International Journal of Industrial Ergonomics最新文献_第9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 : 2025-09-01 Epub 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

Shoulder pain influences kinematics during farm work tasks: An in-field study 肩部疼痛影响农场工作任务中的运动学：一项实地研究

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-05 DOI: 10.1016/j.ergon.2025.103798

Angelica E. Lang , Denise Balogh , Opeyemi Vincent Akinluyi , Niels Koehncke

Background

Work-related musculoskeletal disorders (MSDs) are prevalent among agricultural producers. Upper limb MSDs, especially in the shoulder and neck, are common, yet research on their development and prevention is limited. This study aims to investigate the influence of shoulder pain, age, and sex on shoulder kinematics during farm work tasks.

Methods

Farmers in Saskatchewan were recruited and divided into groups with and without shoulder pain. Participants performed four tasks (Overhead Drill, Climb Seeder, Seed Bag Lift, Shovel) while wearing inertial measurement units (IMUs) to track humeral and scapular movements. Data were analyzed using linear regression and Kruskal-Wallis tests (p < .05) to assess the effects of pain, age, and sex on shoulder kinematics.

Results

Forty-two participants (23 without pain, 19 with pain) completed the study. Pain significantly influenced shoulder kinematics during the Overhead Drill, Seed Bag Lift, and Shovel tasks. During the Overhead Drill, the pain group exhibited higher scapular upward rotation (p = .04, +5.1°) and females showed lower maximal humeral elevation (p = .049, −11.7°). In the Seed Bag Lift, the pain group had lower scapular upward rotation (p = .012, −18.7°) and higher humeral internal rotation (p = .04, +12.0°). Humeral elevation was also lower in the pain group during the Shovel task (p = .019, −12.7°).

Conclusions

Shoulder pain affects shoulder kinematics in farm work tasks, with variations depending on the task. Pain-related compensations can be both protective and harmful. These findings highlight the potential risk for shoulder injury in many aspects of farm work.

与工作相关的肌肉骨骼疾病（MSDs）在农业生产者中很普遍。上肢，特别是肩部和颈部的msd是常见的，但对其发展和预防的研究有限。本研究旨在探讨肩部疼痛、年龄和性别对农场工作时肩部运动学的影响。方法招募萨斯喀彻温省的农民并将其分为有肩痛组和无肩痛组。参与者在佩戴惯性测量装置（imu）来跟踪肱骨和肩胛骨运动的同时，完成了四项任务（架空播种机、爬升播种机、种子袋提升和铲子）。数据分析采用线性回归和Kruskal-Wallis检验(p <；.05)评估疼痛、年龄和性别对肩关节运动的影响。结果42例受试者（无疼痛23例，有疼痛19例）完成研究。疼痛显著影响肩运动学在架空钻，种子袋提升和铲任务。在头顶训练期间，疼痛组的肩胛骨向上旋转幅度较大（p = 0.04, +5.1°），而女性的最大肱骨抬高幅度较小（p = 0.049, - 11.7°）。在种子袋提术中，疼痛组肩胛骨下向上旋转（p = 0.012,−18.7°），肱骨内旋转（p = 0.04, +12.0°）。在Shovel任务期间，疼痛组的肱骨抬高也较低（p = 0.019, - 12.7°）。结论：肩关节疼痛会影响农活任务中肩关节的运动学，并随任务的不同而变化。与疼痛相关的补偿可能是保护性的，也可能是有害的。这些发现强调了在农场工作的许多方面肩部受伤的潜在风险。

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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 : 2025-09-01 Epub 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

Modelling type 2 diabetic patients’ glucose metabolism for real-time predictive healthcare service 2型糖尿病患者糖代谢模型的实时预测医疗服务

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 DOI: 10.1016/j.ergon.2025.103802

Qidi Zhang, Zhonghao Chang, Liang Ma

Continuous glucose monitoring (CGM) sensors and other smart wearables offer valuable opportunities for advancing diabetes disease self-management. However, whether patients may take advantage of CGM data, take preventative behavior, and achieve improved glucose self-management result under natural living conditions still needs to be explored. Human’ s capacity of time series data processing in glucose self-management scenario needs to be evaluated. Accordingly, this study aims to (1) examine whether wearing a CGM sensor alone is effective for glucose self-management and explore key obstacles if any, and (2) develop a high-performance predictive model for real-time glucose forecasting to facilitate self-management. Thirty Type 2 Diabetes (T2D) patients were recruited to collect 13–14 days of glucose, dietary, exercise, and medication data in real-world settings using CGM sensors and smart bands, supplemented by self-reported loggings. The results show no significant improvement in patients' mean glucose levels. An attention-enhanced long short-term memory (ALSTM) glucose prediction model was developed and validated using data from 20 out of the 30 participants, achieving high predictive accuracy for 30/60-min prediction accuracy (errors <5 %). When applied to the other 10 participants, the model combined with deep transfer learning gained high prediction accuracy (errors <6.4 % and 4.7 %, respectively), and may enable early-stage predictions for new patients with limited data. Further experiment with 60 graduate students showed that human’ s predicting accuracy cannot compete with the model and is insufficient for self-management. The proposed approach holds promise for future predictive interventions, enabling timely and personalized glucose management strategies for T2D patients.

