bluuebunny/crossref_metadata_2025 huggingface dataset:
Panel Discussion Cognitive Engineering: Will They Know Our Name When We Are 40?
Authors: Dominguez Cindy , Rayo Michael F. , Dorton Steve , Morey Dane A. , Naikar Neelam , Roth Emilie , Allspaw John
Published: November 2021

This panel discussion will examine the societal awareness of cognitive engineering today. Cognitive engineering celebrated its 30th anniversary in 2018 at the HFES annual meeting. Still, some would say that cognitive engineering is not as well-known as it should be, and that it is applied in an ad hoc manner in the many high-stakes, high-risk technology modernization efforts where it would be useful. As technology advances proliferate for sharp end of the spear decision makers, we are at risk of catastrophic results if CE remains in the shadows; these results are arguably emerging on a daily basis. Each panelist will describe, from their vantage point, CE’s state of the art today, thoughts on barriers to acceptance and application, and how they envision we act towards a future in 2028 in which cognitive engineers engage systematically in complex systems’ development.
Epidemic Response: Follow-up and lessons learned from the US response to the evolving and conflicting risk information, focusing on education and clinical environments
Authors: Vredenburgh Alison G. , Sunderman Gail L. , Daly Guris Rodrigo J. , Cheruku Sreekanth R.
Published: November 2021

In this follow-up panel, we discuss what we have learned over the last year about responding to an epidemic or pandemic that has demonstrated a level of transmission unprecedented in the modern era. Two medical doctors that have worked on the front of this pandemic share their experiences transitioning from the “sharp end” of the response. Decisions about how to mitigate hazards have occurred at the personal, institutional, and health policy levels, in real-time, with frequent adaptation, and often in advance of concrete evidence. Over the course of the pandemic, hospital systems revised existing protocols to manage perceived risks in real time using emerging information from other centers. With the introduction of vaccines, there is a new type of risk perception. Is the vaccine perceived to be safe? Is there a disparity in perception among different population groups? That said, analyses are also complicated by emerging viral mutations with unclear implications. What factors increase or decrease public compliance with precautions? How are US education policymakers deciding about face-to-face classroom instruction? This panel includes a warnings expert, an expert on education policy, and two practicing physicians.
Muscle Activation Differs Between Individuals During Initial Powered Ankle Exoskeleton Adaptation
Authors: Acosta-Sojo Yadrianna , Stirling Leia
Published: November 2021

Although previous studies have shown that powered exoskeletons reduce muscle activation while walking across participants, less is known about how they impact an individual’s muscle activation. This study examined an individual’s muscle activity during walking with a powered ankle exoskeleton. The designed human-exoskeleton coordination was defined as a decrease in medial gastrocnemius (MGAS) muscle activation with the exoskeleton powered and increase with the exoskeleton unpowered. 60% of the participants were observed to coordinate with the exoskeleton as designed, with 67% showing a decrease in RMS MGAS during adaptation. 60% of the participants showed no change during the de-adaptation, with 47% not returning to baseline metrics by late de-adaptation. Muscle activity differs between individuals in response to the exoskeleton power state and over time within the power state. It is important to consider these different behaviors when integrating exoskeletons into occupational settings as adaptation may be supported by training and experience.
Exploring the Effects of Swarm Degradations on Trustworthiness Perceptions, Reliance Intentions, and Reliance Behaviors
Authors: aldin Hamdan Izz , Capiola August , Alarcon Gene M. , Lyons Joseph B. , Nishimura Keitaro , Sycara Katia , Lewis Michael
Published: November 2021

Swarms comprise robotic assets operating autonomously through local control laws. Research on human-swarm interaction (HSwI) investigates how human operators collaborate with swarms to accomplish shared goals. Researchers have begun to investigate the role of trust in HSwI, specifically which aspects of robotic swarms affect human trust. Through a human factors lens, the present research builds on earlier HSwI work and investigates the effect of swarm asset degradations on trustworthiness perceptions, reliance intentions, and reliance behaviors. Results showed that trustworthiness perceptions of and intentions to rely on swarms (but not reliance behaviors) were correlated, demonstrating the relation between theoretically relevant antecedents to trust in HSwI contexts. Contrary to past work, the results showed no statistical evidence that asset degradations differentially affect trustworthiness perceptions, reliance intentions, or reliance behaviors. Limitations of the current work (e.g., heterogeneity of post-intervention foraging behavior, sample size) are discussed and followed with future research suggestions.
Effects of Human-Likeness on Robot Use in High-Risk Environments
Authors: Tenhundfeld Nathan L. , Barr Hannah M. , O’Hear Emily , Atchley Andrew , Cotter Jenna E.
Published: November 2021

