International Journal of Industrial Ergonomics最新文献_第10页

A virtual reality-based study on tunnel black hole effects on drivers' psychological stress and driving performance 基于虚拟现实的隧道黑洞对驾驶员心理压力及驾驶性能影响研究

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-07-29 DOI: 10.1016/j.ergon.2025.103791

Hanlin Xu , Xianliang Ge , Ke Zhang , Hao Ni , Lei Du , Liezhong Ge , Zhen Yang , Duming Wang

The phenomenon known as the "black hole effect," which occurs at tunnel entrances, is a severe visual illusion induced by dramatic transitions in illuminance, space and reference. Previous studies on tunnel driving safety have been conducted mainly in real tunnels, making it difficult to isolate the effects of different tunnel lighting environments on driving safety and to accurately measure drivers' speed and distance estimations. Therefore, in this work, we introduce a virtual tunnel model with consistent lighting and introduce three scenarios: entering the tunnel (T1), outside the tunnel (T2), and open road (Base). We compared changes in ego speed and dynamic distance estimates for 30 drivers across the three scenarios using the time-to-contact (TTC) paradigm to investigate the effects of spatial transitions. Linear mixed model analyses revealed that spatial transitions caused drivers to significantly overestimate their own speed and underestimate the TTC and caused significant pupil dilation in the T1 scenario. However, results for T2 did not show significant differences in distance or speed estimation from the base results, but the pupil diameter increased significantly. The results of this experiment support the hypothesis that tunnels introduce spatial transitions that directly affect the ego speed and dynamic distance estimation and that tunnels induce driver stress immediately upon entry into the visual field.

这种现象被称为“黑洞效应”，发生在隧道入口处，是一种严重的视觉错觉，由照度、空间和参考的戏剧性变化引起。以往对隧道行车安全的研究主要是在真实隧道中进行的，难以隔离不同隧道照明环境对行车安全的影响，也难以准确测量驾驶员的速度和距离估计。因此，在这项工作中，我们引入了一个具有一致照明的虚拟隧道模型，并引入了三种场景：进入隧道（T1）、隧道外（T2）和开放道路（Base）。本研究采用接触时间（time-to-contact， TTC）范式，比较了30名司机在三种情景下自我速度和动态距离的变化，以研究空间转换的影响。线性混合模型分析表明，在T1情景下，空间转换导致驾驶员显著高估自身速度和低估TTC，并导致显著的瞳孔扩张。然而，T2的结果在距离和速度估计上与基础结果没有显著差异，但瞳孔直径明显增加。本实验结果支持隧道引入空间转换的假设，直接影响自我速度和动态距离估计，隧道在进入视野后立即引起驾驶员应力。

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引用次数: 0

Differences in types and causes of human errors between high-speed and conventional railway dispatching: the potential impact of automation 高速铁路和常规铁路调度的人为错误类型和原因的差异：自动化的潜在影响

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-07-19 DOI: 10.1016/j.ergon.2025.103790

Zizheng Guo , Huishan Pang , Jun Liu , Jiazhe Wang , Jingyu Zhang , Mingming Gao

Dispatcher errors are critical for railway safety, yet the impact of new technology on error types and causes is less understood. High-speed railways (HSR) utilize advanced automated technologies that enhance efficiency but introduce new challenges. This study analyzed 8522 error records from both HSR and conventional rail (CR) dispatchers using a human error classification framework. We categorized these errors into three key task types: monitoring, planning and scheduling, and dispatching instructions. Results showed that HSR dispatchers make more errors in planning and scheduling tasks, particularly decision-making errors influenced by poor crew resource management and adverse mental states. In contrast, they make fewer errors in monitoring and dispatch instructions, with reduced decision errors and violations. Additionally, skill-based errors were less affected by factors such as personal readiness and supervisory issues. We explained these findings by linking them to how automation reduces procedural workload, decreases controllability and predictability, and induces out-of-the-loop unfamiliarity.