连续血糖监测（CGM）传感器和其他智能可穿戴设备为推进糖尿病疾病的自我管理提供了宝贵的机会。然而，在自然生活条件下，患者能否充分利用CGM数据，采取预防行为，达到更好的血糖自我管理效果，仍有待探讨。人类在葡萄糖自我管理情景下处理时间序列数据的能力有待评估。因此，本研究旨在(1)检验单独佩戴CGM传感器是否对血糖自我管理有效，并探索存在的关键障碍；(2)开发用于实时血糖预测的高性能预测模型，以促进自我管理。招募了30名2型糖尿病（T2D）患者，在现实环境中使用CGM传感器和智能手环收集13-14天的血糖、饮食、运动和药物数据，并辅以自我报告的记录。结果显示，患者的平均血糖水平没有明显改善。使用来自30名参与者中的20名的数据，开发并验证了注意力增强长短期记忆（ALSTM）葡萄糖预测模型，在30/60分钟的预测精度（误差<； 5%）内实现了较高的预测精度。当应用于其他10名参与者时，该模型结合深度迁移学习获得了很高的预测精度（误差分别为6.4%和4.7%），并且可以在数据有限的情况下对新患者进行早期预测。对60名研究生的进一步实验表明，人类的预测精度无法与模型竞争，也不足以进行自我管理。提出的方法为未来的预测性干预提供了希望，为T2D患者提供及时和个性化的血糖管理策略。

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引用次数: 0

Evaluation and improvement of rail station name list signage on platform for direction by VR experiments with eye-tracker 基于眼动仪的VR实验评价与改进站台指路的铁路车站名单标识

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-05 DOI: 10.1016/j.ergon.2025.103781

Weitong Wang , Zijia Wang , Yufeng Li , Zixuan Mao , Danyong Feng , Liang Yu

Although considerable research has been conducted on signage, there remains room for further study on platform station name list signage. To evaluate and improve this, wayfinding experiments were carried out in a virtual reality-based rail station. Participants' multidimensional eye movement data and wayfinding performance were collected. The results revealed that participants strongly favored horizontal signage (HS), while vertical signage (VS) demonstrated better wayfinding performance. Additionally, participants exhibited varying levels of attention towards different regions of different types. Based on these findings, the signage was modified, outperforming HS in effectiveness and surpassing VS in information clarity and conciseness. This study contributes to a deeper understanding of passengers' cognitive behavior during wayfinding on subway platforms, particularly concerning diverse signage types, and provides valuable recommendations for signage evaluation and optimization.

虽然对标识进行了大量的研究，但站台名单标识的研究还有待进一步深入。为了评估和改进这一点，在一个基于虚拟现实的火车站进行了寻路实验。收集参与者的多维眼动数据和寻路表现。结果显示，参与者强烈喜欢水平标识（HS），而垂直标识（VS）表现出更好的寻路性能。此外，参与者对不同类型的不同区域表现出不同程度的注意力。基于这些发现，对标识进行了修改，在有效性上优于HS，在信息清晰度和简洁性上优于VS。本研究有助于更深入地了解乘客在地铁站台寻路过程中的认知行为，特别是对不同类型标识的认知行为，并为标识的评价和优化提供有价值的建议。

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 : 2025-09-01 Epub 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

Influence of surface curvature and pinch span on the maximal force exertion of pinch grip: a prospective cohort study 面曲率和捏握间距对捏握最大力发挥影响的前瞻性队列研究

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-22 DOI: 10.1016/j.ergon.2025.103800

Jeewon Choi , Yu Lin , Ping Yeap Loh

This study investigated how the pinch surface curvature and pinch span influence the maximal voluntary pinch grip forces (MVFs) for different pinch types. Twelve male participants (age range: 22–34) underwent MVF measurements using a pinch grip on a dynamometer with six interchangeable attachment surfaces. They were randomly assigned to either a concave or convex handle group, each tested with three pinch spans (3, 5, and 7 cm) using a custom-designed dynamometer (Model T.K.K. 1269m and TSA-210; Takei Scientific Instruments Co., Ltd.). The pinch type was controlled as a tip, three-jaw, or key pinch, and both the dominant and non-dominant hands were examined. After completing the trials for each condition, participants rated their overall comfort, perceived fit, and perceived difficulty on a 5-point rating scale. We demonstrated that the concave surface was associated with greater MVFs than the convex surface (p < 0.01). However, the difference in MVF was insignificant when the pinch span was increased to 7 cm. The key pinch and dominant hand showed higher MVFs, better fit, and lower difficulty than their counterparts (key pinch: ps < 0.05; dominant hand: ps < 0.01). This study provides evidence on the design of pinch surface curvature and span that can effectively enhance MVF performance under varying pinch span conditions.

