Influence of Increasing Task Complexity and Use of Informational Assistance Systems on Mental Workload

Workplace Well-Being in Industry 5.0: A Worker-Centered Systematic Review

The paradigm of Industry 5.0 pushes the transition from the traditional to a novel, smart, digital, and connected industry, where well-being is key to enhance productivity, optimize man-machine interaction and guarantee workers' safety. This work aims to conduct a systematic review of current methodologies for monitoring and analyzing physical and cognitive ergonomics. Three research questions are addressed: (1) which technologies are used to assess the physical and cognitive well-being of workers in the workplace, (2) how the acquired data are processed, and (3) what purpose this well-being is evaluated for. This way, individual factors within the holistic assessment of worker well-being are highlighted, and information is provided synthetically. The analysis was conducted following the PRISMA 2020 statement guidelines. From the sixty-five articles collected, the most adopted (1) technological solutions, (2) parameters, and (3) data analysis and processing were identified. Wearable inertial measurement units and RGB-D cameras are the most prevalent devices used for physical monitoring; in the cognitive ergonomics, and cardiac activity is the most adopted physiological parameter. Furthermore, insights on practical issues and future developments are provided. Future research should focus on developing multi-modal systems that combine these aspects with particular emphasis on their practical application in real industrial settings.

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.

On the potential of pupil size as a metric of physical fatigue during a repeated handle push/pull task

Force output and muscle activity represent the gold standards for measuring physical fatigue. This study explores using ocular metrics for tracking changes in physical fatigue during the completion of a repeated handle push/pull task. Participants completed this task over three trials, and pupil size was recorded by means of a head-mounted eye-tracker. Blink frequency was also measured. Force impulse and maximum peak force were used as ground-truth measures of physical fatigue. As expected, a reduction in peak force and impulse was observed over time as participants became more fatigued. More interestingly, pupil size was also found to decrease from trial 1 through trial 3. No changes in blink rate were found with increasing physical fatigue. While exploratory in nature, these findings add to the sparse literature exploring the use of ocular metrics in Ergonomics. They also advance the use of pupil size as a possible future alternative for physical fatigue detection.

Protocol for a scoping review on 'surgical sabermetrics:' technology-enhanced measurement of operative non-technical skills

INTRODUCTION

Surgeons need high fidelity, high quality, objective, non-judgemental and quantitative feedback to measure their performance in order to optimise their performance and improve patient safety. This can be provided through surgical sabermetrics, defined as 'advanced analytics of digitally recorded surgical training and operative procedures to enhance insight, support professional development and optimise clinical and safety outcomes'. The aim of this scoping review is to investigate the assessment of surgeon's non-technical skills using sabermetrics principles, focusing on digital, automated measurements that do not require a human observer.

METHODS AND ANALYSIS

To investigate the current methods of digital, automated measurements of surgeons' non-technical skills, a systematic scoping review will be conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, using databases from medicine and other fields. Covidence software is used for screening of potential studies. A data extraction tool will be developed specifically for this study to evaluate the methods of measurement. Quality assurance will be assessed using Quality Assessment Tool for Diverse Designs. Multiple reviewers will be responsible for screening of studies and data extraction.

ETHICS AND DISSEMINATION

This is a review study, not using primary data, and therefore, ethical approval is not required. A range of methods will be employed for dissemination of the results of this study, including publication in journals and conference presentations.

Cognitive Analyses for Interface Design Using Dual N-Back Tasks for Mental Workload (MWL) Evaluation

In the manufacturing environments of today, human-machine systems are constituted with complex and advanced technology, which demands workers' considerable mental workload. This work aims to design and evaluate a Graphical User Interface developed to induce mental workload based on Dual N-Back tasks for further analysis of human performance. This study's contribution lies in developing proper cognitive analyses of the graphical user interface, identifying human error when the Dual N-Back tasks are presented in an interface, and seeking better user-system interaction. Hierarchical task analysis and the Task Analysis Method for Error Identification were used for the cognitive analysis. Ten subjects participated voluntarily in the study, answering the NASA-TLX questionnaire at the end of the task. The NASA-TLX results determined the subjective participants' mental workload proving that the subjects were induced to different levels of mental workload (Low, Medium, and High) based on the ANOVA statistical results using the mean scores obtained and cognitive analysis identified redesign opportunities for graphical user interface improvement.