调度员错误对铁路安全至关重要，然而新技术对错误类型和原因的影响却鲜为人知。高铁利用先进的自动化技术提高了效率，但也带来了新的挑战。本研究使用人为错误分类框架分析了高铁和常规铁路（CR）调度员的8522条错误记录。我们将这些错误分为三种关键任务类型：监视、计划和调度以及调度指令。结果表明：高铁调度员在计划和调度任务上的失误较多，尤其是决策失误，主要受机组资源管理不善和不良心理状态的影响。相比之下，他们在监控和调度指令方面的错误更少，决策错误和违规行为也更少。此外，基于技能的错误受个人准备和监督问题等因素的影响较小。我们通过将这些发现与自动化如何减少程序性工作负载、降低可控性和可预测性以及引起环外不熟悉联系起来，来解释这些发现。

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引用次数: 0

Enhancing Human-AI perceptual alignment through visual-haptic feedback system for autonomous drones 基于视觉-触觉反馈系统的无人机人机感知一致性研究

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-07-16 DOI: 10.1016/j.ergon.2025.103780

Jiahao Wu , Bowen Sun , Hengxu You , Jing Du

Artificial Intelligence (AI) has emerged as an effective agent for controlling autonomous drones in navigation and target search tasks across various applications with minimal human intervention. Despite their advantages, significant challenges exist in aligning human operators' perceptual understanding with autonomous drone AI's assessment of environmental changes, particularly in dynamic and complex urban settings. This study addresses this issue by proposing a human-machine sensory sharing system that integrates visual and haptic feedback to enhance situational awareness, reduce cognitive load, and improve trust in the AI agent that controls the drones. By bridging the perceptual gap between humans and AI, our approach fosters a more cohesive and responsive interaction, enabling operators to make informed decisions in real-time. Through a human-subject experiment (N = 30) in a simulated urban environment, participants assessed environmental changes and adjusted drone AI parameters based on multimodal sensory feedback. Eye-tracking data were collected to evaluate cognitive load and engagement under different feedback conditions. Results show that combining visual and haptic feedback significantly enhances user performance, satisfaction, and decision-making speed, reducing perceptual misalignment between humans and AI. Participants using multimodal feedback demonstrated faster response times and higher environmental assessment accuracy than single-modality feedback. This research advances the design of intuitive human-drone interaction systems, emphasizing the role of multimodal sensory integration and physiological monitoring in improving human-machine collaboration. These findings have implications for applications in logistics, search and rescue, surveillance, and environmental monitoring, where operator engagement and performance are critical.

人工智能（AI）已经成为一种有效的代理，可以在各种应用中以最少的人为干预来控制自主无人机的导航和目标搜索任务。尽管它们具有优势，但在将人类操作员的感知理解与自主无人机人工智能对环境变化的评估相结合方面存在重大挑战，特别是在动态和复杂的城市环境中。本研究通过提出一种人机感官共享系统来解决这一问题，该系统集成了视觉和触觉反馈，以增强态势感知，减少认知负荷，并提高对控制无人机的人工智能代理的信任。通过弥合人类和人工智能之间的感知差距，我们的方法促进了一种更具凝聚力和响应性的互动，使运营商能够实时做出明智的决策。通过模拟城市环境的人体实验（N = 30），参与者评估环境变化并根据多模态感官反馈调整无人机AI参数。收集眼球追踪数据，评估不同反馈条件下的认知负荷和投入。结果表明，视觉和触觉反馈的结合显著提高了用户的性能、满意度和决策速度，减少了人与人工智能之间的感知偏差。使用多模态反馈的参与者表现出比单模态反馈更快的响应时间和更高的环境评估准确性。本研究提出了直观的人-无人机交互系统设计，强调多模态感觉整合和生理监测在提高人机协作中的作用。这些发现对物流、搜索和救援、监视和环境监测等领域的应用具有重要意义，在这些领域，操作人员的参与和表现至关重要。

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引用次数: 0

A review of potential factors affecting roughness perception 影响粗糙度感知的潜在因素综述

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-07-01 DOI: 10.1016/j.ergon.2025.103778

