bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing Presence, Workload, and Performance in Desktop and Virtual Reality Flight Simulations
Authors: van Weelden* Evy , Wiltshire Travis J. , Alimardani Maryam , Louwerse Max M.
Published: October 2022

Virtual reality (VR) offers a training environment that promotes increased learning and performance. However, to what extent VR flight simulations offer increased performance compared to less-immersive simulators is not clear, and neither are their underlying cognitive aspects. In a within-subject experiment, we compared fight performance and subjective measures of workload, presence, and engagement in two flight training environments (Desktop and VR) on two flight tasks of equal difficulty (changing speed and performing turns). No differences were observed in the flight performance between these conditions. However, participants reported higher presence and engagement in the VR training environment. Additionally, we found a correlation between subjective workload and flight performance in the Desktop condition, but not in VR. We conclude that VR is promising for basic flight training tasks and encourage future work to explore this further by investigating neurophysiological indices of workload and engagement and establishing relationships between presence, workload, and flight performance.
A User-Centered Approach to Designing Secondary Anesthesia Medication Labels
Authors: Goel Swati , Joseph Anjali , Neyens David M. , Catchpole Kenneth , Alfred Myrtede , Jaruzel Candace , Tobin Catherine , Aberathy James H , Heinke Timothy , Haney Jason
Published: October 2022

Poorly designed and implemented medication labels have been identified as a source of medication errors within anesthesia delivery. Previous studies noted that simplified text and icons are useful in warning labels used for prescription drugs, especially for people with low literacy levels. In addition, Tallman lettering can reduce errors due to the custom capitalization of text. However, icons, color, and Tallman lettering have not been explored for improving the readability of anesthesia medication labels. This study utilizes a user- centered approach to design and evaluate icons and other graphical features to be included on secondary medication labels placed on infusion bags within anesthesia point-of-care. The study utilizes an iterative design process to examine the potential efficacy of these design characteristics by evaluating them with the anesthesia providers/clinicians through an online survey. Findings suggest that introducing graphical components like icons and color may be useful and accepted by clinicians to improve medication recognition.
Flexible Task Analysis Framework: Feedforward and Feedback
Authors: Li Ruixuan , Blanc Katya Le
Published: October 2022

Researchers and practitioners have different emphases and goals when conducting task or system analyses. This paper proposes a task analysis framework to augment other task analysis and human performance modeling approaches. The intent is not to replace but provide flexibility to use. The proposed framework includes critical processes (i.e., modules) that must be considered based on psychological theories, methodologies, and findings. It integrates the feedforward mechanism in motor and cognitive tasks in order to explain how users achieve multiple goals via a single task and prevent or mitigate undesired conflicts. It also includes a General Purposes module that combines some perspectives of user needs in user experience and functional purposes in work domain analysis to accommodate different domains’ characteristics. Ultimately, a task analysis pertaining to the work carried out by an electric grid transmission operator was conducted as an example of how this framework can be implemented.
Mental imagery testing for personnel selection, training, and HCI applications
Authors: Colombe Jeffrey B. , Gallo Samantha , Panic Sacha
Published: October 2022

This theoretical paper advocates for research to assess whether tests of mental imagery may be used as reliable and valid predictors to inform the design of human-computer interactions suited to individual differences, and industrial-organizational psychology applications including personnel selection and customized training regimens. Mental imagery includes multisensory, non-sensory spatial, and motor rehearsal forms, and has been correlated with emotional reactivity and performance on laboratory tasks such as memory recognition and recall. We focus on air traffic control and aircraft pilot roles, as cognitive testing has been pioneered in these high-consequence professions, with resulting cultural and institutional support for the use of testing to guide personnel development decisions. Mental imagery testing may also offer benefits in the lifelong career pipeline for STEM, creative, and problem-solving work roles more broadly.
Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and Workload
Authors: Chandarana Meghan , Chancey Eric T. , Le Vie Lisa R. , Politowicz Michael S.
Published: October 2022