Previous research has shown that the design of robots can impact the level of trust, liking, and empathy that a user feels towards a robot. Additionally, this empathy can have direct impacts on users’ interactions with the system. Existing research has looked at how empathy can influence user willingness to, for example, put the robot in harm’s way or to destroy the robot. However, these studies have been inherently reliant upon narrative driven manipulations, which may result in experimental demands which could have influenced the results. As such, we provide a human-likeness manipulation in order to evaluate the impacts of design which may evoke empathy, on use of robots in high-risk environments. Results indicate no significant difference in robot use between conditions. These results are in conflict with previous research. More research is needed to understand when users are/are not willing to use a robot in a high-risk environment.
Using Technology to Support Distributed Teams: A Work System-Based Study of an Interdisciplinary Team Responding to COVID-19
Authors: Hale-Lopez Kaitlyn L. , Wooldridge Abigail R. , Goldstein Molly H.
Published: November 2021

Effective teams are essential to meet the complex and dynamic requirements during pandemic response. This case study analyses the work system of mobileSHIELD, a distributed team developing a diagnostic test in response to the COVID-19 pandemic. We conducted interviews with 18 team members to understand how work system design influences the use of technology to support distributed teams. We identified six work system barriers and facilitators. The barriers related to rapidly adopting new technologies and not utilizing features of technologies that support relationships. The facilitators were related to the use of technology to support informal communication, synchronous and asynchronous communication, and mobile technology to improve productivity and collaboration. Our findings indicate technology that is mobile, cloud based, simple and user-friendly can support distributed teams, in particular by improving asynchronous communication. Future research will holistically explore implications for work system design to support interdisciplinary teams responding to societal crises.
Shipboard Operations Room Layout Analysis Using Modeling and Simulation
Authors: Wang Wenbi , Le Jimmy
Published: November 2021

The introduction of low-profile consoles into shipboard operations room opens new possibilities to design its spatial layout. A modeling study was conducted to examine six layout options by manipulating two design factors: console orientation and supervisor seat assignment. The quality of each option was evaluated algorithmically based on its support to operator interaction. The results revealed the strengths and weaknesses of each design: face-to-face was found to be superior for supporting visual and auditory communication, face-to-back was better at facilitating tactile interaction, whereas back-to-back was preferable for an operations room where extensive interaction involved operators moving to one another’s workstations. Benefits were also predicted for configurations where supervisors were assigned to a side seat, primarily for improving the cost scores of tactile and distance interaction links. Results from this study strongly support the inclusion of faceto-face setup and alternative supervisor seating assignment as options in future shipboard operations room design.
Voice’s Effect on Student Effort Ratings and Recall Performance While Under Cognitive Stress
Authors: Morris Thomas W. , Chen Hung-Tao M.
Published: November 2021

Computer-generated speech is becoming more commonplace in classrooms, so it is important to examine the impact of computer voice on students’ cognition in a variety of learning situations. The current study investigated the effects of voice in a cognitively stressful, audio-only learning situation. In this experiment, 122 college students were recruited to listen to an audio lecture and respond to test questions. Our findings indicated that participants rated the classic voice engine as demanding the most effort and the human voice as demanding the least effort. Students also had the best recall performance in the human voice condition and the worst recall performance in the classic voice condition. Our results indicated that when learners are placed under cognitive stress, the human voice is the superior pedagogical agent. These results contribute to a growing body of research examining modern computer voice as a pedagogical agent.
Human Factors in Urban Transport: Control Room Resource Management Training (CRRM)
Authors: Schadow Jana , Wiegand Normen , Bruder Carmen
Published: November 2021

Control center operations are highly demanding in terms of the collaboration required for monitoring and decision making in teams. In a joint effort led by the DLR, several institutions investigated psychological requirements among teams in control centers. This involved holding workshops and shadowing the work of experts for operative processes in control rooms of several industry partners (Deutsche Flugsicherung GmbH, Deutsche Lufthansa AG, Flughafen Hamburg GmbH, Hamburger Hochbahn AG). An initial control room resource management (CRRM) training was developed and tested with a group of operators from the Galileo Control Center (GCC). The refined version of the 2-day CRRM training was developed for groups of 10-12 participants and was validated in seven training sessions with a total of 79 operators from the subway control center of the Hamburger Hochbahn AG. In conclusion, the CRRM training provides a successful approach to improve teamwork in control rooms.
Model blindness: A Framework for Understanding how Model-Based Decision Support Systems can Lead to Performance Degradation
Authors: Parmar Sweta , Illingworth David A. , Thomas Rickey P.
Published: November 2021

Model-Based Decision Support Systems (MDSS) are ubiquitous in many high-consequence domains like emergency management and military command and control. This paper proposes a framework of model-blindness imposed by MDSS via filtering relevant information and presenting irrelevant information to the decision-maker, causing performance degradation. The paper also defines novel categories of performance: model-limited, strategy-limited, and context-limited. We propose a theoretical confluence model of operator performance under model blindness and a framework to evaluate model blindness empirically. We report simulation results to demonstrate the impact of model blindness on performance and outline mitigation strategies for designers and developers of MDSS. The recommendations and insights can be used to evaluate the limitations associated with particular MDSS before implementation.
The Relationship Between Takeover Request Lead Time and Drivers’ Situation Awareness for Freeway Exiting in Conditionally Automated Driving
Authors: Tan Xiaomei , Zhang Yiqi
Published: November 2021