Hankyoul Kim, Sung H. Han, Subin Kim, Heetae Hwang, Junseong Park, Kimin Kwon

The importance of tactile feedback in extended reality has gained increasing attention for its potential to enhance immersive user experience. However, the implementation of tactile feedback still faces various challenges not only due to technical difficulties but also because the cognitive processes involved remain unclear. Additionally, previous studies on roughness perception are fragmented due to varying implementations of tactile stimuli, specimen provision, and experimental environments. Therefore, a comprehensive understanding of roughness perception is essential. This study reviews existing literature to identify the key potential factors affecting roughness perception, categorizing them into four main elements based on the User Experience Framework: Interaction, System, User, and Context. Interaction refers to how subjects experience roughness, System pertains to the implementation of roughness stimuli, User represents the characteristics of subjects perceiving roughness, and Context addresses the environment of roughness perception. As a result, 32 factors and 8 factor groups were identified and systematically organized to better understand their effects on roughness perception. By structuring these factors within the User Experience Framework, this study provides a foundation for a more comprehensive understanding of roughness perception. Furthermore, these findings offer insights into the broader domain of tactile experience, suggesting potential applications in various fields such as haptic technology development, virtual reality, and human-computer interaction.

触觉反馈在扩展现实中的重要性因其增强沉浸式用户体验的潜力而受到越来越多的关注。然而，触觉反馈的实现仍然面临着各种各样的挑战，这不仅是因为技术上的困难，还因为所涉及的认知过程尚不清楚。此外，由于触觉刺激、标本提供和实验环境的不同，以往的粗糙度感知研究是碎片化的。因此，全面了解粗糙度感知是必不可少的。本研究回顾了现有文献，以确定影响粗糙度感知的关键潜在因素，并基于用户体验框架将其分为四个主要元素：交互、系统、用户和上下文。交互涉及受试者如何体验粗糙度，系统涉及粗糙度刺激的实施，用户代表受试者感知粗糙度的特征，而上下文涉及粗糙度感知的环境。结果，确定了32个因素和8个因素组，并进行了系统组织，以更好地了解它们对粗糙度感知的影响。通过在用户体验框架内构建这些因素，本研究为更全面地理解粗糙度感知提供了基础。此外，这些发现为更广泛的触觉体验领域提供了见解，并提出了在触觉技术开发、虚拟现实和人机交互等各个领域的潜在应用。

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引用次数: 0

Developing workload-informed crew configuration recommendations for emergency medical services 为紧急医疗服务制定工作负荷知情的机组配置建议

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-07-01 DOI: 10.1016/j.ergon.2025.103777

Setareh Darvishi , Paul Misasi , Laila Cure

While crew configuration in primary care settings has been studied in terms of its impact on patient outcomes, less is known about how it influences the members' workload experience. This study investigates the workload implications of crew configuration based on members' certification in emergency medical services (EMS). Advanced life support (ALS) ambulance crews are commonly comprised of two paramedics (homogeneous crew) or an emergency medical technician (EMT) and a paramedic (heterogeneous crew). The goals of this study were the following: (1) to investigate differences in workload among members of the same crew, and (2) to use workload assessments to inform crew configuration strategies. We mapped one year of an EMS system's dispatch data to members' workload estimates using the visual, auditory, cognitive, and psychomotor (VACP) approach. We found that lead members (lead paramedics) experience higher workload levels compared to support members (support paramedics or EMTs) in both types of crews. Neither configuration had a consistently lower workload than the other, but differences varied for different shifts and stations. These results informed crew configuration recommendations for stations and shifts in the collaborating system, and in terms of more generalizable variables. A minimum number of staffed crews, half-half shift type (covering both day and night hours), and 30-day frequency of calls with priority P7 most significantly impacted the recommended crew configurations.