Technological advances have increased the automation of Uncrewed Aerial Vehicles, allowing human operators to manage multiple vehicles at a high-level without the need to understand low-level system behaviors.Previous laboratory studies have explored the relationship between reliability, trust, use of automation, andthe effects of number of vehicles under supervision on subjective workload. Due to limitations resulting fromthe COVID-19 pandemic, in-person laboratory studies are not always possible. Therefore, this work aimed to investigate if remote data collection alternatives, such as Amazon’s Mechanical Turk, can provide comparativeresults as those obtained in laboratorysettings. A study was conducted in the context of small droneoperations. As expected, higher reliability led to higher trust ratings and the inclusion of more vehicles ledto higher workload. In contrast, reliability unexpectedly had no significant effect on intention to use theautomation. Though these results were encouraging, several limitations were identified
Human in the Loop Evaluations of A Taxi Assistance Tool for Pilots
Authors: Estes Steven , Helleberg John , Pollack Matthew
Published: October 2022

Runway Incursions (RIs) - the improper presence of an aircraft on a runway - have proven difficult to reduce below current levels. RIs are mostly the result of pilot deviations (PDs), and most pilot deviations are made by general aviation (GA) pilots. MITRE is developing a taxi assistance concept to create taxi guidance and conformance technology with the hope of reducing RIs caused by lost, distracted, or confused pilots. This research is primarily focused on smaller Class D airports where GA traffic is higher, and controllers do not have advanced technologies in the tower cab. Three studies were conducted evaluating pilot interaction with MITRE's taxi assistance application, as implemented as an iPad application. Study results provided design guidance and evidence that these applications could reduce the likelihood of RIs caused by pilots. In this paper we will briefly review each study.
Influence of different honeypot proportions on adversarial decisions in a deception game
Authors: Katakwar Harsh , Uttrani Shashank , Aggarwal Palvi , Dutt Varun
Published: October 2022

Cyberattacks are proliferating, and deception via honeypots may provide efficient strategies for combating cyberattacks. Although prior research has examined deception and network factors using deception-based games, it is still unknown how the proportion of honeypots in a network influences the adversarial decision. This study evaluates the influence of different honeypot proportions on the adversary’s decisions using a deception game (DG). DG has two consecutive stages, probe and attack. In the probe stage, participants may probe a few webservers or not probe the network. In the attack stage, participants may attack any of the webservers or decide not to attack the webservers. Participants were randomly assigned to one of three between-subject conditions containing different honeypot proportions: small, medium, and large. With an increase in the proportion of honeypots, the honeypot and no-attack actions increased dramatically. We show how our findings are applicable in deception-based cyber scenarios.
Confirmative or Normative? Information Redundancy in Decision Support Systems
Authors: Mulugeta Filmona , Ben Yaakov Yoav , Meyer Joachim
Published: October 2022

Decision Support Systems (DSS) provide users with information that is combined with their existing knowledge or information from other available sources. We investigate how redundancy of the information from the DSS affects the decision to purchase decision support, as well as the use of and trust in the support. Participants performed a classification task. Depending on the condition, they could purchase advice from either an independent, partly redundant, or fully redundant DSS. Purchase decisions, classification performance and trust were recorded. Participants preferred to purchase the independent system, performed better with it and trusted it more, compared to the partly or fully redundant systems. There was no significant learning effect across blocks. Overall, the results support a model of more normative, rather than confirmative preferences for decision support.
Joint Activity Design Evaluation Tools for Conducting Staged-World Studies
Authors: Haggit J.M. , Antonik C. , Flach J.M. , McEwen T.R. , Smith M.W.
Published: October 2022

Intelligence analysis requires an analyst to search for meaningful events in vast amounts of distributed data and synthesize those events into insights to inform decision-making. Because of the complexity, dynamics of the ecology, and typical functions of work, analysis performance can be difficult to study in traditional laboratory environments. Staged-world studies, which maintain experimental control while preserving the complexity of the work domain, represent a promising approach to study analyst performance. To support an ongoing research program, we are developing the Joint Activity Design Evaluation (JADE) platform, a software tool for conducting staged-world studies within the intelligence analysis (IA) domain. Herein, we describe three of JADE’s core capabilities for presenting scenarios based on common challenges of cognitive work, eliciting participant responses, and storing and displaying pertinent data. As JADE continues to mature and add new features, we expect it to become a tool for researchers to conduct staged-world studies across a broader range of application domains.
A Text Mining Analysis of Complacency and the Role of Complexity in the Tree-Felling Operations of Wildland Firefighters
Authors: Jonidis Douglas , Nauert Elliot , Gillan Dr.Doug
Published: October 2022

