Human Factors and Ergonomics in Manufacturing & Service Industries最新文献

Sports bras function as a form of personal protective equipment, designed to minimize breast motion and pain. The sports bra design significantly affects breast support and discomfort. Although the use of underwire has been shown to enhance bra support, no quantitative data related to the relationship between underwire properties and bra performance has been published to guide designers and manufacturers in selecting underwire. This study aimed to quantitatively examine the relationship between underwire rigidity and breast motion and discomfort. Ten participants were recruited to perform treadmill running under six bra conditions: one without underwire and five with underwires of varying levels of rigidity. A decreasing trend was observed in vertical breast displacement, perceived breast movement, and discomfort as underwire rigidity increased. Significant exponential relationships were identified between underwire rigidity and vertical breast displacement. However, no significant associations were found for perceived breast movement and perceived breast discomfort. These findings underscore the importance of selecting appropriately rigid underwires for sports bras, under the tested conditions (young women with bra size 75 C performing treadmill jogging/running at 7.5 and 10 km/h using the same bra model), offering valuable insights into the design and manufacturing of sports bras in the underwear industry.

Personalization in the workplace may be used to support workers by simplifying tasks or reducing workload, but requires the collection of personal data, and this raises concerns over privacy and possible discrimination if applied indiscriminately. The study explored the factors associated with acceptance of three types of workplace personalization system (Suggester, Swappers and Controller, within-subjects) and two personal data types (Heart Rate, Performance, between-subjects) by presenting vignettes using an online experimental platform (Prolific.com) and capturing respondents' (n = 204) attitudes using recognized acceptance questionnaires (e.g., the Advanced Transport Telematics Acceptance Assessment, [ATTAA]). Results show acceptance is influenced by the type of personalization system, particularly when physiological (heart rate) data is used, with “Swapper” systems receiving the highest ratings for “Usefulness” and “Satisfying” (interpreted as higher acceptance) compared to suggesters and controllers. Acceptance ratings were not significantly different between personalization types when performance data were used. The Affinity for Technology (AFT) and Need for Cognition (NFC) scales were used to categorize participant characteristics, but only revealed significant differences associated with NFC and usefulness—most notably when using performance data. Overall, the results support the need to consider the type of intervention and the type/amount of personal data required when designing and implementing workplace personalization systems and highlight a particular need for caution when physiological data is required.

With the increasing application of robots in industrial manufacturing, ensuring the safety of robots designed for close-proximity human-robot collaboration (HRC) has become paramount. Trust is a critical factor influencing human-perceived safety and is essential for sustainable HRC. However, the integration of trust-related influences into safety strategies for close-proximity HRC remains underexplored. This study aims to investigate safety control mechanisms centered around human trust in robots within close-proximity HRC environments. Task performance and safety performance are considered as key factors affecting trust, and Bayesian inference is employed for human trust assessment. Additionally, the concept of a danger field (DF) is introduced, and the DF calculation formula is refined to enhance robot danger assessment. Building on trust and danger assessments, a safety control strategy is designed by integrating the relationship between trust and safety. To validate the effectiveness of this strategy, a scenario is constructed in the Virtual Robot Experiment Platform where a digital human and a UR5 robot collaboratively transport goods, and the safety system is subsequently integrated to conduct simulation experiments. The results indicate that the implementation of the safety control strategy leads to a reduction in peak robot joint speed, a significant decrease in the maximum, mean, and variance of danger assessment values, and a rapid response capability to shut down the system under high-risk conditions. These findings confirm the reliability of the proposed safety control framework.

Safe surgical practice depends on both technical expertise and strong non-technical skills. Scrub nurses play a key role in the operating room, yet their performance may be affected by high mental workload. This cross-sectional study evaluated non-technical skills and mental workload among 200 scrub nurses in five educational hospitals in 2025. Data were collected using the NASA-TLX and SPLINTS tools. Results showed that while scrub nurses had generally good non-technical skills, they also experienced high mental workload. Among female nurses, higher frustration levels were linked to lower performance in assertiveness and information recognition. In nurses with temporary employment, greater mental demand correlated positively with some skill components. Older, more experienced nurses scored lower in information gathering. As the scores of mental workload domains are negatively correlated with scrub nurses' non-technical skills domains, targeted strategies to reduce mental workload may improve non-technical skills performance. Further research is recommended for exploring these results.