Conditionally automated vehicles require the out-of-the-loop driver to intervene when the system is unable to handle forthcoming situations, such as freeway exiting. The takeover request (ToR) for exiting a freeway can be scheduled in advance. Upon a ToR, the driver needs to gain situation awareness (SA) and resume manual control. This study examined how the ToR lead time affects driver SA for resuming control and when to send the ToR is most appropriate for freeway exiting. A web-based, supervised experiment was conducted with 31 participants. Each participant experienced 12 levels of ToR lead time (6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 45, and 60 s). The results showed positive effects of longer ToR lead times (16–60 s) on driver SA for resuming control to exit from freeways in comparison to shorter ToR lead times (6–14 s), and the effects level off at 16–30 s.
Effect of body-gender transfer in virtual reality on the perception of sexual harassment
Authors: Wu Linfeng , Chen Karen B. , Fitts Edward P.
Published: November 2021

While sexual harassments are inappropriate behaviors in the society, the interpretation of and sensitivity toward sexual harassment can vary by individual. Differences across individuals, such as gender, may influence whether one interprets an action to be sexually harassing or not. Virtual reality technology enables human behavior assessment without interfacing with physical danger. The present work examined whether gender and body-gender transfer in VR influenced the perception of sexually harassing behaviors, and explored the utility of emerging technology in increasing one’s awareness of behaviors that may be considered sexually harassing. Participants (n=12) embodied in virtual characters of different genders and experienced seven sexually harassing scenarios in an immersive virtual environment in random order. In general, participants provided higher rating to the sensitivity toward sexual harassment in the VR harassment scenarios than those scenarios described on paper. There was an increase in participants’ sensitivity toward sexual harassment after experiencing sexual harassment scenarios from the perspective of the victim in VR. Participants perceived higher level of sexual harassment when they embodied in female avatars, which suggested there was an effect of VR with body-gender transfer on perception of sexual harassment. There were gender differences in awareness of harassing behaviors in VR environment, and VR may be a training method to narrow gender gap and increase awareness toward sexual harassment.
Evaluation of a High-Risk Clinical Guideline through implementation of Usability Evaluation
Authors: Newton Sydney , Yale Sarah , Gosbee John , Scanlon Matthew
Published: November 2021

This paper des cribes the use of heuristic evaluation on a clinical guideline for the treatmentof diabetic ketoacidosis, a medical emergency. After an hour of instruction, two novices tousability testing applied a heuristic tool revealing numerous usability issues in the dom ainsof metaphor, organization, typology and layout. When compared to Nielsen’s principles ofheuristics, the findings identified multiple sources of potential error. A dditionally, thispaper demonstrates that novices to usability testing can perform effective heuristicevaluation with limited training and the use of a heuristic tool. The findings will guideredesign of the studied guideline as well as prompt and more readily accessible usabilitytesting of other high-risk and high-volume clinical guidelines.
Human Prediction of Robot’s Intention in Object Handling Tasks
Authors: Soratana Teerachart , Yang X. Jessie , Liu Yili
Published: November 2021

Trained human workers can predict the intentions of other workers from observed movement patterns when working collaboratively. The intentions prediction is crucial to identify their future actions. In human-machine teams, predictable movement patterns can enhance the interaction and improve team performance. In this article, we investigated the eﬀects of diﬀerent robot trajectory characteristics on the early prediction performance in human-machine teaming and on perceived robot’s human-likeness. The results showed that humans can predict the robot’s intention quicker and more accurately when the observed robot’s trajectory was generated with relatively lower energy expenditure. We found that the amount of jerk and acceleration in the robot’s joint-space aﬀected perceived robot’s human-likeness.
Development and pilot test of a machine learning-based knee exercise system with video demonstration, real-time feedback, and exercise performance score
Authors: Chen Tianrong , Or Calvin Kalun
Published: November 2021

Exercise therapy is a common and effective approach for managing chronic knee pain. However, individuals often receive minimal supervision from physical therapists when exercises are performed at home. In this study, we developed a video-based training system to allow individuals to perform lower limb exercises, based on a machine learning algorithm for pose detection and estimation. The system included three key features: (1) an exercise video demonstration, (2) real-time tracking and feedback of exercise movements, and (3) an overall score of exercise performance. We also pilot tested the system by having participants (n = 8) to use the system to perform lower limb exercises for 3 consecutive days. The results indicated that, compared with the baseline, the perceived usefulness of the system ( t = 3.25, p = 0.01) and perceived lower limb muscle strength ( t = 2.94, p = 0.02) significantly improved after 3 days. These findings provide knowledge about the initial views on this system by the participants. However, further enhancements of the features and full-scale experiments to examine the usability and acceptance of the system and its impact on knee health are needed.
Exploring Electric Transmission Operation with Cognitive Work Analysis Models
Authors: Üreten Ece , Olatoye Olamide , Kelly Adrian , Burns Catherine
Published: November 2021

