International Journal of Industrial Ergonomics最新文献

The Black Hole Illusion (BHI) is a nighttime aviation landing illusion where pilots overestimate their descent angle. This dangerous illusion can cause pilots to compensate by flying lower than intended, which can result in them crashing into the ground or obstacles in front of the runway. A common interpretation of the BHI is that it is a perceptual illusion, and two quantitative perception based theories have been proposed. The first theory was developed by Perrone (1983), and it assumes that pilots misestimate their descent angle due to the loss of contextual information surrounding the runway, such as ground texture, during nighttime landing conditions. Adapted from work by Galanis et al. (1998) and Robinson et al. (2020), the second (eye-level) theory assumes that pilots misestimate their descent angle due to loss of the horizon during nighttime landing conditions. Quantitative analyses of Perrone's theory suggest that the magnitude of the illusion should vary with runway width and length in nighttime conditions, but in daylight conditions there should be no illusion and no effect of runway width or length. Analyses of the eye-level theory predict no impact of runway width or length for any condition. Across two empirical laboratory studies, we do demonstrate a BHI for nighttime evaluations of descent angle, but the data do not support either theory. Thus, the two algorithms analyzed here are not sufficient to explain the BHI; and the BHI may reflect general disorientation due to limited information.

Multiple incidents in the offshore oil and gas industry have been associated with poor safety culture. Regular assessments of safety culture among operators and contractors is recommended as part of a safety management system. Poor safety culture has also shown to impact how operators manage offshore hazards, such as worker fatigue. Assessing workers' fatigue states is also critical to ensure safety in the offshore oil industry. This paper describes findings from an interview study that aimed to identify current safety culture assessment and worker fatigue management practices in the offshore oil and gas industry. One-hour virtual semi-structured interviews were conducted with eighteen offshore oil rig supervisors. Various state-of-the-art methods for assessing safety culture (e.g., experience sampling method) and worker fatigue (e.g., physiological sensors and psychomotor vigilance test) were introduced to the participants. Participants commented on the feasibility and potential barriers to implementation/administration of the various methods, as well as how the information might be useful in their supervisory decisions. User expectations for a safety dashboard displaying data from such tools and user requirements for such a dashboard were elicited. In addition, participants completed a modified technology readiness and acceptance model questionnaire to assess participants' readiness levels and perceived usefulness of a safety dashboard. The interview results revealed a mixed understanding of what safety culture is and opinions about safety culture measurements. Participants indicated that efforts to manage fatigue currently relied solely on supervisors' observation and workers' self-reports. Participants’ opinions about the new assessment methods varied. Some were supportive and commented that the new methods will be helpful to improve supervisory-level decisions, whereas others pointed out potential compliance issues.

Lack of the biodynamic data of lightweight and heavyweight human bodies in seating posture becomes an impediment to developing dynamic dummies and relevant standards for improving vehicle ride comfort and reducing health risks caused by vibration. To acquire missing data and gain an understanding of relevant biodynamic responses, the vertical apparent masses of seated subjects in lightweight and heavyweight groups as well as the mediumweight group (targeted mass 55 kg, 98–115 kg, and 75 kg) were experimentally measured and studied under 9 vibration magnitudes (0.25, 0.315, 0.4, 0.5, 0.63, 0.8, 1.0, 1.25 and 1.6 ms⁻² r.m.s. with a common ratio of ca. 1.25) without and with the support of an upright backrest. Each group had twelve subjects. With an increase in the vibration magnitude from 0.25 to 1.6 ms⁻² r.m.s., the resonance frequency of the vertical apparent mass showed a decreasing trend. This was observed with all three bodyweight groups and two backrest conditions. Results of pairwise Wilcoxon signed-rank tests showed that, when the vibration magnitude increased by a factor of ca. 1.25, its effect on the resonance frequency was statistically insignificant in most cases. The results provided data on the vertical apparent mass for the heavyweight subjects that have not been reported and augmented the database of those for the lightweight subjects.

