Ergonomics最新文献

An uncontrolled vehicular population escalates distraction and affects mental wellness due to ambient noise, profoundly affecting the academic landscape. This study investigates the significant influence of ambient noise on schoolchildren's learning, attention, and cognition, underscoring the critical challenges and potential limitations it poses to their academic progress. Cognitive assessments were conducted under prevailing noise and controlled conditions. Noise levels (L_Aeq, L₉₀, L₁₀) were measured using a sound level metre (Kimo dB300) in classrooms of ten roadside schools. Findings reveal that noise levels exceed WHO thresholds for classroom environments. Statistical analyses (z-test, paired t-test, ANOVA, regression analysis) indicate significant differences in noise levels and cognitive test scores between both noise exposure conditions. Schools S8 and S10 showed a remarkable 15% improvement in cognitive test scores when transitioning from noisy to silent conditions. Noise disproportionately affected students aged 11-13, particularly boys. Effective noise control measures were suggested to create conducive learning environments.

One goal of automated driving is to mitigate risks by minimising human intervention. However, widespread acceptance of automated vehicles hinges on their perceived ease of use, particularly during takeover scenarios. This online survey investigates the perceived difficulty of takeover in Level 3 Automated Vehicles, focusing on factors influencing takeover performance such as duration of automated mode and traffic density, as well as Non-Driving-Related Tasks like listening to music or engaging in conversation. Using Anderson's experimental protocol based on Integrated Information Theory, 235 drivers aged 18-72 rated takeover difficulty across 32 realistic scenarios varying in these factors. Results indicate significant impacts of all factors on takeover perception, identifying three distinct driver profiles: takeover averse, adaptive, and confident. Findings underscore implications for vehicle acceptance and risk management in automated driving.

The 'Sit-Stand e-Guide' e-training program, designed to promote appropriate use of sit-stand workstations (SSWs), was evaluated for usability, acceptability and impact on various outcomes among SSW users. Participants from a large municipal organisation (25% male; mean age 45 [SD = 10.6] years) completed questionnaires pre-training (T0, n = 57), immediately post-training (T1, n = 50), and four weeks (T2, n = 46: primary endpoint) and twelve months later (T3, n = 30). High usability, acceptability and usefulness scores were reported at T1. Median [IQR] knowledge (4.4/5 [0.9]) and confidence (4.6/5 [1.0]) significantly increased at T1 compared to baseline (2.8 [1.2]; 3.3 [1.4]) and maintained at T2 and T3. At T2, mean [SD] sitting time (5.3 [1.2] h/workday) and low back discomfort (2.4 [2.3]) significantly decreased compared to baseline (6.1 [1.3] h; 3.4 [2.5] discomfort), SSW usage increased (1.4 [1.4]-2.8 [1.7] transitions), with no significant changes in work performance. Some behavioural changes were sustained at T3. The Sit-Stand e-Guide was acceptable and effective; evaluation across diverse workplaces and workers is now needed.

This paper presents analyses of anthropometric measurements of Ethiopian young men aged 18-30 years and draws implications for the improvement of the fit of readymade clothing. Thirty-five anthropometric dimensions of 4022 subjects were measured according to ISO 8559:2017. The anthropometric dimensions were described with mean, standard deviation, and some percentiles. Differences in the anthropometric measurements with the body mass index (BMI) and ethnicity of the subjects were examined by analysis of variances. Furthermore, differences in some anthropometric measurements from that of Indian and Greek young men of similar ages were tested by one-sample t-tests. The result showed that the average BMI of the subjects was 20.63 which is normal. Statistically significant mean differences were observed among the subjects with different BMIs and ethnicities in most of the anthropometric dimensions. The anthropometric measurements of the subjects were mostly larger than the Indians and smaller than the Greek men.

Preserving human well-being has become challenging for businesses, which continue efforts to overcome managing business processes concurrently, due to the cumulative effects of psychosocial risks at work that may seriously impair one's health. By focusing on this need, this paper proposes a more effective and realistic way of measuring job satisfaction comprising psychosocial risks by integrating multi-criteria decision-making (MCDM) methodology. Simplified PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA-S), i.e. the selected MCDM method, is used for weighting domains based on the opinions of employees working for a company in Türkiye, who also provide their attitudes towards job satisfaction through 36 items of Job Satisfaction Survey (JSS). This paper uses nine subscales of JSS to represent domains relevant to psychosocial risks. Three developed scenarios discuss the effectiveness of the proposed subscale-weighted job satisfaction measurement by presenting the subscales having different ranges in standard scores relative to the subscale-weighted scores.

