the θ power of EEG and concentration of O₂Hb in the prefrontal region increase while the concentration of HHb decreases with task difficulty. It was further observed, for the first time, that the energy of each band of EEG signals was significantly different in the occipital lobe region, and the power of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta_{1}$$\end{document}β1 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta_{2}$$\end{document}β2 bands in the occipital region increased significantly with task difficulty. The changing range and the mean amplitude of O₂Hb in high-difficulty tasks were significantly higher compared with those in low-difficulty tasks.

Conclusions

The channel configuration of EEG–fNIRS-based mental workload detection was optimized to 26 EEG channels and two frontal fNIRS channels. A four-level mental workload detection accuracy of 76.25 ± 5.21% was obtained, which is higher than previously reported results. The proposed configuration can promote the application of mental workload detection technology in military, driving, and other complex human–computer interaction systems.

Effects of noise and music on situation awareness, anxiety, and the mental workload of nurses during operations

This study aims to explore the effects of noise and music types on nurses' anxiety, mental workload and situation awareness during an operation. Participants included 20 circulating nurses (CNs) and 16 nurse anesthetists (NAs) who completed a total of 70 operations in which each operation required one CN and one NA. The experiment was separated into a control group (operating noise only) vs. an experimental group (3 different music types-between subjects and 2 music volume levels-within-subjects). Results showed that all participants had excellent situation awareness performance despite their mental workload showing significant differences in various phases of the surgery. Music at 55-60 dB caused lower mental workloads and anxiousness for nurses than those exposed to levels of 75-80 dB. When Mozart's music was played, the participants' mental workload and situation anxiety were lower than when exposed to other music types. Music played at 60 dB during an operation may be a feasible solution to mitigate the negative effects of extra noise and thus improve the nurses' performance.

Measuring mental workload in assistive wearable devices: a review

As wearable assistive devices, such as prostheses and exoskeletons, become increasingly sophisticated and effective, the mental workload associated with their use remains high and becomes a major challenge to their ecological use and long-term adoption. Numerous methods of measuring mental workload co-exist, making analysis of this research topic difficult. The aim of this review is to examine how mental workload resulting from the use of wearable assistive devices has been measured, in order to gain insight into the specific possibilities and limitations of this field. Literature searches were conducted in the main scientific databases and 60 articles measuring the mental workload induced by the use of a wearable assistive device were included in this study. Three main families of methods were identified, the most common being 'dual task' and 'subjective assessment' methods, followed by those based on 'physiological measures', which included a wide variety of methods. The variability of the measurements was particularly high, making comparison difficult. There is as yet no evidence that any particular method of measuring mental workload is more appropriate to the field of wearable assistive devices. Each method has intrinsic limitations such as subjectivity, imprecision, robustness or complexity of implementation or interpretation. A promising metric seems to be the measurement of brain activity, as it is the only method that is directly related to mental workload. Finally, regardless of the measurement method chosen, special attention should be paid to the measurement of mental workload in the context of wearable assistive devices. In particular, certain practical considerations, such as ecological situations and environments or the level of expertise of the participants tested, may be essential to ensure the validity of the mental workload assessed.

The Cognitive Relevance of a Formal Pre-incision Time-out in Surgery

Surgical time-outs are designed to promote situation awareness, teamwork, and error prevention. The pre-incision time-out in particular aims to facilitate shared mental models prior to incision. Objective, unbiased measures to confirm its effectiveness are lacking. We hypothesized that providers’ mental workload would reveal team psychophysiological mirroring during a formal, well-executed pre-incision time-out. Heart rate variability was collected during cardiac surgery cases from the surgeon, anesthesiologist, and perfusionist. Data were analyzed for six cases from patient arrival until sternal closure. Annotation of surgical phases was completed according to previously developed standardized process models of aortic valve replacement and coronary artery bypass graft procedures, producing thirteen total surgical phases. Statistical analysis revealed significant main effects. Tukey HSD post hoc tests revealed significant differences across provider roles within various phases, including Anesthesia Induction, Heparinization, Initiation of Bypass, Aortic Clamp and Cardioplegia, Anastomoses or Aortotomy, Separation from Bypass, and Sternal Closure. Despite these observed differences between providers over various surgical phases, the Pre-incision Time-out phase revealed almost negligible differences across roles. This preliminary work supports the utility of the pre-incision safety checklist to focus the attention of surgical team members and promote shared team mental models, measured via psychophysiological mirroring, using an objective mental workload measure. Future studies should investigate the relationship between psychophysiological mirroring among surgical team members and the effectiveness of the pre-incision time-out checklist.

