Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting最新文献

{"title":"Applying Forces Measured at the Hands to Estimate L5/S1 Compression During Manual Patient Bed-to-Wheelchair Transfers Across Different Levels of Patient Assist","authors":"Jacob J. Banks, Jie Zhou, Chelsea O. Riehle, Neal E. Wiggermann","doi":"10.1177/21695067231192653","DOIUrl":"https://doi.org/10.1177/21695067231192653","url":null,"abstract":"Transferring a patient from a bed to a wheelchair is important for patient well-being. Research has shown that manually performing this task exposes healthcare workers (HCWs) to lower back kinetic demands that can exceed safety standards, necessitating the use of mechanical lift equipment. However, HCWs still commonly perform this task manually, especially for lighter patients who are capable of assisting. Although lower back kinetic demands are presumably dependent upon the patients (in)ability to assist during the transfer, this has not been systematically tested. Therefore, the primary aim of this research was to compare the peak L5/S1 intervertebral joint (IVJ) compressive force demands during a bed-to-wheelchair manual transfer across different levels of simulated patient assist (0%, 18%, and 36% of patient bodyweight). We also compared peak IVJ compressive forces from an approach using external forces directly measured at the hands of the HCW, with an alternative traditional approach that assumed the patient’s mass was fully lifted by the HCW throughout the transfer. Peak L5/S1 IVJ compressive forces were lower ( p < .001) during the 36% than the 0% and 18% bodyweight patient assist conditions when applying the measured forces at the hand. Overall, peak compressive forces were lower ( p < .001) and tended to occur at different phases of the transfer when applying the measured forces at the hand versus assuming all the patient’s mass was being lifted. Our results emphasize the importance of accurately modeling the forces at the hands when estimating in vivo demands. Further, these findings suggest that encouraging the patient to assist during transfers may reduce IVJ forces on HCWs, but for heavier patients even a modest degree of patient assistance is not likely to protect the HCW from elevated spine loads. In most circumstances, lift equipment is warranted.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135113387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Progressive Medical Simulation: An Analysis of the Integration of Progressive and Personalized Learning in Central Line Simulators","authors":"Isra K. Elsaadany, Jessica M. Gonzalez-Vargas, Jason Z. Moore, Scarlett R. Miller","doi":"10.1177/21695067231192713","DOIUrl":"https://doi.org/10.1177/21695067231192713","url":null,"abstract":"Progressive learning gradually increases task difficulty as students advance in their education. One area that can benefit from it is medical education since it can optimize medical trainees’ skill acquisition. While progressive learning can allow for skill transfer to patient encounters, personalized learning increases the efficiency and effectiveness of learning. However, it is not well understood the number of practice trials needed to reach proficiency. To evaluate whether progressive and personalized learning can enhance medical trainees’ learning gains, the learning interface of the Dynamic Haptic Robotic Trainer (DHRT) for Central Venous Catheterization was assessed. Results showed that residents’ performance on the DHRT did not differ based on task difficulty and residents’ performance was as effective with less number of trials. The findings imply a need to integrate progressive and personalized learning on the DHRT simulator to ensure that residents are fully prepared for any patient scenario in a real-life encounter.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"17 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135113693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Primary, Secondary, and Tertiary Interactions for Fleet HumanRobot Interaction: Insights from Field Testing","authors":"Elizabeth Phillips, Lilia Moshkina, Karina Roundtree, Adam Norton, Holly Yanco","doi":"10.1177/21695067231192890","DOIUrl":"https://doi.org/10.1177/21695067231192890","url":null,"abstract":"A growing number of domains for Human-Robot and Human-Machine Interactions (HRI/HMI) will involve fleets of autonomous machines. In these fleet environments, robots will encounter not just primary interactors in one-on-one encounters, but also secondary, and even tertiary ones who are bystanders to direct human-to-robot interactions. Thus, the interaction paradigms used by such robots may need to be reconsidered to meet a growing diversity of interactions as fleet HRI/HMI applications continue to grow. Relying on use cases from field testing in mock urban environments, the purpose of this paper is to discuss our lessons learned when supporting multiple “layers” of interactors and how they relate to needs that Human Factors and Ergonomic (HF/E) science can help to address.