虽然已经研究了初级保健机构的工作人员配置对患者结果的影响，但对其如何影响成员的工作量体验知之甚少。本研究旨在探讨紧急医疗服务中，基于成员资格认证的机组配置对工作量的影响。高级生命支持（ALS）救护人员通常由两名护理人员（同质人员）或一名紧急医疗技术人员（EMT）和一名护理人员（异质人员）组成。本研究的目的如下：(1)调查同一机组成员之间的工作量差异；(2)使用工作量评估来告知机组配置策略。我们使用视觉、听觉、认知和精神运动（VACP）方法将EMS系统一年的调度数据映射到成员的工作量估计。我们发现，在这两种类型的工作人员中，领导成员（领导护理人员）比支持成员（支持护理人员或emt）的工作量更高。两种配置都没有始终比另一种更低的工作量，但不同班次和站点的差异有所不同。这些结果为协作系统中站位和班次的机组人员配置建议提供了依据，并提供了更多可推广的变量。最小工作人员数量、半轮班类型（包括白天和夜间）以及优先级为P7的30天呼叫频率对建议的工作人员配置影响最大。

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引用次数: 0

The influence of interface attributes and interaction elements on user performance and cognitive load in task interruption scenarios 任务中断场景下界面属性和交互元素对用户性能和认知负荷的影响

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-06-25 DOI: 10.1016/j.ergon.2025.103761

Chi Zhang , Da Peng Wei , Yue Ji , Ding Chen , Xin Yan Li , Xiao Dong Gong

This study aims to investigate the mechanisms by which digital interface attributes (interface complexity and similarity) and interaction elements (contextual guidance during the task resumption phase) influence user task performance and cognitive load in task interruption scenarios. A within-subject experimental design was employed, where participants were required to switch between primary and interrupting tasks while completing designated arithmetic tasks, thereby simulating real-world task interruptions. The results indicate that interface complexity is a key factor affecting task performance and cognitive load. High-complexity interfaces significantly prolonged task resumption lag times, increased error rates, and led to higher levels of cognitive load. The effect of interface similarity on performance showed a significant interaction with complexity. Under high complexity conditions, high-similarity interfaces increased resumption lag times; conversely, under low complexity conditions, high-similarity interfaces reduced resumption lag times. Furthermore, providing clear contextual guidance significantly shortened resumption lag times during the task resumption phase and reduced the number of selection errors, although it did not have a sufficiently significant impact on cognitive load. Despite the varying influence of each variable on resumption performance, the overall performance can be explained by the Memory for Goals Theory (MFG). The findings offer valuable theoretical and practical guidance for optimizing interface design in complex task environments, underscoring the importance of considering interface complexity, similarity, and resumption guidance when designing multitasking interfaces.

本研究旨在探讨任务中断情境下，数字界面属性（界面复杂性和相似性）和交互元素（任务恢复阶段的语境引导）对用户任务绩效和认知负荷的影响机制。采用受试者内实验设计，要求参与者在完成指定的算术任务时在主要任务和中断任务之间切换，从而模拟现实世界的任务中断。结果表明，界面复杂性是影响任务绩效和认知负荷的关键因素。高复杂性的界面显著延长了任务恢复延迟时间，增加了错误率，并导致更高水平的认知负荷。界面相似度对性能的影响与复杂性有显著的交互作用。在高复杂性条件下，高相似度接口增加了恢复延迟时间；相反，在低复杂度条件下，高相似度的接口减少了恢复延迟时间。此外，提供清晰的上下文指导显著缩短了任务恢复阶段的恢复滞后时间，减少了选择错误的数量，尽管它对认知负荷没有足够显著的影响。尽管每个变量对恢复表现的影响不同，但总体表现可以用目标记忆理论（MFG）来解释。研究结果为在复杂任务环境下优化界面设计提供了有价值的理论和实践指导，强调了在设计多任务界面时考虑界面复杂性、相似性和恢复指导的重要性。

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引用次数: 0

Gender-specific effects of passive wearable exoskeletons (pwExo) on gait stability and fall risk in simulated construction tasks 被动可穿戴外骨骼（pwExo）对模拟施工任务中步态稳定性和跌倒风险的性别影响

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-06-24 DOI: 10.1016/j.ergon.2025.103776