Subtypes of nurses' mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

BACKGROUND

Nurses play critical roles when providing health care in high-risk situations, such as during the COVID-19 outbreak. However, no previous study had systematically assessed nurses' mental workloads and its interaction patterns with fatigue, work engagement and COVID-19 exposure risk.

METHODS

A cross-sectional study was conducted via online questionnaire. The NASA Task Load Index, Fatigue Scale-14, and Utrecht Work Engagement Scale were used to assess nurses' mental workload, fatigue and work engagement, respectively. A total of 1337 valid questionnaires were received and analyzed. Nurses were categorized into different subgroups of mental workload via latent class analysis (LCA). Cross-sectional comparisons, analysis of covariance (ANCOVA), and multivariate (or logistic) regression were subsequently performed to examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups.

RESULTS

Three latent classes were identified based on the responses to mental workload assessment: Class 1 - low workload perception & high self-evaluation group (n = 41, 3.1%); Class 2 - medium workload perception & medium self-evaluation group (n = 455, 34.0%); and Class 3 - high workload perception & low self-evaluation group (n = 841, `62.9%). Nurses belonging into class 3 were most likely to be older and have longer professional years, and displayed higher scores of fatigue and work engagement compared with the other latent classes (p < 0.05). Multivariate analysis showed that high cognitive workload increased subjective fatigue, and mental workload may be positively associated with work engagement. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels.

CONCLUSIONS

The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses' perceived workload, as well as their physical fatigue, work engagement and personal safety when working in public health emergencies.

Understanding fatigue in a naval submarine: Applying biomathematical models and workload measurement in an intensive longitudinal design

Fatigue is a critically important aspect of crew endurance in submarine operations, with continuously high fatigue being associated with increased risk of human error and long-term negative health ramifications. Submarines pose several unique challenges to fatigue mitigation, including requirements for continuous manning for long durations, a lack of access to critical environmental zeitgebers (stimuli pertinent to circadian physiology; e.g., natural sunlight), and work, rest and sleep occurring within an encapsulated environment. In this paper, we examine the factors that underlie fatigue in such a context with the aim of evaluating the predictive utility of a biomathematical model (BMM) of fatigue. Three experience sampling studies were conducted with submarine crews using a participant-led measurement protocol that included assessments of subjective sleepiness, workload (NASA-Task Load Index [TLX] and a bespoke underload-overload scale), and sleep. As expected, results indicated that predicting KSS with a BMM approach outperformed more conventional linear modelling approaches (e.g., time-of-day, sleep duration, time awake). Both the homeostatic and circadian components of the BMM were significantly associated with KSS and used as controls in the workload models. We found increased NASA-TLX workload was significantly associated with increased average KSS ratings at the between-person level. However, counter to expectations, the two workload measures were not found to have significant linear or quadratic relationship with fatigue at the within-person level. An important outcome of the research is that applied fatigue researchers should be extremely cautious applying conventional linear predictors when predicting fatigue. Practical implications for the submarine and related extreme work context are discussed. Important avenues for continued research are outlined, including directly estimating BMM parameters.

