International Journal of Industrial Ergonomics最新文献_第3页

An LSTM-based system for accurate breast shape identification and personalized bra recommendations for young women 一个基于lstm的系统，为年轻女性提供准确的乳房形状识别和个性化的胸罩推荐

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-11 DOI: 10.1016/j.ergon.2025.103736

Sha Sha , Zhe Fan , Cheng Chi , Yaru Wan

{"title":"An LSTM-based system for accurate breast shape identification and personalized bra recommendations for young women","authors":"Sha Sha , Zhe Fan , Cheng Chi , Yaru Wan","doi":"10.1016/j.ergon.2025.103736","DOIUrl":"10.1016/j.ergon.2025.103736","url":null,"abstract":"<div><div>Young women often struggle with ill-fitting bras, which can impede breast development and may contribute to breast-related health issues. From a business perspective, this also increases the likelihood of product returns. While various methods have been proposed to classify breast shapes and enhance bra design, the lack of accessible measurement tools and expertise often makes it difficult for young women to select appropriate bras. This study addresses this issue by introducing a Long Short-Term Memory (LSTM)-based recommendation system that helps young women easily and accurately choose well-fitting bras. To precisely identify the shapes of young women's breasts, this study collected human body data from 150 individuals using a 3D body scanner and employing ergonomics expertise and statistical analysis methods such as Principal Component Analysis (PCA) to classify 7 key indices such as bust circumference, underbust circumference, and lower mammary cup arc length as breast shape indices. The k-means clustering method subdivided breast shapes into six categories. Next, based on the classification result, an LSTM based discrimination model was developed to identify the breast morphology, achieving a breast identification accuracy of 85.71 %, surpassing both the Back Propagation (BP) neural network and Convolutional Neural Network (CNN) in terms of operational efficiency, fitting accuracy, and overall performance. Finally, users only need to input the breasts measurements to receive recommended bra parameters and corresponding style chart. This study not only enhances comfort and health by facilitating optimal bra selection but also minimizes return rates and improves the shopping experience, crucial for the sustainable development of the apparel industry.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103736"},"PeriodicalIF":2.5,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Creating more viable safety recommendations in accident investigation by revising the human factors intervention matrix (HFIX) 通过修改人为因素干预矩阵（HFIX），为事故调查提供更可行的安全建议

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-10 DOI: 10.1016/j.ergon.2025.103743

Wesley Tsz-Kin Chan , Wen-Chin Li , Richard Yeun , Thomas Wang

引用次数: 0

Accessibility evaluation of assembly operations in confined space based on digital human model 基于数字人模型的密闭空间装配作业可达性评价

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-10 DOI: 10.1016/j.ergon.2025.103719

Silu Wang, Jianguang Li, Mingyue Yin, Qian Wu

{"title":"Accessibility evaluation of assembly operations in confined space based on digital human model","authors":"Silu Wang, Jianguang Li, Mingyue Yin, Qian Wu","doi":"10.1016/j.ergon.2025.103719","DOIUrl":"10.1016/j.ergon.2025.103719","url":null,"abstract":"<div><div>The confined spaces (CS) of large equipment are typically compact with intricate operational environments, which significantly affect the accessibility, efficiency, and operational quality of workers. Spatial accessibility evaluation, as a critical indicator of worker safety and product design optimization, is an essential part of equipment product design. This study proposes a comprehensive evaluation method based on digital human models (DHMs) and virtual reality systems (VRS) for the quantitative analysis of operational accessibility in CS. The method integrates DHMs and ergonomics data to analyze human dynamics, path accessibility, operational accessibility, and visibility. It defines the spatial restriction ratio (SRR) and the operational freedom ratio (OFR), and combines directional weight coefficients for specific operation types with REBA posture ratings to construct a multi-dimensional quantitative evaluation system. The experiment was based on 6 confined units and 11 operations of an equipment, recruiting 10 subjects to simulate real operations through VRS to validate the effectiveness of the method. The results of the tests demonstrate that the method can effectively evaluate the operation accessibility in CS, optimize the product layout, reduce the risk of musculoskeletal injuries for workers, and provide theoretical support for the iterative design of industrial equipment. It promotes the transition of operational accessibility evaluation in CS from experience-driven to data-driven precision upgrades, offering new perspectives and methodological support for the spatial layout optimization and scientifically reasonable operation planning of complex industrial products.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103719"},"PeriodicalIF":2.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of a parametric model of adult human ear geometry 成人耳几何参数化模型的建立