Muhammad Khan, Chukwuma Nnaji

Exoskeletons (Exos) offer significant benefits, but they may also introduce balance-related challenges, which could vary across genders or be exacerbated by gender-specific factors. This study investigates their biomechanical impact on gait stability and fall risk, considering gender-specific differences and task-specific outcomes. Key metrics, including Peak Pressure (PP), Mean Pressure (MP), Pressure-Time Integral (PTI), and Full Width at Half Maximum (FWHM), were analyzed across dynamic and static tasks. Results revealed that pwExos significantly influenced plantar pressure distribution, particularly in dynamic tasks such as lifting and carrying. Female participants experienced substantial reductions in peak heel pressure (up to 17.7%, p = 0.021), metatarsal pressures (14.2%, p = 0.034), and arch PTI (up to 52.8%), suggesting enhanced load redistribution and stability, whereas males exhibited increased forefoot loading, including a 15.5% increase in metatarsal PP and a 90.8% rise in toe PTI, indicating potential compensatory adaptations. Mean Pressure in females decreased by 73.5% at the heel during placing tasks, while males showed increased anterior pressure in static tasks. The pwExos were most effective during high-load tasks such as lifting and walking with sandbags (10lb), where pressure redistribution was greatest. While static tasks showed limited benefits, improvements in the arch and metatarsal regions suggest partial stabilization. These findings emphasize the potential of pwExos to enhance stability and reduce biomechanical fatigue, highlighting the need for task-specific and gender-sensitive designs. Future research should assess long-term effects, real-world applicability, and the role of individual factors such as Body Mass Index to optimize Exo integration in construction safety and health management.

外骨骼（Exos）提供了显著的好处，但它们也可能带来与平衡相关的挑战，这些挑战可能因性别而异，或因性别特定因素而加剧。考虑到性别差异和特定任务的结果，本研究调查了他们对步态稳定性和跌倒风险的生物力学影响。关键指标包括峰值压力（PP）、平均压力（MP）、压力-时间积分（PTI）和半最大全宽度（FWHM），在动态和静态任务中进行了分析。结果显示，pwExos显著影响足底压力分布，特别是在动态任务中，如举起和搬运。女性受试者的峰值足跟压力（高达17.7%,p = 0.021）、跖骨压力（14.2%,p = 0.034）和足弓PTI（高达52.8%）显著降低，表明负荷再分配和稳定性增强，而男性受试者的前脚负荷增加，包括跖骨PP增加15.5%，趾部PTI增加90.8%，表明潜在的代偿性适应。在放置任务中，女性脚后跟的平均压力下降了73.5%，而男性在静态任务中表现出增加的前压。pwexo在搬运沙袋（10磅）等高负荷任务中最为有效，因为这些任务的压力再分配效果最好。虽然静态任务的益处有限，但足弓和跖骨区域的改善表明部分稳定。这些发现强调了pwExos在增强稳定性和减少生物力学疲劳方面的潜力，强调了针对特定任务和性别敏感设计的必要性。未来的研究应评估长期效果、现实适用性以及个体因素（如身体质量指数）的作用，以优化Exo集成在建筑安全与健康管理中的作用。

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引用次数: 0

Comparative analysis of classical and ensemble models for predicting whole body vibration induced lumbar spine stress. A case study of agricultural tractor operators 经典模型与集合模型预测腰椎全身振动应力的比较分析。农用拖拉机操作员的案例研究

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-06-20 DOI: 10.1016/j.ergon.2025.103775

Amandeep Singh , Naser Nawayseh , Philippe Doyon-Poulin , Stephan Milosavljevic , Krishna N. Dewangan , Yash Kumar , Siby Samuel