Significant difference exists in spatial fitness and perception between elderly and non-elderly drivers. However, due to dynamic and real-time changes in human subjective feelings and joint movements, two-dimensional human body templates and human-machine simulation software are not enough to obtain necessary space parameters. In this study, seven key dimensions of the legroom were measured thrice and averaged, in the situation that the seat and posture are comfortable. Such anthropometric data can reflect dynamic perception that may change due to personal emotions and environmental influences. Extreme learning machine (ELM) was adopted to build a prediction model of leg space discomfort degree, and the influence of the activation function and the number of hidden layer neurons on the prediction accuracy of the model were analyzed. In addition, a multiple linear regression (MLR) model was established with the discomfort score as the dependent variable and the seven key dimensions as the independent variables. The results indicated that the ELM model could effectively predict elderly drivers’ discomfort degree (MSE = 0.182, MRE = 9.364, R² = 0.869) by learning the dimensions of the seven key positions. The MLR model (R² = 0.861) did not perform as well as ELM. However, the regression coefficients could reflect the degree to which each dimension affects the discomfort degree of leg space for elderly drivers. The conclusions could function in elderly-oriented in-vehicle space arrangement and driving risk assessment of elderly people.

With the continuous development of human-computer interaction technologies and the widespread use of graphical interfaces, icons that represent various objects and functions have a particularly important role. This study investigates the effect of semantic distance of icons on cognitive performance through an eye-movement-based experiment which involves a visual search for icons. The findings show that the semantic distance of icons has a significant effect on cognitive performance. A higher cognitive performance is found with semantically close icons which can better capture user attention. In addition, we use eye-movement indicators that are highly correlated with semantic distance, including mean pupil diameter, mean gaze duration and initial gaze time of an AOI, and analyze the objective relationship between these three eye-movement indicators and the semantic distance of icons to establish a dataset. The dataset is used as input for a Gradient Boosting Decision Tree (GBDT), which is a machine learning-based method for classifying the semantic distance of the icons in this study. The output of the GBDT model is classifying the semantic distance as far and close, and the experimental results show that the accuracy of the model reaches 84.28% after a comparison with other types of classifiers, which is in good agreement with the experimental results. Therefore, the model can address the relevant application requirements and simplify the evaluation process of icons to a certain extent, which has great significance in the field of icon design.

Neck pain is one of the most prevalent painful conditions among professors. Covid-19 has led to significant changes in work organization, with remote work becoming predominant even after the pandemic. Home office obliged to use information technologies for a longer duration, give classes at distance, and adjust workstations with consequences on neck musculoskeletal symptoms (MSS). The aim of this study was to characterize the determinants of neck MSS among university professors from Brazilian Universities, in two moments, during Covid 19 pandemics.

Two cross-sectional studies were based on an online survey applied to university professors in 2020–21 and 2021–22. The samples included 220 professors in the first moment and 180 in the second one. A logistic regression model considering Cervical Musculoskeletal Symptoms in the last 12 months as the dependent variable was adjusted for each data collection period.

According to the model for the period 2020–21, the log of the odds of a professor who has neck MSS in the last 12 months was positively related with having multisite musculoskeletal symptoms, duration of work in a seated posture superior to 6 h, teleworking or using a hybrid format, having two or more dependents, self-report diseases and stress perception. For the period 2021–2022, was positively related with having multisite musculoskeletal symptoms, and age over 50 years; negatively related with the mean duration of work per week.

The knowledge of protective and risk factors has an important role in the definition of preventive strategies and the design of home office by the universities.

Objective

Using machine learning techniques, we have developed an interactive exercise training system to assist individuals aged 55 years or over with knee pain to perform lower-limb exercises to improve their knee health. The system has three features: video-based exercise demonstrations, real-time feedback on exercise movements, and tracking of exercise performance and progress. The current study aimed to evaluate the design of the computer prototype of the system, and determine its usability and end users’ intention to use it (i.e., acceptance of it).

Methods

Heuristic evaluation and end-user testing of the computer-based prototype system were conducted. Three human factors practitioners identified the design deficiencies, with reference to 64 design principles. In addition, 10 individuals with knee pain were recruited to use the prototype system to complete five tasks in the study laboratory. We recorded and examined the task success rate, number of requests for assistance, difficulties encountered during tasks, and perceptions of usability and acceptance.