The term complacency is often referenced in many risk and safety domains, despite a unifying definition for the term currently backed by the field of psychology. Complacency has been listed as a cause for accidents in the domain of wildland firefighting. Moreover, fires resulting in fatalities or near-fatalities share a common factor of occurring on small fires or deceptively quiet areas of larger fires. This fact suggests complacency may be a key factor in circumstances that lead to the deaths of firefighters. This study analyzes the application of complacency in wildland firefighting tree-felling accident reports to develop a guiding framework informed by complexity thinking for determining a theory of complacency within the domain. Using a text mining method for accident report analysis, we aim to develop a framework for understanding complacency in this domain. A framework of complacency can help to inform firefighting risk management strategies and potentially save lives.
Shift Happens: Human Factors Considerations for Handoffs in Cyber-Security Operations Centers
Authors: Fausett Crystal M. , Keebler Joseph R.
Published: October 2022

Cybersecurity breaches have consequences not only at a technical level, but also at economic, legal, individual levels. Organizations depend heavily on the internet to conduct daily operations and activities. As cyber threats increase with frequency and severity, organizations and the cybersecurity experts they employ are facing an uphill battle. To our knowledge, very little research has been done to investigate the handoff processes that exist in Security Operations Centers (SOCs). Researchers and practitioners within the cybersecurity community would benefit from a better understanding of how handoff mechanisms influence SOC team processes and performance. To help attain this goal, this paper aims to explore handoff processes within other domains and illuminate what aspects of handoffs may be extended to SOCs and in what ways handoffs performed in SOCs may need special consideration.
Human Acceptance of the Cleaning Robot in Grocery Environments During the COVID-19 Pandemic
Authors: Chen Yuhao , Luo Yue , Ozkan Yerebakan Mustafa , Hu Boyi
Published: October 2022

Cleaning work is a labor-intensive job that frequently exposes workers to substantial occupational hazards. Unfortunately, the outbreak of coronavirus disease 2019 (COVID-19) has increased the pressure on janitors and cleaners to meet the rising need for a safe and hygienic environment, particularly in grocery stores, where the majority of people get their daily necessities. To reduce the occupational hazards and fulfill the new challenges of COVID-19, autonomous cleaning robots, have been designed to complement human workers. However, a lack of understanding of the new generation of cleaning tools’ acceptance may raise safety concerns when they’re deployed. Therefore, a video-based survey was developed and distributed to 32 participants, aiming to assess human acceptance of the cleaning robot in grocery environments during the COVID-19 pandemic. Moreover, the effects of four factors (gender, work experience, knowledge, and pet) that may influence human acceptance of the cleaning robot were also examined. In general, our findings revealed a non-negative human acceptance of the cleaning robot, which is a positive sign of deploying cleaning robots in grocery stores to reduce the workload of employees and decrease COIVID-related anxiety and safety concerns of customers. Furthermore, prior knowledge of robotics was observed to have a significant effect on participants’ acceptance of the cleaning robot ( p = 0.039).
It’s risk, Jim, but not as we know it: identifying the risks associated with future Artificial General Intelligence-based Unmanned Combat Aerial Vehicle systems
Authors: Salmon* Paul M. , McLean Scott , Carden Tony , King Brandon , Thompson Jason , Baber Chris , Stanton Neville A. , Read Gemma J. M.
Published: October 2022

