Applied Human Factors and Ergonomics Conference最新文献

This study examined the goodness-of-fit of using a sigmoid function to characterize time-series angular displacement trajectories during two-handed anterior lifting. Twenty-six participants performed two-handed anterior lifting with a low (4.5 kg) vs. high (22.7 kg) load at floor vs. knee lifting height. A sigmoid function with three parameters was fit to the torso-thigh included angle, knee flexion-extension (F-E), and ankle F-E angles in the sagittal plane obtained from body-worn inertial sensors. Mean ± SD RMSE between measured vs. fitted trajectories were 3.6 ± 2.9°, 3.9 ± 4.2°, and 2.7 ± 2.8° for the torso-thigh included angle, knee F-E, and ankle F-E angles, respectively. Findings suggest that the sigmoid function adequately describes the trajectory shape of two-handed lifting kinematics. Functional representations facilitate data aggregation and feature extraction in large time-series datasets encountered in inertial-based motion analysis and machine learning applications.

The World Health Organization (WHO) estimates older adults aged 60+ will double by 2050 with 80% living in low to moderate income countries. As remote research studies supported by digital devices increase separation between researchers and participants, it is important to maintain participant trust. Research participants have expressed an interest in accessing both group and individual level results, which are not readily available. To bridge this gap, we engaged residents of a local continuing care senior housing community (CCSHC) to co-design documents used to convey information about study results. The process informed the refinement of informational materials for communicating scientific research that the CCSHC community considers accessible and meaningful.

Doctor-patient communication is a crucial element in effective medical care, and the striking health disparities evident in patients with Type II Diabetes may in part be caused by physicians' difficulties in establishing effective communication with patients who differ from them racially, culturally, and economically. REPEAT (Realizing Enhanced Patient Encounters through Aiding and Training) is a digital tutor developed to help solve this problem. REPEAT teaches and coaches learners to improve their general and disparities-focused clinical communication skills using simulated encounters with computer-generated Synthetic Standardized Patients (SSPs) and augments experiential learning in virtual encounters by applying customized, context-sensitive, learner-focused scaffolding. REPEAT authoring tools enable rapid development of learning content, allowing economical transferability to other domains. Key human factors challenges and their design solution in REPEAT are discussed.

We examined the effects of sleep quality on next day driving outcomes in a 3.5-month naturalistic driving study of 67 OSA and 47 matched control drivers. Sleep quality measures included total sleep time and sleep fragmentation from actigraphy. The driving outcomes included average speed, lateral control, longitudinal control, distraction, attention to driving- and non-driving related tasks. Sleep quality affected next day's driving performance differently for OSA and control drivers. Better sleep quality was associated with better lateral and longitudinal control during highway driving for control drivers. The reverse was true for OSA drivers. Similar effects were also seen in terms of distractions and attention to the driving task. These effects suggest improved sleep leads to greater risky driving and 'activation' among OSA drivers. Collectively, the findings suggest investment in long-term monitoring of sleep quality in commercial vehicle drivers both with and without sleep disorders may help manage safety risks.