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-09 DOI: 10.1016/j.ergon.2025.103738

Matthew P. Reed, Tyler R. Vallier, Anne C. Bonifas

引用次数: 0

Affective judgment of viewing an illuminated in-product space in relation to the surrounding lighting 观察产品内部照明空间与周围照明的关系的情感判断

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-09 DOI: 10.1016/j.ergon.2025.103742

Byeongjin Kim, Hyeon-Jeong Suk

{"title":"Affective judgment of viewing an illuminated in-product space in relation to the surrounding lighting","authors":"Byeongjin Kim, Hyeon-Jeong Suk","doi":"10.1016/j.ergon.2025.103742","DOIUrl":"10.1016/j.ergon.2025.103742","url":null,"abstract":"<div><div>This study deals with the appropriate lighting conditions within in-product spaces, focusing on two parameters: illuminance and correlated color temperature (CCT), in relation to the surrounding light conditions. The study was structured around two main experiments. The first experiment investigated how the perceived illuminance inside these in-product spaces correlates with the intensity of surrounding light, demonstrating that preferred interior lighting levels are directly influenced by surrounding lighting conditions and the color of the interior surfaces. The optimal illuminance was predicted using a regression model: Best Illuminance = 18.20 × L value of product +.70 × Surrounding illuminance - 514.30 (<em>R</em><sup>2</sup> = .75), indicating that preferred in-product illuminance increases with higher surrounding illuminance. The second experiment examined the perception of ’whiteness’ and preference for in-product space lighting CCT under varying CCT of surrounding light. The results showed that higher surrounding CCT significantly increased the perceived white point of in-product. The perceived white point was predicted using a model: 10<sup>6</sup>∕Correlated Color Temperature of Whitest Light = 3.13 × 10<sup>5</sup> × Surrounding Correlated Color Temperature +150.69 (<em>R</em><sup>2</sup> = .57), indicating that the perceived white point shifts toward higher CCT under cooler surroundings. Additionally, participants preferred a higher CCT than the perceptual white point as the lighting within the in-product space. These experiments provide concrete guidelines for designing lighting within in-product spaces, offering predictive models for both illuminance and CCT to support more effective and user-preferred lighting solutions across various product settings.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103742"},"PeriodicalIF":2.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond certification: Improving lifeguard drowning detection through validated tools and specialized training 超越认证：通过有效的工具和专业培训提高救生员溺水检测

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-09 DOI: 10.1016/j.ergon.2025.103741

Benjamin T. Sharpe , Marcus S. Smith , Steven C.R. Williams , Adam Hampshire , Maria Balaet , William Trender , Peter J. Hellyer , Jo Talbot , Jenny Smith

{"title":"Beyond certification: Improving lifeguard drowning detection through validated tools and specialized training","authors":"Benjamin T. Sharpe , Marcus S. Smith , Steven C.R. Williams , Adam Hampshire , Maria Balaet , William Trender , Peter J. Hellyer , Jo Talbot , Jenny Smith","doi":"10.1016/j.ergon.2025.103741","DOIUrl":"10.1016/j.ergon.2025.103741","url":null,"abstract":"<div><div>This study investigated two key aims: (1) the external validity of an animated performance assessment tool previously utilized in lifeguard training, with a focus on how lifeguard experience and task duration affect performance metrics, and (2) the impact of two distinct training protocols on lifeguard-specific drowning detection abilities. In the first experiment, experienced lifeguards demonstrated superior performance compared to inexperienced lifeguards in both 30-min tasks; however, both groups exhibited a decline in performance over time. The external validity of the animated tool was supported by its ability to produce performance outcomes aligned with real-world lifeguard tasks. The second experiment revealed that training specifically designed for lifeguard drowning detection significantly enhanced detection performance, while working memory training showed no measurable effect. These results highlight the necessity of incorporating realistic drowning detection challenges—such as varied bather numbers, drowning durations, and locations—into lifeguard certification programs, which currently do not emphasize these critical elements. The study also points to the significant proportion of lifeguards who missed drowning scenarios at baseline, underscoring the urgent need for improved training. Future research should explore the potential of animated tools in training and further investigate the cognitive mechanisms that underpin effective drowning detection.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103741"},"PeriodicalIF":2.5,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of physical exertion on workers safety awareness: A biosensing and eye-tracking study 体力消耗对工人安全意识的影响：一项生物传感和眼动追踪研究