This study aims to examine how digital addiction based experiences of employees influence attention processes, safety awareness, and collective responsibility in the workplace. It particularly seeks to identify challenges in digitally intensive environments regarding cognitive load, behavioral reflexes, and institutional risk communication. The research employed a phenomenological design with semi- structured interviews conducted with 19 employees from various sectors across Turkey. Criterion sampling was used, and interviews continued until data saturation was reached. All interviews were audio recorded, transcribed verbatim, and analyzed using Colaizzi's (1978) seven step method. Reporting followed the COREQ checklist to ensure rigor and transparency. Thematic analysis revealed three main themes: Cognitive Load and Deterioration in Safety Perception, Behavioral Disconnection and Erosion in Safety Attitudes, and Organizational Silence and Collective Collapse in Risk Awareness. These findings show that digital addiction negatively affects attention, reflexes, safety behaviors, and institutional reporting processes. Digitalization influences not only work efficiency but also employees' safety behaviors and organizational risk communication. Constant digital stimuli cause distraction, disrupt safety practices, and weaken collective responsibility. The study provides insights into how digital addiction transforms workplace safety culture and recommends comprehensive prevention strategies for employers, managers, and policymakers.

Anthropomorphic avatars serve as a key tool to humanizing chatbots. This study aimed to investigate the effects of four specific anthropomorphic visual design—human avatars, caricatured avatars, zoomorphic avatars, and functional avatars—on users' first impressions of customer service chatbots. A combination of subjective evaluation and eye-tracking methods were employed to capture users' initial responses. The results revealed that the anthropomorphic nature of chatbot avatars influences users' perceptions of whether the chatbot is human or artificial intelligence, with more human-like designs increasing the likelihood of being categorized as human. Both human and caricatured chatbot avatars enchanced perceptions of warmth, competence, social presence and trust, whlie also generating higher fixation counts and longer fixation durations compared to the other two avatar types. In conclusion, anthropomorphic avatar play a critial role in shaping users' subjective impressions and visual engagement with customer-service chatbots. A key implication of this study is that chatbot avatars should incorporate a high degree of anthropomorphism to foster positive first impressions among users. However, given the privacy concernss associated with using real photos, it is not necessary to use images of actual individuals. Instead, caricatured avatars can effectively enhance users' first impressions while mitigating potential drawbacks of hyper-realistic designs, such as uncanny valley effects or mismatched user expectations. Furthermore, this study demonsterates the feasibility of using eye-tracking tools to evaluate avatar designs in customer-service chatbots.

Considering the COVID-19 pandemic, understanding the behavior of social groups on crosswalks has become increasingly important. This field study aims to investigate the dynamic behavior of pedestrian groups crossing streets during the pandemic. By analyzing the movement patterns and behaviors of group under different conditions, we aim to provide insights into how crosswalk infrastructures can be improved for a safer and more efficient pedestrian experience during the pandemic. An observation experiment was conducted at a crosswalk near Shinjuku Station in Japan in 2021. Trajectories of 296 groups were analyzed with up to five members, examining their velocity characteristics and spatial relations. Our findings reveal several important insights. First, the group size affects the average speed and speed difference of group members, and that the width of the crosswalk is positively correlated with the average speed of group members. Second, the group size is uncorrelated with mean inter-distance of members, regardless of group size. However, the farther members are from the leader, the greater the average distance between adjacent members. Third, distinct group shapes for groups of different sizes. Groups of three people form a V shape, while groups of four people form a U shape, and groups of five people form a trapezoid shape. Finally, the group size is correlated with the average offset angle of group members in the northbound scenario. Larger groups tend to have smaller average offset angles, making them more likely to choose the shortest route. Overall, this study is a crucial step in developing safety-oriented walking modeling tools for pedestrians at intersections. It also has important implications for predicting pedestrian crossing behavior and show how human factors and ergonomics methods can be used to improve urban public infrastructure systems in densely populated countries, such as Japan.