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"37 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135168440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing Armband EMG-based Lifting Load Classification Algorithms using Various Lifting Trials","authors":"Sakshi Pranay Taori, Sol Lim","doi":"10.1177/21695067231192435","DOIUrl":"https://doi.org/10.1177/21695067231192435","url":null,"abstract":"The objective of this study was to evaluate the performance of machine learning (ML) algorithms developed using surface electromyography (EMG) armband sensor data in predicting hand-load levels (5 lb and 15 lb) from diverse lifting trials. Twelve healthy participants (six male and six female) performed repetitive lifting with three different lifting conditions, i.e., symmetric (S), asymmetric (A), and free-dynamic (F) lifts. ML models were developed with four lifting datasets (S, A, S+A, and F) and were cross-validated using F as the test dataset. Mean classification accuracy was significantly lower in models developed with the S dataset (78.8%) compared to A (83.2%) and F (83.4%). Findings indicate that the ML model developed with controlled symmetric lifts was less accurate in predicting the load of more dynamic, unconstrained lifts, which is common in real-world settings.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135215970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examination of Human Spatial Reasoning Capability and Simulated Autonomous Rendezvous and Docking Monitoring Performance","authors":"Hannah Larson, Leia Stirling","doi":"10.1177/21695067231192262","DOIUrl":"https://doi.org/10.1177/21695067231192262","url":null,"abstract":"Autonomous rendezvous and docking (ARD) maneuvers are challenging tasks that require collaboration between a human and a spacecraft to be successful. As automation becomes more integrated into ARD systems, it is important to consider when and why a human may take control. Intrinsic human characteristics can influence these decisions. We consider how human spatial orientation capacity affects participants when monitoring a simulated ARD maneuver and initiating takeover when the system is perceived to be failing. Participants’ spatial reasoning capability was assessed and compared to performance in the monitoring task and perceived mental workload. While participants showed high rates of success in the task, they showed a wide range in spatial reasoning capacity and perceived mental demand. Spatial reasoning capacity did not indicate participants’ mental workload, which has implications for the human as the supervisor. These results inform future work on augmentative displays that may incorporate exocentric and egocentric views.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"414 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135218207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redesigning Educational Countermeasures to Increase Virginia Drivers’ Road-Sharing Safety Knowledge","authors":"Alexandra B. Proaps, Jeremiah D. Still","doi":"10.1177/21695067231192669","DOIUrl":"https://doi.org/10.1177/21695067231192669","url":null,"abstract":"The lack of alignment between drivers’ and cyclists’ road-sharing knowledge results in unsafe interactions. To address this issue, educational countermeasures must clearly present and apply evidence-based practices to increase the likelihood that drivers will learn how to share the road safely with cyclists. In this study, we redesigned an existing Virginia road-sharing safety educational handbook to support a series of experiments. The redesign was based on established principles of instructional, organizational, and visual design. Virginia drivers completed a comprehension test after reviewing road-sharing educational material online. Results showed that reviewing the redesigned brochure did not improve global comprehension, law-based knowledge, and procedural knowledge about sharing the road with cyclists. However, the improved design of the educational material enhanced drivers’ declarative knowledge of road-sharing laws and safety. Further research is needed to determine the effectiveness of transferring these design choices to other transportation domains, so policymakers and instructors can effectively prioritize approaches for improving road safety.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"83 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning by Successful or Unsuccessful Experiences?","authors":"Keum Joo Kim, Eugene Santos","doi":"10.1177/21695067231192528","DOIUrl":"https://doi.org/10.1177/21695067231192528","url":null,"abstract":"Humans learn from both successful and unsuccessful experiences, because useful information about how to solve complex problems can be gleaned not only from success but also from failure. In this paper, we propose a method for investigating this difference by applying Preference based Inverse Reinforcement Learning to Double Transition Models built from replays of StarCraft II. Our method provides two advantages: (1) the ability to identify integrated reward distributions from computational models composed of multiple experiences, and (2) the ability to discern differences between learning by successes and failures. Our experimental results demonstrate that reward distributions are shaped depending on the trajectories utilized to build models. Reward distributions based on successful episodes were skewed to the left, while those based on unsuccessful episodes were skewed to the right. Furthermore, we found that players with symmetric triple reward distributions had a high probability of winning the game.