Reference values and subscale patterns for the task load index (TLX): a meta-analytic review

The Task Load Index (TLX) is the predominant instrument for self-reporting workload. On the basis of a meta-analytic review of 556 studies, this paper supplies reference values for TLX and its six subscales across domains, technologies, regions, and real-life/lab settings. Across domains, TLX spans mean values from 35 for leisure to 56 for manual labour. TLX tends to be driven upward by the subscales of mental demand and effort and downward by the subscales of physical demand and frustration. For technologies, handheld devices are associated with lower TLX, possibly because they are simpler and more task-specific. TLX also varies across regions in that it is higher for studies in Asia than in Europe and North America. This variation is only partly explained by co-variation in domains. Furthermore, TLX is higher and its subscales more inter-correlated when it is studied in real-life rather than lab settings. Practitioner summary: Practitioners can use the reference values supplied in this paper to benchmark their TLX measurements against those from the corpus of TLX research. Furthermore, the reported subscale patterns add to the diagnostic power of the TLX instrument. Abbreviations: TLX: task load index; MD: mental demand; PD: physical demand; TD: temporal demand; EF: effort; PE: performance; FR: frustration.

A review of augmented reality systems and their effects on mental workload and task performance

Augmented Reality (AR) systems have been shown to positively affect mental workload and task performance across a broad range of application contexts. Despite the interest in mental workload and the increasing number of studies evaluating AR use, an attempt has yet to be made to identify the relationship between the effects of AR on mental workload and task performance. This paper seeks to address this gap in AR technology literature. With a better understanding how AR affects mental workload and task performance, researchers and developers can design more effective AR systems. 34 articles investigating the effects of the use of AR systems were selected for the review. A positive correlation was found between effects on mental workload and effects on task performance: if the effect on mental workload is positive, then the effects on task performance are more likely to be positive as well, and vice versa. Effectiveness of AR systems were shown to be influenced by the type of AR display device used, relevance and timeliness of content, information presentation, user characteristics and task characteristics. Additionally, the paper addresses the use of the concept of mental workload and limitations in current literature.

Cardiovascular Biomarkers' Inherent Timescales in Mental Workload Assessment During Simulated Air Traffic Control Tasks

One central topic in ergonomics and human-factors research is the assessment of mental workload. Heart rate and heart rate variability are common for registering mental workload. However, a major problem of workload assessment is the dissociation among different workload measures. One potential reason could be the disregard of their inherent timescales and the interrelation between participants' individual differences and timescales. The aim of our study was to determine if different cardiovascular biomarkers exhibit different timescales. We focused on air traffic controller and investigated biomarkers' ability to distinguish between conditions with different load levels connected to prior work experience and different time slots. During an interactive real-time simulation, we varied the load situations with two independent variables: the traffic volume and the occurrence of a priority-flight request. Dependent variables for registering mental workload were the heart rate and heart rate variability from two time slots. Our results show that all cardiovascular biomarkers were sensitive to workload differences with different inherent timescales. The heart rate responded sooner than the heart rate variability features from the frequency domain and it was most indicative during the time slot immediately after the priority-flight request. The heart rate variability parameters from the frequency domain responded with latency and were most indicative during the subsequent time slot. Furthermore, by consideration of biomarkers' inherent timescales, we were able to assess a significant effect of work experience on heart rate and mid/high frequency-band ratio of the heart rate variability. Results indicated that different cardiovascular biomarkers reveal different inherent timescales.

Development and validation of a behavioural video coding scheme for detecting mental workload in manual assembly

Manual assembly in the future Industry 4.0 workplace will put high demands on operators' cognitive processing. The development of mental workload (MWL) measures therefore looms large. Physiological gauges such as electroencephalography (EEG) show promising possibilities, but still lack sufficient reliability when applied in the field. This study presents an alternative measure with a substantial ecological validity. First, we developed a behavioural video coding scheme identifying 11 assembly behaviours potentially revealing MWL being too high. Subsequently, we explored its validity by analysing videos of 24 participants performing a high and a low complexity assembly. Results showed that five of the behaviours identified, such as freezing and the amount of part rotations, significantly differed in occurrence and/or duration between the two conditions. The study hereby proposes a novel and naturalistic method that could help practitioners to map and redesign critical assembly phases, and researchers to enrich validation of MWL-measures through measurement triangulation. Practitioner summary: Current physiological mental workload (MWL) measures still lack sufficient reliability when applied in the field. Therefore, we identified several observable assembly behaviours that could reveal MWL being too high. The results propose a method to map MWL by observing specific assembly behaviours such as freezing and rotating parts. Abbreviations: MWL: mental workload; EEG: electroencephalography; fNIRS: functional near infrared spectroscopy; AOI: area of interest; SMI: SensoMotoric Instruments, ETG: Eye-Tracking Glasses; FPS: frames per second; BORIS: Behavioral Observation Research Interactive Software; IRR: inter-rater reliability; SWAT: Subjective Workload Assessment Technique; NASA-TLX: National Aeronautics and Space Administration Task Load Index; EL: emotional load; DSSQ: Dundee Stress State Questionnaire; PHL: physical load; SBO: Strategisch Basis Onderzoek.