The next generation of artificial intelligence, known as Artificial General Intelligence (AGI), could either revolutionise or destroy humanity. Human Factors and Ergonomics (HFE) has a critical role to play in the design of safe and ethical AGI; however, there is little evidence that HFE is contributing to development programs. This paper presents the findings from a study which involved the use of the Work Domain Analysis-Broken Nodes approach to identify the risks that could emerge in a future ‘envisioned world’ AGI-based unmanned combat aerial vehicle system. The findings demonstrate that there are various potential risks, but that the most critical arise not due to poor performance, but rather when the AGI attempts to achieve goals at the expense of other system values, or when the AGI becomes ‘super-intelligent’, and humans can no longer manage it. The urgent need for further work exploring the design of AGI controls is emphasised.
A Dynamic Bayesian Network Approach for Predicting Multitasking Performance
Authors: Li Jiaxin , Sun Tianchen , Hamza Shakur Ameer , Johnson Madison , Huang Shuai , Kim Ji-Eun
Published: October 2022

This study examines the utilities of a dynamic Bayesian network (DBN) to predict multitasking performance. Multitasking is the practice of conducting more than one task simultaneously. Compared with BN (Bayesian network), the DBN has the advantage of encoding both spatial and temporal relationships of the multiple variables under uncertain information. We established the DBN model based on contextual and observable variables from 19 participants to predict multitasking performance over time. The proposed DBN outperformed the BN model with smaller prediction errors and showed great potential to be used as a tool in error management and operator screening in diverse work environments.
Comparison of physical workload in upper extremities between left- and right-hand ultrasound scanning
Authors: Tetteh Emmanuel , Wang Tianke , Norasi Hamid , Bremer Merri , Schmida Elizabeth , Kim Joseph , Koenig Jordyn , Fortune Emma , Kane Garvan , Susan Hallbeck M.
Published: October 2022

Ames, IA Cardiac sonographers suffer from high prevalence of work-related upper extremity musculoskeletal pain due to awkward postures and fatigue accumulation. Sonographers can choose either left- or right-hand scanning, or alternate between both, however, the impact of each scanning technique on the upper extremity muscles remains unknown. Four ambidextrous cardiac sonographers performed between four to six cardiac scans using left- and right-hand while postural and muscle activity were collected from specific muscles on the upper extremities. A comparison of the posture showed that apart from forearm pitch and 90th percentile upper arm deviation, upper extremity postures between the two scanning techniques did not differ significantly. Furthermore, while right-hand scanning (RHS) appeared to induce slightly higher muscle activity in the deltoids compared to left-hand scanning (LHS), the difference between the two techniques was not significant. We recommend alternating between these two techniques to distribute muscle stress evenly to prevent muscle overuse.
On-Road Assessment of Driver Mode Awareness of Assisted and Automated Driving
Authors: Britten Nicholas , Perez Miguel
Published: October 2022

Increasingly, today’s vehicles offer Society of Automotive Engineers (SAE) Level 2 (L2) technology, and a limited number of SAE Level 3 (L3) automated driving systems (ADSs) are being developed. Since L3 ADSs can operate in L2 and manual driving, drivers’ correct mode awareness is essential. To investigate driver’s mode awareness after transitions between modes, an on-road experiment was conducted using a Wizard-of-Oz method to simulate Assisted Driving (L2-like) and Automated Driving (L3/L4-like). A total of 36 drivers completed the on-road experiment. Participants experienced periods of manual driving, assisted driving, automated driving, and transitions between these modes. After each transition, participants’ mode awareness was measured. It was hypothesized that drivers’ mode awareness would increase with system exposure over the planned automated driving periods. Results showed that drivers exhibited declarative mode awareness during both Assisted (ASD) and Automated Driving (AD) modes.
Analysis of Team Member Evaluations Based on Gender
Authors: Tchupo Dominique Engome , Macht Gretchen A.
Published: October 2022

Using data collected from multiple teams of undergraduate engineering students, this study examines whether team members evaluate members of different perceived genders differently than they would a member of their own perceived gender. This was done using social relations modeling to analyze the dyadic differences within the teams over the course of several years. This research found that despite what was expected, gender only played a minor role in how different team members rated each other as time progressed. This lack of significance of gender in the model could be attributed to the high proportion of women in this major as well as how the teams were formed.
Predicting Laparoscopic Surgical Skills of Trainees with Eye Metrics Associated with Focused Attention and Workload
Authors: Deng Shiyu , Wang Tianzi , Hartman-Kenzler Jacob , Henrickson Parker Sarah , Safford Shawn D. , Barnes Laura E. , Lau Nathan
Published: October 2022