Electric power networks are regarded as complex socio-technical systems as they incorporate a wide number of tasks and dynamic data that needs to be monitored continuously. This preliminary study investigated the work environment of electric power transmission and the related control tasks performed by the system operators. These findings shall be incorporated into the design of an ecological interface to improve situation awareness, reduce cognitive workload, and especially support novice operators in training.
Effects of unreliable automation and takeover time budget on young drivers’ mental workload
Authors: Shahini Farzaneh , Park Junho , Zahabi Maryam
Published: November 2021

Young drivers are involved in a significantly higher number of crashes than any other age group. Highly automated vehicles are expected to improve traffic safety and reduce human errors; however, driver needs to take over in situations where the automation fails. A driving simulation study was conducted with twenty-eight young drivers to investigate the effects of unreliable automation, different takeover time budgets (TOTBs), and secondary tasks on mental workload during takeover situations. Mental workload was measured using a combination of physiological and secondary task performance measures. Results suggested that when faced with critical incidents, young drivers experienced lower mental workload under 10s of TOTB as compared to 5s or 8s of TOTB especially when they were engaged in a demanding secondary task. In addition, drivers experienced higher mental workload when regaining the control of the vehicle in the automated mode than the manual driving condition.
Exploring the Use of Cognitive Work Analysis in Developing a Nuclear Power Plant New-State Vision
Authors: Kovesdi Casey R. , Spielman Zachary A.
Published: November 2021

The United States nuclear industry needs to identify and implement a new strategy that will lower operating and maintenance costs while maintaining safety for existing plants. The industry must also have a clear and strategic vision of this transformative new state that focuses on ways in which technologies can be integrated to maximize the benefits of technology and people. While there are ongoing efforts in this area, this work discusses how the use of cognitive work analysis may offer further support. This paper provides an overview of cognitive work analysis, as well as the state of current new-state development efforts. The use of cognitive work analysis as a tool to enhance existing practices is presented to ensure the systematic and complete development of a new state vision.
Case report for the learning science evaluation checklist
Authors: Li Siyuan , Siegle Robert F. , Craig Scotty D.
Published: November 2021

eLearning practitioners are eager to know what factors affect the effectiveness of online learning and how they can implement evidence-based evaluation to examine and improve their organizations. This study adopted the learning sciences evaluation checklist to successfully evaluate a military-based training and learning organization via a semi-structured interview and provide actionable recommendations afterward. The criteria include educational networks, human-centered evaluations, administrator-instructor trust, institution-student trust, organization support-level strategies, support services, humans/technological support infrastructures, and class size flexibility. Seven practitioner take-aways were provided to ease the use of the checklist.
Moving From Piloted to Autonomous Operations: Investigating Human Factors Challenges in Urban Air Mobility
Authors: Panesar Karanvir , Mathur Akshay , Atkins Ella , Sarter Nadine
Published: November 2021

Urban Air Mobility (UAM) is expected to be the next major revolution in the aviation industry and a solution to the growing traffic congestion on the ground. The long-term goal of UAM is to reach fully autonomous operations with minimal to no human supervision. Transitioning from today’s piloted to fully autonomous operations while maintaining or exceeding the current safety level in commercial aviation will require sig-nificant advances in technology and extensive collaboration between government, industry, and community stakeholders. In this paper, we discuss results from a focus group aimed at capturing the perspectives of five subject matter experts on the challenges associated with transitioning to fully autonomous operations. The focus group revealed five major themes for future research: overall system and automation design, training, system safety and security, community and, regulations and policy. The findings from this research highlight gaps in technology, regulations and our understanding of large-scale complex systems.
The relationship between movement behavior, musculoskeletal discomfort, and cardiometabolic measures among sedentary office workers
Authors: Athena Nguyen , Federico Arippa , Massimiliano Pau , Adamson Carisa Harris
Published: November 2021

Background: Sedentary behavior is associated with musculoskeletal discomfort (MSD) and especially prevalent in office workers. Objective: This cross-sectional analysis examined postures and activities of office workers to determine whether there were associations between posture/activity levels, MSD, and cardiometabolic measures. Methods: Participants completed baseline questionnaires, wore an inertial measuring unit, blood pressure cuff, and heart rate monitor to quantify posture, physical activity, and cardiometabolic measures. The relationships among posture/activity, MSD, and cardiometabolic data were assessed using Pearson correlation coefficients. Results: There were weak to moderate negative correlations between steps per day, hours spent standing, and hours spent walking and MSD. Weak to moderate positive correlations existed between time spent sitting, transitions, and MSD, yet there were moderate correlations between the number of transitions and measures of heart rate. Conclusion: Future interventions should take into consideration comprehensive approaches to decrease sedentary time throughout the day and maximize worker health.
Using Three-Dimensional Augmented Reality to Enhance General Aviation Weather Training
Authors: Meister Philippe , Miller Jack , Wang Kexin , Dorneich Michael C. , Winer Eliot , Brown Lori , Whitehurst Geoff
Published: November 2021