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-04 DOI: 10.1016/j.ergon.2025.103737

Shashank Muley , Chao Wang , Fereydoun Aghazadeh

{"title":"Effect of physical exertion on workers safety awareness: A biosensing and eye-tracking study","authors":"Shashank Muley , Chao Wang , Fereydoun Aghazadeh","doi":"10.1016/j.ergon.2025.103737","DOIUrl":"10.1016/j.ergon.2025.103737","url":null,"abstract":"<div><div>Construction's unique occupational health and safety challenges manifest from workers' exposure to stressful and hazardous conditions, impairing their cognitive abilities to identify and eliminate risky situations. Physical stress imposed as physical exertion is a major workplace stress category that impacts construction workers' safety behavior. While previous studies have demonstrated the effect of physical exertion on workers' hazard recognition and safety performance, research gaps persist regarding the direct impact of physical exertion on workers' physiological responses and near-miss recognition performance. This study investigates workers' ability to recognize near-miss incidents using an eye-tracking experiment conducted in controlled non-stress and physical stress (overexertion) conditions. Thirty-five participants were exposed to near-miss scenarios from construction sites. Physiological and eye-tracking matrices measured their bio signals and safety behavior during the experiment. The findings from this study reveal that physical overexertion triggered by manual material handling activity can adversely affect worker safety behavior and cognitive ability toward near-miss recognition. Visual attention toward near-miss scenarios was reduced by 39.43 % post-exposure to physical exertion. Additionally, physiological data collected using wearable sensors shows a significant statistical association with near-miss recognition of participants. Individuals with low neuroticism and extraversion showed the highest reduction in recognition performance post-exposure to physical exertion. The study confirms the significant impact of fatigue on reducing workers' efficiency in identifying near-misses, suggesting avenues for developing overexertion relief assessment systems using wearable sensors. Additionally, personality-based safety worker allocation models could aid in recruiting and training workers with lower recognition abilities.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103737"},"PeriodicalIF":2.5,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Validation of markerless vision-based motion capture for ergonomics risk assessment 基于无标记视觉的人体工程学风险评估的动作捕捉验证

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-04-04 DOI: 10.1016/j.ergon.2025.103734

Armin Bonakdar , Negar Riahi , Maryam Shakourisalim , Linda Miller , Mahdi Tavakoli , Hossein Rouhani , Ali Golabchi

{"title":"Validation of markerless vision-based motion capture for ergonomics risk assessment","authors":"Armin Bonakdar , Negar Riahi , Maryam Shakourisalim , Linda Miller , Mahdi Tavakoli , Hossein Rouhani , Ali Golabchi","doi":"10.1016/j.ergon.2025.103734","DOIUrl":"10.1016/j.ergon.2025.103734","url":null,"abstract":"<div><div>Work-related musculoskeletal disorders impact millions annually, often due to awkward postures and heavy lifting. Vision-based markerless optical motion capture (ML-OMC) systems have gained attention as a possible solution for identifying ergonomic risks in workplace settings. However, their reliability remains unknown compared to marker-based optical motion capture (MB-OMC) and inertial measurement units (IMUs). This study reports on a comparative analysis of an ML-OMC against MB-OMC and IMUs and its suitability for joint reaction force estimation. Eight participants performed lifting, a task considered physically demanding among manual handling activities, while their joint angles were recorded using the three measurement systems, and joint reaction forces were determined using joint angle data and ground reaction forces through biomechanical modeling. Furthermore, postural ergonomic assessment scores were computed for the lifting initiation posture of the activity using data from the three systems and biomechanics experts’ inputs. The back angle obtained by ML-OMC exhibited a strong correlation (0.95) with both MB-OMC and IMUs, along with small RMSE values of 6.5° and 9.9° compared to the readouts from MB-OMC and IMUs, respectively. The L5-S1 joint reaction forces obtained by ML-OMC showed a high correlation (0.91 with MB-OMC and 0.85 with IMUs), and small RMSE and normalized RMSE values. Additionally, postural ergonomic assessment scores obtained from ML-OMC aligned with MB-OMC for 87 % of participants, showing significant consistency compared to the notable variation seen with expert-derived scores. These findings underscore the potential of ML-OMC as a dependable in-field ergonomic risk assessment tool for preventing work-related musculoskeletal disorders.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103734"},"PeriodicalIF":2.5,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cognitive workload assessment during VR forklift training VR叉车培训过程中的认知工作量评估