Eye metrics are effective indicators of focused visual attention and perceived workload that have been used to differentiate surgical expertise and task difficulties. However, the change in eye metrics throughout surgical training in a cohort of trainees is under-investigated. This study collected eye-tracking data from 13 medical students practicing the peg transfer task until reaching the passing criteria of the Fundamentals of Laparoscopic Surgery. Six eye metrics measuring focused visual attention and workload were computed and then used in multiple linear regression analysis to predict trial completion time. All predictors were significant in the regression model, collectively explaining 61.7% of the variance in log-transformed completion time. Fixation rates and gaze entropy were the most important metrics at revealing skill acquisition as medical students self-train on the peg-transfer task. The results on these eye metrics demonstrate potential in assessing surgeons-in-training and providing feedback to ensure surgical competency.
SecureLD: Secure And Accessible Learning for Students with Disabilities
Authors: Shrestha Sunny , Thomas David , Das Sanchari
Published: October 2022

COVID-19 has impacted various sectors of everyday living, including the education sector. Due to the pandemic, the educational institutions everywhere were forced to switch to the online platform as per CDC guidelines. However, the transition and adaptation to the online learning format have had varied effects on different populations. This study looks at 62 students with disabilities and their experience with online learning. The technology and tools used in online learning have many vulnerabilities related to privacy and security; thus, we aim to understand students' perceptions of security and privacy in an online learning platform. We have found that, although students with learning disabilities like the option of online learning, they want and require more guidance and coordination in learning to use online learning platforms. We also see that neurodiverse students with learning disabilities recognize the need for a secure and privacy-preserving online learning environment.
Measuring Cognitive Workload of Novice Law Enforcement Officers in a Naturalistic Driving Study
Authors: Wozniak David , Park Junho , Nunn Jordan , Maredia Azima , Zahabi Maryam
Published: October 2022

There is a large amount of variation between novices and experts in their cognitive workload when performing tasks. A naturalistic pilot study was conducted with nine novice law enforcement officers (nLEOs) to determine how their use of in-vehicle technology affected their cognitive workload during their normal patrols. Physiological data were collected using a novel synchronization process for naturalistic driving studies, allowing heart rate variability and eye tracking measurements to be synchronized together and directly compared to subjective workload levels. It was found that nLEOs have average or higher workload compared to experienced officers and the general population when they are on duty. Future studies can utilize the approaches and findings of this pilot study for conducting naturalistic driving studies and developing cognitive performance models for novice users.
Sharing the Road: How Human Drivers Interact with Autonomous Vehicles on Highways
Authors: Huang Chunxi , Wen Xiao , He Dengbo , Jian Sisi
Published: October 2022

With more autonomous vehicles (AVs) being tested or deployed on public roads, human-driven vehicles (HVs) have to share the road with AVs. However, human drivers may not interact AVs the same way as they interact with HVs. Very few studies have investigated drivers’ behaviors when sharing the road with AVs. Based on a real-world dataset, our study explored drivers’ interactions with AVs in two types of events on highway, i.e., car-following event and car-passing event. The results show that, compared to interacting with HVs, drivers tended to keep a larger safety margin (i.e., larger gap distance and time gap) at high speed in both types of events when interacting with AVs. At the same time, drivers seemed to have difficulty anticipating AVs’ speed changes at high speed, as indicated by a larger standard deviation of the HVs’ speed and a smaller time to collision when following AVs versus following HVs.
Nephrologists’ and nephrology nurses’ design preferences for a wearable dialysis device
Authors: Anna Jónsdóttir Auður , Lazo Gabrielle R. , Sundar Sahana , Kessler Larry , Kim Ji-Eun
Published: October 2022

