Ergonomics最新文献

The way the road transport system is developed in a country affects safety. This study aims to identify the roles and relationships of road transport stakeholders and to explore the understanding of control and feedback mechanisms and associated gaps influencing road safety. A System-Theoretic Accident Model and Processes (STAMP) model was applied to document and interview data (n = 30). Participants emphasised the hindrance of overlapping mandates among stakeholders on the road transport system's operations and underlined the roles of coalitions for road safety as system enablers. Further, the withdrawal of some controls by international agencies can increase system vulnerability. Most importantly, critical control and feedback gaps were shown to increase risks for safety within the road transport system. The findings underscore the complexity of the road transport system and add to the discussion on a system's approach to road safety.Practitioner summary: Using a STAMP methodology, we extensively studied the road transport system in Tanzania. Road transport stakeholders were identified through the review of documents, interviews were conducted, and the main findings were discussed. Control and feedback mechanisms and associated gaps were critically presented, recommendations were proposed, and policy implications were suggested.

Subacromial pain syndrome (SAPS) is the most common upper-extremity musculoskeletal problem among workers. In this study, a machine learning model was built to predict and classify the presence or absence of SAPS in assembly workers with shoulder joint range of motion (ROM) and muscle strength data using support vector machine (SVM). Permutation importance was used to determine important variables for predicting workers with or without SAPS. The accuracy of the support vector classifier (SVC) polynomial model for classifying workers with SAPS was 82.4%. The important variables in model construction were internal rotation and abduction of shoulder ROM and internal rotation of shoulder muscle strength. It is possible to accurately perform SAPS classification of workers with relatively easy-to-obtain shoulder ROM and muscle strength data using this model. In addition, preventing SAPS in workers is possible by adjusting the factors affecting model building using exercise or rehabilitation programs.Practitioner summary: This study aimed to create a machine learning model that can predict and classify SAPS using shoulder ROM and muscle strength and identify the variables that are of high importance in model construction. This model could be used to predict or classify workers' SAPS and manage or prevent SAPS.

Firefighter hoods must provide protection from elevated temperatures and products of combustion while simultaneously being comfortable and limiting interference with firefighting movement or completion of fireground activities. This study was to quantify the impact of hood design (traditional knit hood vs. several models of particulate-blocking hoods) on wearability measures such as range of motion, noise production and hearing threshold. Firefighters' perceptions of wearability were also collected. In a controlled laboratory environment, 24 firefighters performed movement and hearing tests. Wearing particulate-blocking hoods resulted in decreased rotational range of motion, and thicker hoods reduced hearing ability. Design, but not necessarily the number of layers, affected noise production by the hood during head movement.Practitioner summary: Particulate-blocking hoods resulted in reduced rotational range of motion relative to the traditional design and the no-hood condition. Hoods with additional layers resulted in decreased hearing ability. Noise production was increased in designs of particulate-blocking hoods with a membrane-based blocking layer independent of the number of layers.

Self-reported driver behaviour has long been a tool used by road safety researchers to classify drivers and to evaluate the impact of interventions yet the relationship with real-world driving is challenging to validate due to the need for extensive, detailed observations of normal driving. This study examines this association by applying the large UDRIVE naturalistic driving study data involving 96 car drivers, comprising 131,462 trips and 1,459,110 km travelled over a duration of 32,096 hours, to compare individual questions and composite indicators based on the Driver Behaviour Questionnaire with real world driving. Self-reported speed behaviour was compared to the measured values under urban and highway conditions. Generalised Linear Mixed Models were developed to examine the relationships between the observed speed behaviours with DBQ errors and violations scores in conjunction with traffic and environmental factors. Drivers' self-reported data on speed selection seldom aligned with their real-world behaviour and there were no meaningful differences between many of the response categories. The DBQ violations and errors scales showed a highly significant correlation with driving speed indicators however they had a low explanatory power compared to other traffic situational and driving factors. Overall, the study highlights the need to validate self-reported driving data against the accuracy and relevance to real-world driving.

Friction from knitted clothing can cause discomfort and skin issues, underscoring the importance of tactile comfort for wearers. Seamless knitted garments are assumed to be comfortable to wear, yet there is little understanding of their tactile comfort in comparison to linked seams - the most common form of knitted garment. This novel study examines the influence of a garments knitted structural architecture on clothing comfort and wearability by investigating skin friction and tactile perception across ten body regions in both male and female participants, using two commonly utilised materials and seam designs: cotton and merino wool with plain and linked seams. The impact of seam design and regional factors on skin friction and tactile perception was analysed, revealing varying levels across tested body regions. Removing seams exposed a greater surface area to skin contact, leading to higher perceived friction levels. As such, structural elements in knitted garments enhance wearer comfort.