This work evaluates augmented reality (AR) training materials for general aviation (GA) weather training. Reviews of GA weather training identify gaps where students lack opportunities to experience weather patterns and lack the ability to correlate weather knowledge in weather-related situations. Three-dimensional (3D) visual models may help close the gaps by visualizing information about weather processes, hazards, and visual cues. A 3D AR thunderstorm model visualizes a single-cell thunderstorm clouds, winds, precipitation, lightning, and advective movement. Preliminary evaluation of the model was conducted through a subject matter expert (SME) review and a usability study. The SME review identified improvements to the model and areas for future content design. The usability study identified usability issues with the model. Insights about the design of weather visualizations are developed into recommendations. The approach will integrate 3D AR models into the weather training curriculum to create interactive print training.
Effects of Head-locked Augmented Reality on User’s Performance and Perceived Workload
Authors: Ghasemi Yalda , Singh Ankit , Kim Myunghee , Johnson Andrew , Jeong Heejin
Published: November 2021

An augmented reality (AR) environment includes a set of digital elements with which the users interact while performing certain tasks. Recent AR head-mounted displays allow users to select how these elements are presented. However, few studies have been conducted to examine the effect of presenting augmented content on user performance and workload. This study aims to evaluate two methods of presenting augmented content — world-locked and head-locked modes in a data entry task. A total of eighteen participants performed the data entry task in this study. The effectiveness of each mode is evaluated in terms of task performance, muscle activity, perceived workload, and usability. The results show that the task completion time is shorter, and the typing speed is significantly faster in the head-locked mode while the world-locked mode achieved higher scores in terms of preference. The findings of this study can be applied to AR user interfaces to improve content presentation and enhance the user experience.
Improving Service through a Digital Assistant for Direct Support Professionals: Exploratory Focus Groups
Authors: McGough Olivia , Ungerer Matthew , Russell Jaya , Tremoulet Patrice D
Published: November 2021

Direct Support Professionals (DSPs) who assist adults with autism spectrum disorder sometimes find it difficult to keep up with administrative tasks including the documentation of important data needed by others who also provide support to their clients (e.g. behavior analysts, physicians, other DSPs). Existing technologies, such as cameras, smart speakers and smart medication dispensers, could potentially be leveraged to help capture some of the data that DSPs are asked to report as part of their work responsibilities. However, it is not currently known whether DSPs would be amenable to using these technologies ‘on the job’. This paper presents preliminary results from two exploratory focus groups where DSPs were asked to discuss the possibility of using different types of technologies to facilitate capturing and reviewing data about clients they serve.
Infant fatality patterns in shared sleep: keys to intervention strategies?
Authors: Ann Drago Dorothy , Pollack-Nelson Carol , Beth Newens Sarah
Published: November 2021

This study examines infant fatalities that occurred while sharing a sleep surface. Fatality data reported to the U.S. Consumer Product Safety Commission (CPSC) during the time period January, 2013 through December, 2017 and involving infants through age 10 months were reviewed. 1,587 Cases were analyzed on the following variables: infant age and sex; sleep environment by product; cause of death; fatality pattern; and breastfeeding, where it was mentioned. 97% Of deaths were due to some form of asphyxia. Adult beds were associated with 78% of shared sleep fatalities, and the primary fatality pattern was overlay (35.4%)/probable overlay (8.8%). Infants <3 months made up 65% of fatalities. The data reflect that bedsharing continues, despite AAP guidelines to the contrary, and that overlay is the primary hazard pattern to be addressed. This paper discusses potential risk reduction strategies that may reduce the potential for overlay fatalities.
Design Guidelines for Immersive Dashboards
Authors: Ma Qian , Millet Barbara
Published: November 2021

Immersive dashboards facilitate the presentation of large-scale complex data while offering natural interaction and real-time interactivity supporting immediate use. Few studies, however, have investigated the use of immersive dashboards to improve the visualization and analysis of abstract data. This study provides a systematic review of the literature on designing immersive dashboards for abstract data visualization and analytics. Twenty publications met the inclusion criteria. This review identifies guidelines for improving immersive dashboard design.
Effects of a Bolster Curvature on an Automobile Seat Fit
Authors: Lee Baekhee , Park Byoung-Keon (Daniel) , Jung Kihyo , Park Jangwoon
Published: November 2021