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"33 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eliciting Ergonomic User-Defined Gestures for Virtual Reality: A Pilot Study","authors":"Nathan Sanders, Elif Sener, Karen B. Chen","doi":"10.1177/21695067231192530","DOIUrl":"https://doi.org/10.1177/21695067231192530","url":null,"abstract":"People are increasingly using virtual reality (VR) for work. As a result of extended use, fatigue and musculoskeletal disorders affecting the upper arms and shoulders are already becoming common among VR users. This pilot study presented a “virtual working area” (VWA) to reduce the risk of fatigue resulting from using gestures obtained in gesture elicitation studies, and explored how the distance to the user interface (UI) interacted with different functions (select, scroll) during a mock reading task. Results showed that keeping the hands within the VWA had the potential to reduce Rapid Upper-Body Limb Assessment (RULA) and Borg CR10 scores at clinically significant levels. Scores were worse when the UI was far away and for the select function, suggesting the design of virtual UIs can play a role in eliciting naturalistic yet ergonomic interactions. The results also provide effect sizes and variance estimates to plan future work.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"8 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy, Security, and Usability Tradeoffs of Telehealth from Practitioners’ Perspectives","authors":"Faiza Tazi, Archana Nandakumar, Josiah Dykstra, Prashanth Rajivan, Sanchari Das","doi":"10.1177/21695067231199689","DOIUrl":"https://doi.org/10.1177/21695067231199689","url":null,"abstract":"The COVID-19 pandemic has significantly transformed the healthcare sector, with telehealth services being among the most prominent changes. The adoption of telehealth services, however, has raised new challenges, particularly in the areas of security and privacy. To better comprehend the telehealth needs and concerns of medical professionals, particularly those in private practice, we conducted a study comprised of 20 semi-structured interviews with telehealth practitioners in audiology and speech therapy. Our findings indicate that private telehealth practitioners encounter difficult choices when it comes to balancing security, privacy, usability, and accessibility, particularly while caring for vulnerable populations. Additionally, the study revealed that practitioners face challenges in ensuring HIPAA compliance due to inadequate resources and a lack of technological comprehension. Policymakers and healthcare providers should take proactive measures to address these challenges, including offering resources and training to ensure HIPAA compliance and enhancing technology infrastructure to support secure and accessible telehealth.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"22 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135112902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human Factors Extended Reality Showcase","authors":"Randall Spain, Benjamin Goldberg, Shannon Bailey, Stephanie Fussell, Allison Bayro, Kelly Hale, Aaron Jones, Rachel Regina, Bob Thomas, Kevin Owens, Nathan Lau, Abhraneil Dam, Karen Chen, Luke Sturgeon, Monifa Vaughn-Cooke, Nuela Chidubem Enebechi","doi":"10.1177/21695067231192432","DOIUrl":"https://doi.org/10.1177/21695067231192432","url":null,"abstract":"This alternative format session provides a forum for human factors scholars and practitioners to showcase how state-of-the-art extended reality (XR) applications are being used in academia, defense, and industry to address human factors research. The session will begin with short introductions from each presenter to describe their XR application. Afterward, session attendees will engage with the presenters and their demonstrations, which will be set up around the demonstration floor room. This year’s showcase features XR applications in STEM education, medical and aviation training, agricultural data visualization, homeland security, training design, and visitor engagement in informal learning settings. Our goal is for attendees to experience how human factors professionals use XR to support human factors-oriented research and to learn about the exciting work being conducted with these emerging technologies.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"48 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135113307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}