The objective of this study is to characterize nephrology nurses’ and nephrologists’ design expectations and preferences for a wearable dialysis device that allows a dialysis patient greater mobility and improved independence. We gathered ideal design characteristics, acceptable size and weight parameters, and the most preferred design type of a wearable dialysis device. Using qualitative analysis of open-ended questions and quantitative analysis of rank-order questions, our results indicate seven categories of ideal design features and give an estimate of parameters for the largest acceptable size and heaviest acceptable weight of the device. Furthermore, our results show that the clinicians significantly prefer a belt design over a shoulder bag, a vest, or a distributed design type. The findings from this study offer a vision for design preferences and usability objectives to help ensure users’ safe and efficient use of a wearable dialysis device.
Researching Influence Operation (IO) Mitigation: An HFE Step Forward
Authors: Raghav Bhat K. , Curley Richard P. , Gutzwiller Robert S.
Published: October 2022

Influence operations (IO) are coordinated efforts by an actor, individual or group, to interfere in the process of meaning-making for manipulation or corruption of public debate (e.g., Bergh, 2020), often involving dis-or misinformation spread. IOs are often employed through social media and based around political, social and/or ‘hotbutton’ issues and narratives. There is increasing study of misinformation spread and correction, but less research examines IO mitigation using human participants and controlled tests (rather than post-facto metrics). We conducted a lightly scoped literature review of IO research using social media, revealing emergent difficulties and challenges to designing and studying IO, and paths toward improving experimentation based on human factors research.
Factors Affecting Interior Acceleration Sound Preference for Electric Vehicles: A Path Analysis
Authors: Jorella Lazaro May , Kim Sungho , Wilfred Anggang Adriance , Choi Minsik , Hwan Yun Myung
Published: October 2022

Vehicle sound design is gaining attention in the automotive industry, especially for Electric Vehicles (EV). For EVs, acceleration sound is critical for both user experience (UX) and safety. Despite the abundance of UX-related studies investigating the external presentation of acceleration sound for EVs, internal presentation of acceleration sound seems to be overlooked. Thus, further understanding on what influences the user preferences for internal EV sound is essential for better EV sound design. This study aims to explore and develop a simple theoretical path model to help understand the relationship between pragmatic quality, hedonic quality, novelty, and user preferences for EV internal acceleration sounds. Thirty-two participants evaluated twenty-seven EV acceleration sound samples using a 12-item semantic differential scale with bipolar adjective pairs that describe the measured variables in a controlled experimental setting. The relationship between the modeled variables was analyzed using bias-corrected factor score path analysis (BCFSPA). Results showed that the modified model yielded good model fit indices and partially confirmed the initial hypotheses. It was found that pragmatic and hedonic quality had a positive relationship with user preference, whereas, novelty had a negative relationship with hedonic quality and user preference for EV sounds. This study contributes to the understanding of factors that affects user preference for EV sound and provides initial accounts to different approaches and methods for model testing.
Visual feedback and control configuration influences in a head tracking interface
Authors: Arnold Christopher M. , Miller Michael E.
Published: October 2022

Methods for enhancing pilot interaction with large, information dense, cockpit displays were explored. Specifically, the effects of visual feedback and selection button configuration were manipulated when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A repeated measures analysis of variance revealed that removing visual feedback reduced accuracy and selection time, control configuration did not affect performance. However, all head tracking configurations were faster than the current cursor control system. Fitts’ Law models provided a poor fit to the observed data. It is proposed that conditions without visual feedback may impose lower physical workload than the other configurations.
Attentional Considerations in Advanced Air Mobility Operations: Control, Manage, or Assist?
Authors: Sato Tetsuya , Politowicz Michael S. , Islam Samia , Chancey Eric T. , Yamani Yusuke
Published: October 2022

The implementation of automation will enable Advanced Air Mobility (AAM), which could alter the human's responsibilities from those of an active controller to a passive monitor of vehicles. Mature AAM operations will likely rely on both experienced and novice operators to supervise multiple aircraft. As AAM constitutes a complex and increasingly autonomous system, the human operator's set of responsibilities will transition from those of a controller, to a manager, and eventually to an assistant to highly automated systems. The development of AAM will require system designers to characterize these three sets of human responsibilities. The present work proposes different human responsibilities across various roles (i.e., pilot in command, system operator, system assistant) in the context of AAM along with pertinent attention-related constructs that could contribute to each of the three identified roles of AAM operators including situation awareness, workload, complacency, and vigilance.
Computational Assessment of Positional Sensitivity to Injury in Spacecraft Occupants
Authors: Menon Srihari , Ayari Rami , Currie-Gregg Nancy. J
Published: October 2022