Vehicle-seat dimensions measured at specific cross-sections have been historically utilized as shape determinants to evaluate a driver’s seat fit. The present study is intended to quantify the relationships between seat fits and the seat dimensions for designing an ergonomic vehicle seat. Eight seat engineers evaluated seat fits for 54 different driver seats based on their expertise. Five seat dimensions were measured at six cross-sectional planes using a custom-built, computerized program. The best-subset-logistic-regression method was employed to model the relationships between the seat fit and the seat dimensions. As a result, significant seat dimensions, such as insert width, bolster height, and/or bolster curvature, on the subjective seat fit (e.g., loose-fit, right-fit, and tight-fit) were quantified. The developed models showed 98% overall classification accuracy throughout the cross-sectional planes. The models promote a digital design process of an automobile seat, which would increase the efficiency of the process and reduce the development costs.
Validation of Fatigue Failure Risk Assessment Tools Against Physician-Diagnosed Outcomes
Authors: Bandekar AJ , Sesek Richard , Schall Mark , Huangfu Rong , Bani Hani Dania , Gallagher Sean
Published: November 2021

Evidence suggests that musculoskeletal disorders (MSDs) may be the result of a fatigue failure process in musculoskeletal tissues. Recently risk assessment tools using fatigue failure principles have been developed to evaluate risk of low back disorders (LiFFT), distal upper extremity disorders (DUET), and shoulder disorders (The Shoulder Tool). All have been validated against multiple musculoskeletal disorder outcomes such as joint pain and clinic visits for MSD complaints. This paper provides validation of DUET against occupational physician diagnosed carpal tunnel syndrome (CTS) and The Shoulder Tool against diagnosed bicipital tendinosis. Results demonstrated that in both cases the fatigue failure risk assessment tools were significantly associated with physician-diagnosed outcomes in both crude and adjusted analyses (p < 0.01).
Attitudes to Wearing Face Masks at US Collegiate Aviation Programs
Authors: Dattel Andrew R. , Lubner Maxine E. , Gao Peiheng , Xie Hanzi
Published: November 2021

A survey was completed by 598 respondents from 14 collegiate aviation programs. The survey queried attitudes of advantages and disadvantages of wearing face masks (FM). Over 75% of respondents were students (with the remainder about equally split between faculty and staff) and 67% who identified as pilots. Despite public guidelines supporting the advantages of FMs, there were polarized attitudes found with the employed methodology. Females were more likely to report greater values and fewer discomforts of wearing FMs. Pilots were more likely to report fewer advantages and more difficulties wearing FMs than non-pilots. Due to public health guidelines concerning FMs, negative attitudes pilots professed are concerning given the many hours they spend in a cramped cockpit.
Designing and Evaluating an Avatar for On-Person Screening
Authors: Zish Kevin , Band David , Korbelak Kristopher , Endres Daniel , McKee Charles , McKnight Simone
Published: November 2021

In aviation security, avatars are generic human figures that are used to display alarms provided by on-person screening systems. One critical feature of these avatars is that they provide no body detail unique to an individual traveler. However, the generic nature of these avatars leaves few landmarks that can be used to map the location of an alarm on the avatar to a passenger. We manipulated two features of an avatar, body detail and grid lines, to create 6 avatars to investigate how design influences estimation of target location. Body detail was manipulated at three levels: no joints, some joints, and direct outline of the passenger. Grid lines were manipulated at two levels: grid lines or no grid lines. The results of the study showed that security screeners were nearly 20% closer to the true target location when the avatar featured landmarks that can be found on a typical passenger.
Towards standardized metrics for measuring takeover performance in conditionally automated driving: A systematic review
Authors: Cao Yining , Zhou Feng , Pulver Elizabeth M. , Molnar Lisa J. , Robert Lionel P. , Tilbury Dawn M. , Yang X. Jessie
Published: November 2021

A particular concern with SAE Level 3 automated vehicles is the takeover transition from the automated vehicle to the driver. Prior research has employed a wide range of metrics for measuring takeover performance. However, the lack of a set of standard metrics for measuring takeover performance makes it difficult to consolidate findings and summarize the influence of different factors. This article presents a review of the metrics employed in empirical literature examining takeover transitions in Level 3 automated driving and proposes a framework for standardizing the objective takeover performance metrics.
Too Much of a Good Thing is Just About Right: Using Penalty Analysis to Evaluate the Impact of Key Travel on Notebook Keyboard User Experience
Authors: Rupp Michael A. , Wismer Andrew J.
Published: November 2021