Results

Four design deficiencies were identified, regarding recognition and recovery of errors, navigation, auditory perception, and help documentation. Most participants had difficulty in calibrating the camera and performing exercises. However, in general, the prototype system was perceived as usable and acceptable.

Conclusions

The use of heuristic evaluation and end-user testing revealed the capacity to systematically detect design deficiencies in interactive self-help systems, allowing for effective system adjustments. Moreover, our system shows potential for individuals managing knee pain, but conducting iterative usability testing is necessary to identify additional improvements. Furthermore, several design propositions have been submitted.

The construction industry is widely acknowledged as hazardous in nature, requiring proactive measures to mitigate accidents and minimize fatalities. While hazard recognition is recognized as a key preventive measure, research gaps persist regarding the impact of workers' personalities on near-miss identification. This study aimed to investigate the influence of the big five personality traits on construction workers' recognition of the Fatal-four near-miss incidents. Using an eye-tracking experiment conducted in a controlled environment, 35 participants were exposed to 16 well-balanced near-miss scenarios derived from actual construction sites. Participants completed self-reported questionnaires to assess their personality traits, and their near-miss recognition performance was recorded and analyzed using a wearable eye tracker. The findings revealed a significant correlation between openness/intellect and workers' attentiveness indicators. Notably, individuals with higher scores in openness/intellect displayed enhanced attentiveness during the task. Moreover, the influence analysis demonstrated that workers with low conscientiousness and low openness/intellect exhibited a higher frequency and earlier attention to Fatal-four near-miss opportunities within the presented images. This study provides empirical evidence on the relationship between personality traits, attentiveness, prioritization, and near-miss incidents in the construction industry. The results open avenues for developing personalized safety training programs tailored to individuals with lower near-miss identification abilities, thereby fostering robust safety culture within the construction sector.

X-ray screening of passenger baggage at airports is performed in different work settings. In local cabin baggage screening (LCBS), airport security officers (screeners) analyse X-ray images of passenger bags at the checkpoints where they are exposed to noise and social stress from passengers. In remote cabin baggage screening (RCBS), screeners work in remote, quiet, and office-like environments. The primary aim of this study was to compare the screening performance in LCBS and RCBS. In addition, we examined the effects of time on task and task load in both work settings. Using linear mixed models, we analysed threat image projection (TIP) data from 1706 screeners collected over two years (669,168 TIP events). The results showed better detection of prohibited articles (higher hit rate) and longer processing times in RCBS than in LCBS. In both settings, we found a decrease in the hit rate with increasing time on task, and this decrease was stronger when the task load was high. Interestingly, the effects of work setting, time on task, and task load were relatively small compared with the inter-individual differences in performance across screeners.

This study investigates the relationships between visual form attributes (height, shape, and curvature) and product perception, particularly exploring the dynamic interplay between formal aesthetics and product semantics. The challenge of effectively incorporating formal aesthetic characteristics into the design process is addressed by adopting Gestalt theory as a guiding framework. Drawing on the Gestalt principle of Prägnanz, this research investigates the role of primary visual attributes of form on perceived Complexity, Symmetry, Harmony, and Regularity of kettle images. A central aspect of this investigation is the recognition of a product's form, which possesses the potential to influence the symbolism associated with the product's personality traits attributed by users. To this end, the study aims to acquire deeper insights into the perception of familiarity, prototypicality, beauty, and attractiveness to comprehensively analyze the overall product perception while unravelling the underlying significance of emotional responses through the product's personality. The goal of this study is to deconstruct the form attributes exhibited by eight kettles of various designs. By doing so, we seek to understand how these form attributes synergistically contribute to creating a unified perceptual whole to convey a specific character or identity. The findings offer insights into the influence of form on a product's aesthetic perception and perceived personality and how form contributes to a product's symbolic meaning. By grasping the intricacies of product perception, designers can create products that cater to the diverse needs of different user groups, ultimately leading to increased market acceptance and commercial success.