Systems Neuroscience 2021 Top Papers: An Editorial Summary

Many years ago, before the Internet and the introduction of the electronic publications, bibliographical research was conducted in physical libraries, and the most commonly used source of information was the regularly updated Index Medicus, a multi-volume treatise that for 125 years summarized and indexed all published medical literature, classifying it by keywords and subject headings [...].

Information assistance systems as preventive mediators between increasing customization and mental workload

BACKGROUND: The future of work in Germany is shaped by megatrends like globalization, automatization, digitization, and the demographic change. Furthermore, mass customization and the increasing usage of AI even in manual assembly offers new opportunities as well as it creates new challenges. OBJECTIVE: The trend towards mass customization in turn leads to increased complexity in production, which results in additional mental workload. This effect will continue in the foreseeable future. METHOD: Especially for small and medium sized companies, the backbone of Germany’s economy, automatization and Human-Robot-Collaboration will take time to develop. Information assistance systems are and will be a bridging technology to help organizations to manage increasing complexity and the mental workload of their employees to not only boost productivity but also keep their workforce healthy. The ongoing demographic change further underlines the need to use information assistance systems to compensate possible age-associated deficits, but also keep older employees committed to their work and avoid effects of disengagement or disenfranchisement through participatory ergonomics. RESULTS: Information assistance systems can only develop their inherent potential if they are designed to support employees of varying age, competence levels, and affinity for technology. Participatory development and early engagement are key factors for an increased acceptance and usage of the systems as well as the individualization to make it suitable for each individual employee. CONCLUSION: Expanding the functionalities to an adaptive assistance system, using physiological correlates of mental workload as an input, is conceivable in the future.

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.

Robust Assembly Assistance Using Informed Tree Search with Markov Chains

Manual work accounts for one of the largest workgroups in the European manufacturing sector, and improving the training capacity, quality, and speed brings significant competitive benefits to companies. In this context, this paper presents an informed tree search on top of a Markov chain that suggests possible next assembly steps as a key component of an innovative assembly training station for manual operations. The goal of the next step suggestions is to provide support to inexperienced workers or to assist experienced workers by providing choices for the next assembly step in an automated manner without the involvement of a human trainer on site. Data stemming from 179 experiment participants, 111 factory workers, and 68 students, were used to evaluate different prediction methods. From our analysis, Markov chains fail in new scenarios and, therefore, by using an informed tree search to predict the possible next assembly step in such situations, the prediction capability of the hybrid algorithm increases significantly while providing robust solutions to unseen scenarios. The proposed method proved to be the most efficient for next assembly step prediction among all the evaluated predictors and, thus, the most suitable method for an adaptive assembly support system such as for manual operations in industry.

Cognitive Interaction Analysis in Human–Robot Collaboration Using an Assembly Task

In human–robot collaborative assembly tasks, it is necessary to properly balance skills to maximize productivity. Human operators can contribute with their abilities in dexterous manipulation, reasoning and problem solving, but a bounded workload (cognitive, physical, and timing) should be assigned for the task. Collaborative robots can provide accurate, quick and precise physical work skills, but they have constrained cognitive interaction capacity and low dexterous ability. In this work, an experimental setup is introduced in the form of a laboratory case study in which the task performance of the human–robot team and the mental workload of the humans are analyzed for an assembly task. We demonstrate that an operator working on a main high-demanding cognitive task can also comply with a secondary task (assembly) mainly developed for a robot asking for some cognitive and dexterous human capacities producing a very low impact on the primary task. In this form, skills are well balanced, and the operator is satisfied with the working conditions.