Penalty analysis (PA) is a common sensory data analysis method used to develop and improve consumer products. This technique identifies the factors that lead to the greatest reduction in product satisfaction with the largest agreement among participants. Here, we apply PA to a usability study with 51 representative users comparing two different notebook computers with different key travel (1mm vs. 1.5mm). Participants completed a typing task followed by a usability survey. While traditional t-tests revealed limited differences between keyboards, PA identified additional ways to optimize the keyboard by adjusting attributes such as key travel and force. Overall, PA may be a useful complement to usability studies. Recommendations for adapting PA to usability studies will be discussed including advantages and limitations.
An Accessible Autonomous Vehicle Ridesharing Ecosystem
Authors: Carvalho Stephen , Gluck Aaron , Quinn Daniel , Zhang Mengyuan , Li Lingyuan , Groves Kimberly , Brinkley Julian
Published: November 2021

Autonomous ridesharing vehicles provide a potential alternative and affordable mode of transportation for older adults and users with disabilities or special needs, but relatively few studies have investigated the accessibility of autonomous ridesharing applications and vehicles for them. Therefore, a participatory design approach was used to investigate the needs and challenges of this population. This investigation involved interviews, review of past focus group transcripts, literature reviews, and surveys. The findings resulted in a list of user needs to design and build prototypes of accessible technologies as part of an ecosystem for booking and riding in autonomous ridesharing vehicles. The ecosystem of technologies consisted of prototypes of a mobile application, a web application, an in-vehicle human-machine interface, an external human-machine interface, and the vehicle interior design.
Covid-19 Pandemic Behavioral Response in a Sample of Young Adults
Authors: Brazil Cristiane K. , Rys Malgorzata J.
Published: November 2021

The COVID-19 pandemic has changed our everyday lives and our behaviors. New effects, such as being afraid of leaving one’s home, have been reported, and people had to adapt their daily lives to cope with social distancing and pandemic guidelines. This study surveyed 115 young adults ages mostly between 18 and 24 to explore personal perceptions about this pandemic, adaptations made, and feelings in response to this pandemic. Results showed a possible link between self-rate health and confidence in recovering if getting this disease. Behavioral modifications reported included changes in shopping patterns, exercising less, and making more video-calls. Loneliness levels seem to have increased for this age-group, and Fear of Missing Out seems to be still taking place, along with some new feelings of Fear of Going Out. This is unlikely the last pandemic to develop. Understanding the impacts of it will be essential to better act and prepare for the future.
SpearSim: Design and Evaluation of Synthetic Task Environment for Studies on Spear Phishing Attacks
Authors: Xu Tianhao , Singh Kuldeep , Rajivan Prashanth
Published: November 2021

Despite significant advancements in security technologies, phishing attacks continue to be rampant and successful because distinguishing phishing emails from real messages remains difficult to most end-users, mainly the targeted kind known as spear-phishing. There is a severe lack of human factor studies on spear-phishing attacks due to lack of methods and datasets. We have designed a novel multi-player synthetic task environment, called SpearSim, for conducting laboratory experiments on spear-phishing attacks. Using SpearSim, we have conducted an experiment to understand how information exploitation in spear-phishing attacks influences end-user decision-making. This paper describes the SpearSim system’s design and discusses the results from the experiment conducted with SpearSim. The experiment results show that people are more vulnerable to spear-phishing attacks when attackers can explore and exploit different kinds of personal information available to them about their targets. We discuss the implications of this research for the design of anti-phishing training solutions and privacy enhancing technologies.
Utilizing a Learning Strategy Analysis to Determine a System’s Potential Impact on Student Learning: The Augmented-Reality Emotive Virtual Patient System Platform
Authors: Villa Sabrina Cervantes , Craig Scotty D. , Zakhidov Djakhangir , Zielke Marjorie
Published: November 2021

A learning strategy analysis was performed on the Emotive Virtual Patient System, an augmented reality platform that teaches medical students doctor-patient communication skills. The Emotive Virtual Patient System is a complex mixed reality platform that includes both virtual and human peers/instructors who use natural language processing to provide feedback and dialog modeling as a means to improve patient communication learning outcomes. The learning strategy analysis (i.e., system learning strategy/component review, literature review, and heuristic evaluation of best practices) was conducted on the early system plans to determine its potential in supporting student learning and to provide shortand-long-term design considerations. The analysis identified three major categories for potential consideration: verbal interactions, user groups/system objective monitoring, and security. Specific recommendations were given for each of these areas, as supported by the literature.
Graph Convolutional Networks for Exercise Motion Classification
Authors: Haghighat Parian , Prince Aden , Jeong Heejin
Published: November 2021

The growth in self-fitness mobile applications has encouraged people to turn to personal fitness, which entails integrating self-tracking applications with exercise motion data to reduce fatigue and mitigate the risk of injury. The advancements in computer vision and motion capture technologies hold great promise to improve exercise classification performance. This study investigates a supervised deep learning model performance, Graph Convolutional Network (GCN) to classify three workouts using the Azure Kinect device’s motion data. The model defines the skeleton as a graph and combines GCN layers, a readout layer, and multi-layer perceptrons to build an end-to-end framework for graph classification. The model achieves an accuracy of 95.86% in classifying 19,442 frames. The current model exchanges feature information between each joint and its 1-nearest neighbor, which impact fades in graph-level classification. Therefore, a future study on improved feature utilization can enhance the model performance in classifying inter-user exercise variation.
Comparing measures of sensitivity for vigilance tasks: Bayesian-estimated and log-linear corrected measures outperform A!
Authors: McCarley Jason S.
Published: November 2021