本文研究了不同夹握类型下，夹握面曲率和夹握跨度对最大自主夹握力的影响。12名男性参与者（年龄范围：22-34岁）接受了MVF测量，使用一个夹握在6个可互换的附着表面的测力计上。他们被随机分配到凹柄组或凸柄组，每个组使用定制设计的测力计（型号T.K.K. 1269m和TSA-210；武井科学仪器有限公司）进行三个捏距（3,5和7厘米）的测试。捏捏类型被控制为尖捏、三颚捏或键捏，并且检查了优势手和非优势手。在完成每种条件的试验后，参与者对他们的整体舒适度、感知契合度和感知困难度进行了5分制的评分。我们证明了凹表面比凸表面与更大的MVFs相关（p < 0.01）。当夹紧间距增加到7 cm时，MVF的差异不显著。键捏和优势手的MVFs值较高，配合度较好，难度较低（键捏：ps <； 0.05；优势手：ps <； 0.01）。研究结果表明，在不同夹紧跨度条件下，夹紧曲面曲率和夹紧跨度的设计可以有效地提高MVF的性能。

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引用次数: 0

Exploring the relationship between miners’ physiological signals and safety behavior in four emergency scenarios in coal mines: A virtual reality study 基于虚拟现实的煤矿四种应急情景下矿工生理信号与安全行为的关系研究

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-21 DOI: 10.1016/j.ergon.2025.103801

Yanyu Guo , Jizu Li , David Cliff

This study explores the relationship between miners' physiological signals and their safety behavior in emergency scenarios, with the aim of enhancing early warning systems for occupational safety. A virtual reality-based experiment was conducted in which miners were exposed to four simulated emergency scenarios. Physiological signals—including heart rate variability (Mean IBI, RMSSD, PNN50, LF/HF ratio), skin conductance (SC), and blood oxygen saturation (SPO₂)—were continuously recorded alongside behavioral performance measures such as reaction time and accuracy. Statistical analyses, including the Friedman test, repeated measures ANOVA, correlation analysis, and multivariate regression, revealed significant differences between emergency and resting conditions. Key findings indicated that faster reaction times were associated with lower PNN50 and SPO₂ but higher SC. Memory accuracy declined when PNN50 decreased and SC and skin temperature (SKT) increased. Discrimination performance improved with higher Mean IBI and SPO₂, but deteriorated with elevated RMSSD, PNN50, or reduced SKT. A classification model achieved 78.3 % accuracy in predicting miners’ safety behavior competence levels based on physiological inputs. These findings suggest a strong association between physiological responses and behavioral performance during emergencies, supporting the development of real-time physiological monitoring systems to enhance miners' safety. Further research should examine causal relationships and optimize predictive modeling approaches.

本研究旨在探讨紧急情况下矿工的生理信号与安全行为之间的关系，以完善职业安全预警系统。在一项基于虚拟现实的实验中，矿工们被暴露在四种模拟的紧急情况下。生理信号——包括心率变异性（平均IBI、RMSSD、PNN50、LF/HF比）、皮肤电导（SC）和血氧饱和度（SPO2）——与行为表现指标（如反应时间和准确性）一起连续记录。统计分析，包括弗里德曼检验、重复测量方差分析、相关分析和多变量回归，揭示了急救和休息条件之间的显著差异。实验结果表明，PNN50和SPO2降低与SC升高有关，PNN50降低、SC升高、SKT升高导致记忆准确性下降。随着平均IBI和SPO2的升高，识别性能得到改善，但随着RMSSD、PNN50或SKT的降低而恶化。基于生理输入的分类模型预测矿工安全行为能力水平的准确率达到78.3%。这些研究结果表明，紧急情况下的生理反应与行为表现之间存在密切联系，支持开发实时生理监测系统以提高矿工的安全。进一步的研究应该检查因果关系和优化预测建模方法。

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引用次数: 0

Impact of back and leg-support exoskeletons on novice users’ attention during repetitive lifting task 背部和腿部支撑外骨骼对新手用户在重复性举重任务中的注意力的影响