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-03-27 DOI: 10.1016/j.ergon.2025.103718

Saman Jamshid Nezhad Zahabi, Md Shafiqul Islam, Sunwook Kim, Nathan Lau, Maury A. Nussbaum, Sol Lim

{"title":"Cognitive workload assessment during VR forklift training","authors":"Saman Jamshid Nezhad Zahabi, Md Shafiqul Islam, Sunwook Kim, Nathan Lau, Maury A. Nussbaum, Sol Lim","doi":"10.1016/j.ergon.2025.103718","DOIUrl":"10.1016/j.ergon.2025.103718","url":null,"abstract":"<div><div>Virtual Reality (VR)-based training offers a safe and engaging environment for training forklift operators. Given the complexity of forklift operation, monitoring the cognitive workload of novice operators in these virtual settings is essential for optimizing the training process. This study investigated cognitive workload variation during a VR-based training for forklift operators due to varying levels of task difficulty and repeated training. Twenty novice participants completed two sessions in a VR simulator with each session including three forklift driving lessons at three difficulty levels. Perceived workload (NASA-TLX) and normalized encephalographic (EEG) activity were employed to assess cognitive workload. Five of the six NASA-TLX subscales and EEG activity in three distinct frequency bands (theta, alpha and beta) all significantly increased with increasing task difficulty. However, we did not observe significant changes in cognitive workload as measured by EEG in the second training session, highlighting a potential limitation in using EEG to track workload variations across days. Perceived workload and EEG measures showed moderate, positive correlations. Our results highlight the potential of EEG for real-time monitoring of workload during VR-based forklift training, particularly in differentiating tasks of varying difficulty. While more research is needed to confirm measurement consistency across sessions, this capability could facilitate worker monitoring to deliver timely alerts or assistance when workload levels exceed optimal thresholds.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103718"},"PeriodicalIF":2.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating dynamic external hand forces during overhead work with and without an exoskeleton: Evaluating an approach using electromyography signals and random forest regression 在有外骨骼和没有外骨骼的头顶工作中估计动态外力：使用肌电信号和随机森林回归评估方法

IF 2.5 2区工程技术

International Journal of Industrial Ergonomics Pub Date : 2025-03-19 DOI: 10.1016/j.ergon.2025.103735

Mohamad Behjati Ashtiani , Aanuoluwapo Ojelade , Sunwook Kim , Maury A. Nussbaum

{"title":"Estimating dynamic external hand forces during overhead work with and without an exoskeleton: Evaluating an approach using electromyography signals and random forest regression","authors":"Mohamad Behjati Ashtiani , Aanuoluwapo Ojelade , Sunwook Kim , Maury A. Nussbaum","doi":"10.1016/j.ergon.2025.103735","DOIUrl":"10.1016/j.ergon.2025.103735","url":null,"abstract":"<div><div>We developed a model to estimate hand contact forces during dynamic overhead tasks completed with and without passive arm-support exoskeletons (ASEs). One approach to assessing ASE effectiveness is evaluating shoulder joint forces through inverse dynamics, which requires data on both external kinetics and body kinematics. However, obtaining the former (e.g., hand contact forces) is challenging. To address this, our model estimates these forces using electromyographic (EMG) signals. For model development, we used data from a study in which participants completed dynamic overhead task simulations under various conditions, both with and without three ASEs. A random forest regression was used to map EMG signals to time series of hand contact force, considering task conditions and biological sex. Overall, the model produced reasonable force estimations, with errors generally consistent across conditions and regardless of ASE use. However, the model tended to underestimate peak forces, especially for upward <em>vs.</em> forward exertions and among males <em>vs</em>. females. Overall, the proposed model has the potential to support musculoskeletal modeling for assessing the effect of ASE use on workers. We provide several suggestions for improving future model performance.</div></div>","PeriodicalId":50317,"journal":{"name":"International Journal of Industrial Ergonomics","volume":"107 ","pages":"Article 103735"},"PeriodicalIF":2.5,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0