Signal detection analyses often attribute the vigilance decrement to a combination of bias shifts and sensitivity losses. In many vigilance experiments, however, false alarm rates are at or near zero, complicating the analysis of sensitivity. Here, we report Monte Carlo simulations comparing three measures of sensitivity that can be calculated even with extreme hit and false alarm rates: A’, an estimate of the area under the curve that is commonly but mistakenly described as nonparametric; Az calculated using the log-linear correction, a statistic that adjusts individual observers’ data to protect against low false alarm rates; and, 4z estimated using a Bayesian hierarchical procedure, a measure that protects against extreme false alarm rates by sharing information between observers. Results confirm that bias shifts produce spurious changes in A’, and demonstrate that, 4z estimated with either a log-linear correction or through hierarchical Bayesian modeling is more robust against low false alarm rates.
Examining Adverse Patient Outcomes in Nurses: The Role of Patient Acuity, Shift and Fatigue
Authors: Doudna Aaron , Schwerha Diana
Published: November 2021

This study identified key factors contributing to adverse patient outcomes (APOs) at a mid-western hospital. Understanding risk factors that contribute to increased nurse fatigue can provide solutions to reduce the impact that fatigue has on nurse performance and patient outcome. This study was comprised of two phases: 1) a database analysis of current data collected at a mid-western hospital, and 2) three focus groups to identify nurse perceptions pertaining to task demand and fatigue. The APOs analyzed in this study were medical administration errors (MAEs) and patient falls. A comparison of the data from both phases was then conducted to determine whether data reflected in the database correlated with nurse perceptions. This analysis documents significant results with respect to APOs in the following workload factors such as: hours worked, case mix index (CMI), shift, and nursing unit type.
Implementing A Human Factors Approach To Rca2: Analysis Of Resultant Safety Recommendations
Authors: Solomon Demetrius , Wood Laura , Wiegmann Douglas
Published: November 2021

Root Cause Analysis and Action (RCA2) guidelines offer fundamental improvements to traditional RCA. Yet, these guidelines lack robust methods to support a human factors analysis of patient harm events and the development of systems-level interventions. We previously described how human factors tools can be integrated into RCA2 to create a robust process called HFACS-RCA2. Prior analyses of qualitative data associated with an 18-month implementation project at a large academic health center indicated that HFACS-RCA2 fosters a more comprehensive human factors analysis of serious patient harm events and the identification of broader system interventions. The present study builds on this prior research by presenting the analysis of actual recommendations extracted from RCA reports. Results corroborate qualitative stakeholder findings that HFACS-RCA2 produced recommendations that were stronger and included more substantive changes compared to former RCA methods.
Users’ Perception Of Training Approaches For Advanced Driver Assistance Systems (Adas)
Authors: Pai Ganesh , Hungund Apoorva P. , Widrow Sarah , Radadiya Jaydeep , Pradhan Anuj K.
Published: November 2021

Advanced Driver Assistance Systems (ADAS) provide safety and comfort while driving. However, to effectively use ADAS, it is necessary for users to have proper knowledge of the systems and to trust the system to operate safely. Providing knowledge about operational capabilities and limitations of a system may help improve drivers’ mental models and calibrate their trust resulting in proper use of ADAS. Traditionally system information is provided via the owner’s manual, which is known to be tedious and time-consuming and underscores the need for alternate training approaches. This study evaluates two training methods, Text-Based and System Visualization, to examine users’ perceptions of training and change in trust after training. Results show that although training did not affect users’ trust, a qualitative examination showed that users preferred the Text-Based method rather than the Visualization method.
SEEV Modeler: A GUI-Based Tool for the SEEV Model Simulation
Authors: Rheem Hansol , Steelman Kelly S. , Gutzwiller Robert S.
Published: November 2021

The SEEV model of visual scanning offers a quick and easy way of evaluating the attentional demands of various tasks and displays. A SEEV model can be developed without relying on complicated mathematical software or background, making the conceptual model highly accessible. Implementation of SEEV modeling can further be improved by easing the process of running simulations and providing actionable information. In this paper, we showcase the SEEV Modeler, a GUI-based prototype of the computational SEEV model that lowers the technical barriers for human factors practitioners. Furthermore, the prototype’s ability to predict eye movements in dynamic driving scenarios was tested, with an emphasis on the impacts of the attention shifting effort and inhibition of return (IOR) on the model’s prediction performance. The SEEV Modeler produced model fits comparable to those of previous mathematical modeling approaches but also revealed limitations and practical issues to be addressed in the final version.