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-15 DOI: 10.1016/j.ergon.2025.103796

Daniel Leibman, HeeSun Choi

Industrial exoskeletons have the potential to reduce users' physical strain and fatigue and prevent injuries in manual and labor-intensive workplaces. However, the use of exoskeletons may increase users' attentional load, especially among those new to the technology, due to greater task demands involving adaptation to augmented and shifted physical capabilities, unfamiliarity with the device, and interference resulting from discomfort, device misfit, and mobility restrictions. In this study, 25 novice exoskeleton users performed an attentionally demanding visual target detection task concurrently with a repetitive lifting task, both with and without back- and leg-support exoskeletons using a within-subjects design. The results indicate that attentional task performance significantly declined when wearing exoskeletons, suggesting that exoskeleton use may impair users' attention. Participants' lifting task performance was also slowed when wearing exoskeletons. These findings suggest that exoskeleton use may initially impact workers’ performance on both motor and cognitive tasks. Changes in self-rated mental workload were not correlated with observed attentional decrements, indicating that subjective measure may not effectively detect cognitive demands associated with exoskeleton use.

工业外骨骼有可能减少使用者的身体紧张和疲劳，并防止在手工和劳动密集型工作场所受伤。然而，外骨骼的使用可能会增加用户的注意力负荷，特别是对于那些新接触该技术的用户，因为更大的任务需求涉及适应增强和转移的物理能力，对设备的不熟悉，以及由不适、设备不适合和移动限制引起的干扰。在这项研究中，25名外骨骼新手用户使用受试者内部设计，在使用或不使用背部和腿部支撑外骨骼的情况下，同时执行了一项注意力要求高的视觉目标检测任务。结果表明，佩戴外骨骼时，注意力任务表现显著下降，表明外骨骼使用可能会损害用户的注意力。佩戴外骨骼时，参与者的举重任务表现也会减慢。这些发现表明，外骨骼的使用最初可能会影响工人在运动和认知任务上的表现。自评心理工作量的变化与观察到的注意力下降无关，表明主观测量可能无法有效检测与外骨骼使用相关的认知需求。

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引用次数: 0

The effects of cognitive load and task precision restrictions on trunk and shoulder kinematics in a manual material handling task 认知负荷和任务精度限制对人工搬运任务中躯干和肩部运动学的影响

IF 3 2区工程技术 Q2 ENGINEERING, INDUSTRIAL

International Journal of Industrial Ergonomics

Pub Date : 2025-09-01 Epub Date: 2025-08-15 DOI: 10.1016/j.ergon.2025.103795

Anas Kachlan , Steven A. Lavender , Carolyn Sommerich

This study examined how a concurrent mental task and precision restrictions affected the kinematics of the trunk and shoulder during a simulated lifting task. Musculoskeletal disorders in material handling operations are highly prevalent. In addition to completing physically demanding work, workers must also manage concurrent mental demands. Few studies have examined the effect of concurrent mental demands in occupationally relevant tasks. This study quantified the effects of varying degrees of cognitive loads and task precision demands on a material handling task by examining these effects on the kinematics of the trunk and shoulders. Eleven subjects lifted and placed a 5 kg box at one of three destination heights (low, middle, high) while performing a simultaneous cognitive task (no task, a simple task, a complex task) and under two precision conditions (low precision, high precision). The cognitive task consisted of time-based arithmetic questions at two levels of difficulty. The primary dependent measures were the angular velocities of the trunk and shoulders. Significant decreases in angular velocities for both higher cognitive load complexities and higher precision conditions were observed, which differed depending on the destination height. Overall, this study found that increased complexity of a simultaneous cognitive task and higher task precision requirements led to longer lift times and decreased joint velocities.

本研究考察了在模拟举重任务中，并发的心理任务和精度限制如何影响躯干和肩部的运动学。材料搬运作业中的肌肉骨骼疾病非常普遍。除了完成体力要求高的工作外，员工还必须同时管理精神需求。很少有研究考察并行心理需求对职业相关任务的影响。本研究量化了不同程度的认知负荷和任务精度要求对材料搬运任务的影响，通过检查这些对躯干和肩部运动学的影响。11名受试者在同时执行认知任务（无任务、简单任务、复杂任务）和两种精度条件（低精度、高精度）时，将一个5公斤重的箱子举起并放置在三个目标高度（低、中、高）之一。认知任务包括两个难度等级的基于时间的算术问题。主要的依赖指标是躯干和肩膀的角速度。在高认知负荷复杂性和高精度条件下，角速度显著下降，这取决于目标高度。总的来说，这项研究发现，同时认知任务的复杂性增加和任务精度要求提高会导致抬升时间延长和关节速度下降。

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引用次数: 0