Non-technical skills are recognised as important in various work domains, but have been the subject of debate regarding their role in ergonomics/human factors, given their focus on human behaviour itself rather than the interaction between people and systems. This study aimed to examine the relationship between non-technical skills and the work system in which they are enacted. The study setting was community pharmacies in England. Qualitative data were obtained from observation of seven pharmacists and semi-structured interviews with 16 pharmacists, and subjected to thematic analysis. Elements of their work system were found to be related to their non-technical skills; either by creating a need for the skill in the first place, or by facilitating or inhibiting its enactment. The findings highlight the importance of considering the work system that contextualises individuals' and teams' behaviour, in addition to the behaviour itself, when investigating non-technical skills.

This study evaluated the effects of target sizes on biomechanical and cognitive load and the performance of virtual reality (VR) interactions. In a repeated-measures laboratory study, each of the twenty participants performed standardised VR tasks with three different target sizes: small, medium, and large. During the VR tasks, biomechanical load in the neck and shoulders (joint angles, joint moments, and muscle activity), cognitive load (perceived workload and cognitive stress), and task performance (completion time) were collected. The neck and shoulder joint angles, joint moments, and muscle activities were greater with the large targets compared to the medium and small targets. Moreover, the larger VR targets caused greater temporal demand and longer task completion time compared to the other target sizes. These findings indicate that target sizes in VR interfaces play important roles in biomechanical and cognitive load as well as task performance.

An ergonomics assessment of the physical risk factors in the workplace is instrumental in predicting and preventing musculoskeletal disorders (MSDs). Using Artificial Intelligence (AI) has become increasingly popular for ergonomics assessments because of the time savings and improved accuracy. However, most of the effort in this area starts and ends with producing risk scores, without providing guidance to reduce the risk. This paper proposes a holistic job improvement process that performs automatic root cause analysis and control recommendations for reducing MSD risk. We apply deep learning-based Natural Language Processing (NLP) techniques such as Part of Speech (PoS) tagging and dependency parsing on textual descriptions of the physical actions performed in the job (e.g. pushing) along with the object (e.g. cart) being acted upon. The action-object inferences provide the entry point to an expert-based Machine Learning (ML) system that automatically identifies the targeted work-related causes (e.g. cart movement forces are too high, due to caster size too small) of the identified MSD risk (e.g. excessive shoulder forces). The proposed framework utilises the root causes identified to recommend control strategies (e.g. provide larger diameter casters, minimum diameter 8" or 203 mm) most likely to mitigate risk, resulting in a more efficient and effective job improvement process.

This study investigates the perspectives of Canadian student and licenced pilots on general aviation pilot training and licencing practices. Employing a mixed-methods approach, this research critiques the reliance on flight hours as the sole competence metric and examines the alignment of existing practices with modern aviation's complexities. Findings reveal a divergence in opinions between novice and experienced pilots on flight hours' importance, with a consensus towards a competency-based evaluation model. The study identifies critical shortcomings in existing training practices, such as the challenge of integrating technology, fostering advanced skills, and efficiently utilising instructional resources. It suggests recommendations for regulatory enhancements, aiming to ensure training practices evolve in line with the changing requirements of aviation safety and technology. The conclusion calls for urgent reform, underlining the imperative for training adaptations that can prepare pilots to proficiently manage the complexities of contemporary airspace, thus safeguarding their proficiency and safety.

Ankle-based exoskeletons have demonstrated metabolic benefits during steady-state walking; however, variability exists in individual adaptation timelines necessary to achieve those benefits. This study assessed timelines for metabolic and gait-related adaptation while wearing an ankle-based exoskeleton while powered (EXOP) compared to unpowered (EXNP) and no device worn (NOEX). Metabolic (VO₂) and biomechanics data were collected while 14 participants walked on a treadmill at 1.3 m/s for six sessions. To better understand variability in responses to wearing exoskeletons, the cohort was divided based on the slope of the VO₂ response of the first two sessions in the EXOP condition, and gait parameters were compared between subgroups. Repeated measures analyses of variance revealed a significant (p ≤ 0.001) 10% VO₂ reduction for EXOP compared to EXNP and a non-significant 2.5% reduction for EXOP v NOEX. Lack of significant session-based comparisons indicated no additional VO₂ adaptation; however, significant session-related results for peak knee flexion (interaction, p = 0.042) and step width (session main effect, p = 0.003) suggest gait-related adaptation continued during the sessions. Subgroup results indicated different response profiles to wearing exoskeletons; and implications of classifying initial responses based on metabolic response are discussed as an approach to understand what drives variation in responses to these devices.