Ergonomics最新文献

Practitioner summary: This study reveals that individuals' affinity for smart tools is linked to specific brain structures. These findings support the theory of Human-Technology Symbiosis and highlight how technology use is associated with brain anatomy, with implications for technology design and user training.

This study examined how three non-optimal driving states - mind-wandering, distraction, and fatigue - differentially affect driving behaviour and psychophysiological responses from an arousal-resource regulation perspective. Thirty-licenced drivers completed repeated simulated driving tasks, during which behavioural performance and physiological indicators were recorded. Distinct state-specific profiles emerged. Distraction was associated with elevated heart rate and pupil diameter, accompanied by frequent and unstable control adjustments, reflecting a high-arousal, high-load control mode. Fatigue was characterised by reduced heart rate and eyelid opening, prolonged response times, and diminished operational activity, indicating hypoarousal and inhibited control. Mind-wandering showed an intermediate pattern, with moderate physiological activation but unstable behavioural rhythms, suggesting reduced task engagement rather than extreme arousal modulation. These findings indicate that attentional disruptions impair driving stability through distinct arousal- and resource-related mechanisms. The integration of behavioural and physiological measures supports a multimodal approach to driver state assessment.

Understanding human adaptations under varying scenarios is a critical concern from the earliest stages of system design. This study develops within the context of Advanced Air Mobility (AAM) and examines human performance variability during simulated drone operations using the Event Analysis of Systemic Teamwork (EAST) method. The analysis focuses on bird strike events that each of the five participating teams unexpectedly faced during simulated training scenarios. First, Work-As-Instructed (WAIn) EAST networks were constructed based on available Standard Operating Procedures (SOPs) to be trained. These were subsequently compared to Work-As-Trained (WAT) networks developed based on communication logs and transcribed audio recordings from training sessions. The comparative analysis reveals both adaptive behavioural observed tendencies and discrepancies in task-knowledge-agent couplings, visualised via a newly developed joint cognitive network variability matrix. The findings highlight the value of capturing trainee behaviours in terms of task, knowledge, and social interactions while using emerging technologies.

Work-related musculoskeletal disorders are common in surgery due to sustained non-neutral postures. This study evaluated two wearable vibrotactile feedback methods designed to encourage real-time postural correction: one based on standard Rapid Upper Limb Assessment (RULA) thresholds, and another enhanced with Exposure Variation Analysis (EVA) to account for cumulative posture risk. Thirty participants completed a simulated surgical fine motor task under three conditions: control, RULA-based feedback, and EVA-based feedback. EVA-based feedback reduced time spent in high-risk RULA 5-6 postures by 91.5%, compared to 68.5% with RULA-based feedback when normalised by task duration. EVA-based feedback also required fewer cues on average (4.63 ± 2.13 vs. 10.37 ± 13.92). Both feedback methods significantly reduced mean RULA Category scores without increasing task time or cognitive workload. These findings support EVA-based feedback as a low-disruption, real-time ergonomic intervention that improves posture while minimising alert burden in precision-intensive environments.

Practitioner summary: This study shows how DTs can enhance ergonomics in automotive assembly by moving from prevention to adaptive, personalised solutions. The four models identified help practitioners reduce musculoskeletal risks, support flexible task design, and advance human-robot collaboration towards safer, Industry 5.0-ready manufacturing.

Paramedics face a challenging work environment with a high risk of musculoskeletal disorders (MSD). This study examined the prevalence of musculoskeletal pain and its associations with self-reported individual, physical, and psychosocial risk factors among 334 paramedics in Quebec. Data were collected through self-administered questionnaires and analysed using multiple logistic regressions. Results showed that 69% of participants reported musculoskeletal pain in the past 12 months, most commonly in the back, shoulders, and neck. Tasks involving hand movements above shoulder level and working with a twisted back were significantly associated with increased pain, particularly in the lower back. Psychosocial factors, such as low reward, were associated with neck pain.

This article concerns the importance of human values in designing and deploying sociotechnical systems. These values relate to what the system delivers versus what users expect regarding equality, democracy, or quality of work. We explore how the value system (ideology) influences stakeholders' decisions when designing the technical and social dimensions of a system in which they are involved. We focus on the thinking and reasoning processes involved in co-design situations. Through the case of a community system, we closely analyse the verbal interactions during a two-day meeting involving 9 to 12 participants. We illustrate how community ideology plays a central role in reconfiguring the system 'in action', highlighting the misunderstandings and conflicts that arise during the design process and the strategies employed by the participants to advance the project. The findings suggest that examining co-design activities can enhance our understanding of ideology's impact on system design.

The global increase in the elderly population necessitates accurate assessment of the needs of individuals residing in nursing homes. This study aims to optimise a 30-item questionnaire developed on the basis of Maslow's Hierarchy of Needs by employing machine learning algorithms. As one of the pioneering applications in Turkey, the research was conducted with 310 participants from four nursing homes. Data were analysed using Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Linear Regression (LR), and Support Vector Machine (SVM). F-Test results identified the most significant variables, reducing the number of items from 30 to 10. Within the comparative analyses, the GPR model outperformed the others by yielding the lowest mean error metrics (RMSE = 0.252, MSE = 0.064, MAE = 0.195) and the highest predictive accuracy (R² = 0.86). Findings indicate that the physiological, social, and psychological needs of older adults can be assessed through shorter, more reliable questionnaires. This study offers academic and practical contributions to elderly care and interior design.

Ever-greater degrees of work are being undertaken by autonomous systems, and we are left to ask what roles humans will play in these coming, collaborative endeavours. Current consensus points to the increasing requirement for human supervision, largely in the form of sustained attention. The present work seeks to specify boundary conditions to such vigilance. It explores ways to assess the characterising decrement through evaluation of current measures, their shortfalls, and potential avenues for improvement. Decrement in human monitoring capacity is not an obligatory outcome in all hybrid work settings. The vigilance decrement is often avoidable through designs sensitive to the conditions of its occurrence. Where decrement remains, ameliorative recommendations are herewith proposed. The latter strategies are predicated upon improved measurement methods that feature the fuller integration of response accuracy and response latency. How these advances facilitate performance in human-AI teams forms the summary element of the present work.