Accurate prediction of lumbar health is necessary for developing effective ergonomic strategies for tractor operators exposed to whole-body vibration. This study aims to predict static compression dose (S_ed), a key measure of lumbar spine stress as per ISO 2631-5, by comparing classical regression and ensemble models. Three tractor operation parameters (average speed, average depth, and pulling force) are considered to assess S_ed during rotary tillage operation. The performance of two classical models (Linear and Huber regression) is compared with five ensemble models (Random Forest, Gradient Boosting, XGBoost, AdaBoost, and Bagging regressors) in predicting S_ed. The comparison identifies the best models in each category, with linear regression achieving a mean bootstrap R² of 0.91 (95 % CI: 0.87 to 0.94) and Random Forest achieving 0.93 (95 % CI: 0.90 to 0.95). To further enhance performance, meta-models are developed using two meta-learners (Random Forest and Gradient Boosting) to integrate classical and ensemble models. These models are optimized using different ensemble strategies: simple averaging, weighted averaging, stacking, and voting regressors. Among these, the stacking method proves most effective, achieving a mean bootstrap R² of 0.94 (95 % CI: 0.93 to 0.96). Feature importance analysis reveals that the multi-model combination of ensemble models achieves the highest predictive score (0.99) for S_ed. These findings demonstrate that ensemble models outperform classical models in predicting Sed, particularly when combined through stacking methods. This advancement has significant implications for improving occupational health and safety among tractor operators, potentially leading to better ergonomic tractor designs aimed at reducing lumbar spine stress.

准确预测腰椎健康状况对于制定有效的人体工程学策略对于暴露于全身振动的拖拉机操作员是必要的。本研究旨在通过比较经典回归模型和集合模型来预测静态压缩剂量（Sed），这是ISO 2631-5规定的腰椎应力的关键指标。考虑三个拖拉机操作参数（平均速度，平均深度和牵引力）来评估旋转耕作操作中的Sed。将两种经典模型（线性和Huber回归）与五种集成模型（随机森林、梯度增强、XGBoost、AdaBoost和Bagging回归）在预测Sed方面的性能进行了比较。比较确定了每个类别中的最佳模型，线性回归的平均bootstrap R2为0.91 (95% CI: 0.87至0.94)，随机森林的平均bootstrap R2为0.93 （95% CI: 0.90至0.95）。为了进一步提高性能，使用两个元学习器（随机森林和梯度增强）开发元模型来集成经典模型和集成模型。这些模型使用不同的集成策略进行优化：简单平均、加权平均、堆叠和投票回归。其中，叠加法被证明是最有效的，实现了0.94的平均bootstrap R2 （95% CI: 0.93至0.96）。特征重要性分析表明，集成模型的多模型组合对Sed的预测得分最高（0.99）。这些发现表明，集成模型在预测Sed方面优于经典模型，特别是当通过堆叠方法组合时。这一进展对改善牵引车操作人员的职业健康和安全具有重要意义，可能导致更好的符合人体工程学的牵引车设计，旨在减少腰椎压力。

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引用次数: 0

A new measurement for workload assessment in agricultural tasks: EDA-based real-time model 一种新的农业任务工作量评估方法：基于eda的实时模型

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-06-20 DOI: 10.1016/j.ergon.2025.103771

Sujin Seong , Jaehyun Park , Jeong Ho Kim

Agriculture is vital for the global economy but remains one of the most hazardous industries due to the high prevalence of musculoskeletal disorders (MSDs). This study aimed to develop and validate an electrodermal activity (EDA)-based model for non-invasive, real-time assessment of upper limb task workload, addressing the impact of environmental factors on workers' mental and physical strain. To achieve this, participants engaged in simulated pruning and harvesting tasks, which are known for imposing substantial workload and injury risks on the upper extremities in agriculture. Anthropometric data, EDA signals, and the Borg rating of perceived exertion (RPE) were collected. A multinomial logistic regression (MLR) model was employed to classify workload levels based on EDA wavelet features and key task-related variables. The developed models for pruning and harvesting tasks explained 40–50 % of the variance in RPE, demonstrating the highest accuracy in the middle RPE group (88–89 %). Specificity was notably high (>91 %) across both tasks for low and high RPE groups. Additionally, the middle RPE group exhibited recall and F1 scores above 84.5 %, while the high RPE category demonstrated recall, precision, and F1 scores ranging from 73 % to 92 % for pruning and from 60 % to 75 % for harvesting. These findings underscore the model's potential for precise workload categorization and the development of effective management strategies. Furthermore, the proposed EDA-based framework may hold broader applicability across various occupational domains that require non-invasive and continuous workload monitoring.