The COVID-19 pandemic necessitated the implementation of lockdown measures, resulting in children attending classes from their homes through online platforms. This study aimed to examine the impact of studying at home on children by investigating various aspects related to their study environment. Data were gathered through two questionnaires administered in Jordan: One targeted children aged 8-15 year through interviews, while the other targeted parents with at least one school-aged child through an online survey. The interview-based survey (N = 152) identified significant factors such as the study location, excessive use of computer peripherals, and physical discomforts like back, hand, and ear pain. Similarly, the parent survey (N = 1,152) revealed various significant factors including parents' monthly income, educational level, occupation, living area, sources of COVID-19 information, fear of the virus, TV time, eating and reading habits, smartphone usage, difficulty in concentrating while studying, engagement with social media, internet usage, elbow position, and eye protection.

Extensive evaluations exist concerning the linkage between objective task demands and subsequent effects on user performance. However, the human user also experiences a range of emotions related to external task demands. Problematically, little is known about the associations between emotional valence, and arousal associated with the task demand-performance axis. In this paper, we advance a theoretical model concerning such interactive influences using three dimensions: (1) emotional valence, (2) arousal, and (3) task demand. The model evaluates the impact of these dimensions on user performance. It also identifies critical emotional user states, particularly those resulting in negative performance effects, as well as non-critical emotional states that can positively impact performance. Finally, we discuss the implications for affect-adaptive systems that can mitigate the impact of critical emotional states while leveraging the benefits of non-critical ones.

Consumer behaviour changes and strategic management decisions are driving adaptations in manufacturing routines. Based on the theory of situational strength, we investigated how contextual and person-related factors influence workers' adaptation in a two-worker position routine. Contextual factors, like retrieval cues (Study 1), time pressure (Study 2), and convenience (Study 3), were varied. Person-related factors included retentivity, general and routine-specific self-efficacy, and perceived adaptation costs. Dependent variables included various error types and production time before and after adaptation. In each study, 148 participants were trained in a production routine at t1 and executed an adapted routine at t2, one week later. Repeated measures ANOVA for performance at t1 and t2, and MANOVA for performance at t2, revealed that time increased for all groups at t2. For participants in Studies 1 & 2, error rates remained consistent. Retentivity significantly impacted errors at both t1 and t2, emphasising that routine changes in a 'running business' take time, regardless of contextual factors. Workers with lower retentivity may require additional support.

The use of occupational exoskeletons has grown fast in manufacturing industries in recent years. One major scenario of exoskeleton use in manufacturing is to assist overhead, power hand tool operations. This preliminary work aimed to determine the effects of arm-supporting exoskeletons on shoulder muscle activity and human-hand tool coupling in simulated overhead tasks with axially applied vibration. An electromagnetic shaker capable of producing the random vibration spectrum specified in ISO 10819 was hung overhead to deliver vibrations. Two passive, arm-supporting exoskeletons, with one (ExoVest) transferring load to both the shoulder and pelvic region while the second one (ExoStrap) transferring load primarily to the pelvic region, were used in testing. Testing was also done with the shaker placed in front of the body to better understand the posture and exoskeleton engagement effects. The results collected from 6 healthy male subjects demonstrate the dominating effects of the overhead working posture on increased shoulder muscle activities. Vibration led to higher muscle activities in both agonist and antagonist shoulder muscles to a less extent. Exoskeleton use reduced the anterior deltoid and serratus anterior activities by 27% to 43%. However, wearing the ExoStrap increased the upper trapezius activities by 23% to 38% in the overhead posture. Furthermore, an increased human-shaker handle coupling was observed in the OH posture when wearing the ExoVest, indicating a more demanding neuromuscular control.

The affective experience generated when users play computer games can influence their attitude and preference towards the game. Existing evaluation means mainly depend on subjective scales and physiological signals. However, some limitations should not be ignored (e.g. subjective scales are not objective, and physiological signals are complicated). In this paper, we 1) propose a novel method to assess user affective experience when playing single-player games based on pleasure-arousal-dominance (PAD) emotions, facial expressions, and gaze directions, and 2) build an artificial intelligence model to identify user preference. Fifty-four subjects participated in a basketball experiment with three difficulty levels. Their expressions, gaze directions, and subjective PAD emotions were collected and analysed. Experimental results showed that the expression intensities of angry, sad, and neutral, yaw angle degrees of gaze direction, and PAD emotions varied significantly under different difficulties. Besides, the proposed model achieved better performance than other machine-learning algorithms on the collected dataset.