Cognitive load theory: Implications for assessment in pharmacy education

The concept of mental workload is well studied from a learner's perspective but has yet to be better understood from the perspective of an assessor. Mental workload is largely associated with cognitive load theory, which describes three different types of load. Intrinsic load deals with the complexity of the task, extraneous load describes distractors to the task at hand, and germane load focuses on the development of schemas in working memory for future recall. Studies from medical education show that all three types of load are relevant when considering rater -based assessment (e.g. Objective Structured Clinical Examinations (OSCEs), or experiential training). Assessments with high intrinsic and extraneous load may interfere with assessors' attention and working memory and result in poorer quality assessment. Reducing these loads within assessment tasks should therefore be a priority for pharmacy educators. This commentary aims to provide a theoretical overview of mental workload in assessment, outline research findings from the medical education context, and propose strategies to be considered for reducing mental workload in rater-based assessments relevant to pharmacy education. Suggestions for future research are also addressed.

[Investigation of mental workload and related factors among nurses from tertiary hospitals in Shandong]

Objective: To investigate mental workload among nurses from tertiary hospitals in Shandong Province, and analyze various factors related to mental workload. Methods: From May to July 2019, a cluster sampling method was used to select 8255 nurses from 20 third class a general hospitals in 16 cities of Shandong Province as the research objects, and 8159 valid questionnaires were collected. The general information and psychological load of nurses were investigated by general information questionnaire and task load index scale. The measurement data were expressed in percentage (%) ; the nurses' psychological load scores were in accordance with normal distribution, and the differences between groups were compared by t-test or ANOVA; the related influencing factors of nurses' psychological load were analyzed by multiple stepwise regression analysis. Results: The average scores of mental workload among nurses was 77.83 (SD=12.88) . Time demands and physical demands were the two highest rated dimensions of mental workload. the average scores were 90.77 (SD=12.47) and 79.92 (SD=15.23) . Multiple stepwise regression analysis showed that Satisfaction with income, monthly average night shift and professional titles were the significant predictors of mental workload (R(2)=0.08) . Conclusion: Nurses with higher psychological load, lower income satisfaction, higher number of night shifts per month and lower title have higher psychological load.

[Fatigue and mental workload among workers: about social distancing.]

BACKGROUND

Covid-19 is a latent threat; a sector of the population with a labor obligation carries out its work not in person in an unplanned context due to the extraordinary social distancing expressed in remote work, without previous experience in many cases and with health exposure due to psychosocial risk factors conditioning stress. Our objective was to describe the fatigue and mental burden in teleworkers through a bibliographic review, of interest for occupational health, public health, clinical research, psychology and other areas of knowledge. We also intend to inform the community about these issues to promote safe telework and ensure a balanced quality of life.

METHODS

Structured information on the topics of fatigue and mental load was presented, based on the analysis of international literature, mainly from recent years, obtained from the search engine reviews of scientific publications Ebsco, PubMed, and supplemented with Google Scholar, according to recognized thesauri, in English and Spanish.

RESULTS

There are also psychosocial risks in teleworking; work-related stress can be linked to fatigue, which should also be addressed as a psychosocial risk. Fatigue, although multi-causal, can be occupational in origin and may be conditioned by various aspects of labour, such as the mental workload, which is pernicious at its extremes.

CONCLUSIONS

We conclude that both fatigue and mental workload must be watched, their extremes threaten the quality of work life.