农业对全球经济至关重要，但由于肌肉骨骼疾病（MSDs）的高发，农业仍然是最危险的行业之一。本研究旨在开发并验证一种基于皮肤电活动（EDA）的模型，用于无创、实时评估上肢任务工作量，解决环境因素对工人精神和身体压力的影响。为了实现这一目标，参与者参与了模拟修剪和收获任务，这些任务在农业中会对上肢施加大量工作量和伤害风险。收集人体测量数据、EDA信号和感知运动的博格评分（RPE）。基于EDA小波特征和关键任务相关变量，采用多项逻辑回归（MLR）模型对工作负荷进行分类。开发的修剪和收获任务模型解释了RPE中40 - 50%的方差，显示了中间RPE组的最高准确性（88 - 89%）。在低RPE组和高RPE组的两项任务中，特异性都非常高（> 91%）。此外，中等RPE组的召回率和F1得分高于84.5%，而高RPE组的召回率、准确率和F1得分在修剪的73%到92%之间，收割的60%到75%之间。这些发现强调了该模式在精确工作量分类和制定有效管理战略方面的潜力。此外，建议的基于eda的框架可能在需要非侵入性和连续工作负载监控的各种职业领域具有更广泛的适用性。

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引用次数: 0

Metaphorical types of industrial icons: Impact on cognitive performance and the neural pattern in processing 工业标志隐喻类型对认知表现的影响及加工中的神经模式

IF 2.5 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-06-19 DOI: 10.1016/j.ergon.2025.103772

Lan Zhang , Xiaoli Wu , Biao Yan , Linyan Ren , Xiaoyang Mao

The rapid development of intelligent manufacturing poses challenges to the presentation of industrial information, leading to a recent surge of interest in industrial icons. To explore the semantic understanding of industrial icons within the intelligent manufacturing field, this study conducted an event-related potential (ERP) investigation focusing on metaphorical types (object metaphor, structural metaphor) and semantic conditions (match, mismatch). The ERP components observed—N1, P200, N400, and P600—reflect different stages of cognitive processing. N1 represents an initial response to visual perception, P200 indicates early recognition of semantic violations, N400 is associated with semantic processing and integration, and P600 reflects a prolonged reanalysis process for semantic integration. The study found that object metaphor elicited larger amplitudes in P200 and a smaller N400 compared to structural metaphor, suggesting that object metaphor requires more attention resources and is less impacted by semantic violations. However, the amplitude of P600 showed no significant difference between the two metaphorical types. Behavioral results demonstrated that object metaphor had higher accuracy and shorter response times than structural metaphor, indicating superior cognitive performance for object metaphor. These findings propose a novel perspective on using ERP components (N1, P200, N400, P600) to gain a deeper understanding of industrial icons. This contributes to the study of metaphorical design and the semantic understanding of industrial icons in the intelligent manufacturing domain.

智能制造的快速发展对工业信息的呈现提出了挑战，近年来人们对工业图标的兴趣激增。为探索智能制造领域工业图标的语义理解，本研究以隐喻类型（对象隐喻、结构隐喻）和语义条件（匹配、不匹配）为重点，开展了事件相关电位（ERP）调查。观察到的ERP成分n1、P200、N400和p600反映了认知加工的不同阶段。N1表示对视觉感知的初始反应，P200表示对语义违规的早期识别，N400与语义加工和整合相关，P600表示语义整合的再分析过程较长。研究发现，与结构隐喻相比，客体隐喻诱发的P200振幅较大，N400振幅较小，说明客体隐喻需要更多的注意资源，受语义违背的影响较小。而P600的振幅在两种隐喻类型间无显著差异。行为实验结果表明，客体隐喻比结构隐喻具有更高的准确性和更短的反应时间，表明客体隐喻具有更高的认知能力。这些发现提出了使用ERP组件（N1, P200, N400, P600）来更深入地理解工业图标的新视角。这有助于隐喻设计的研究和智能制造领域工业符号的语义理解。

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