Spacecraft occupants are susceptible to injury from sudden loads, such as those experienced during landing. Most injury biomechanics investigations assume perfect seated posture and consistent seated position. However, this assumption is unrealistic, as offsets from these presumed postures and placements are likely during impacts. In this computational study, the Global Human Body Model Consortium’s simplified 5thpercentile female and 50th and 95th-percentile male anthropometric models were seated and restrained in three positions: nominal, (“perfect” posture and placement); and 10 millimeters and 25.4 millimeters forward of the seatback. Biodynamic responses to simulations involving vertical accelerations were analyzed for positional sensitivity. The 5th-percentile female was most susceptible to neck injury due to compressive forces. In 50th and 95th-percentile males, upper spinal intervertebral forces were positively correlated to seated position (increasing 13% for 25.4mm forward offset). Analysis of head excursions and knee splay data indicates potential whiplash and the need for conformal seating, respectively.
Assessing Workers’ Mental Stress in Hand-over Activities during Human-robot Collaboration
Authors: Lu Lu , Xie Ziyang , Wang Hanwen , Su Bingyi , Edward P. Fitts Xu Xu
Published: October 2022

Human-robot collaboration (HRC) is an emerging research area that has gained tremendous attention from both academia and industry. Since some robot-related factors can elicit mental stress or have negative psychological effects on human workers, it is essential to understand these factors and maintain workers’ mental stress at a low level. Galvanic Skin Response (GSR) measures skin conductance and is known to be a physiological measurement that reflects short-term mental stress. Typically, skin conductance increases in response to greater mental stress. In this study, the mental stress caused by the hand-over activities of a collaborative robot was investigated using both GSR as an objective measurement and NASA-Task Load Index (TLX) as a subjective assessment. Several robot-related factors that may lead to mental stress were experimentally examined. GSR outcomes indicated that end effector approaching within workers’ view, low end effector speed, and constrained end effector trajectory led to a significantly lower skin conductance. Some aspects of the NASA-TLX also indicated that speed and trajectory significantly affected the scores. Yet, no significant differences were found between approaching directions regarding NASA-TLX scores.
Evaluating the Usability of a Next-Generation Heads-Up Display for Firefighters in a Virtual Environment
Authors: Saville Jason D. , Spain Randall D. , Slack Donia , Hill Edward , Lester James
Published: October 2022

Virtual environments provide a rich and immersive platform to investigate how interfaces should be designed to support public safety operations. Virtual environments can be used to simulate the tasks, demands, and conditions of emergency response events while providing a controlled and safe environment for testing and developing new user interface capabilities. This paper presents an evaluation of a prototype AR-based heads-up display (HUD) that was integrated in a desktop-based virtual environment that simulated an emergency response scenario. Members of the first responder community (N = 90) completed a series of emergency response tasks and responded to a series of usability and user experience questions and workload ratings. The study used a 2 (Condition: HUD vs. No HUD) x 2 (Task Load: Radio monitoring task vs. No radio monitoring task) mixed experimental design. Participants provided very positive feedback on the utility of the prototype HUD for supporting task performance. Results and future research plans are discussed.
Making Patient Contextual Data Concrete: Abstraction Hierarchyto Understand Patient Self-Management of Type 2 Diabetes
Authors: Kunkes Taylor , Winnie Chen Huei-Yen , Bisantz Ann M. , Cavuoto Lora A.
Published: October 2022

Social determinants of health (SDOH) and other contextual factors influence a patient’s ability to adhere to a plan of care. Providers must understand these factors in order to develop treatment plans which best meet patient needs and preferences. This is particularly important for patients with type 2 diabetes, which is primarily managed by the patient. Abstraction hierarchy is a modeling technique from the cognitive work analysis framework which describes system components at multiple levels of abstraction. This study seeks to examine SDOH as they relate to type 2 diabetes management by the patient and activities carried out by the primary care provider to incorporate these factors into the medical decision-making process. The abstraction hierarchy was developed based on previous literature and interviews with patients and primary care medical personnel. The resulting abstraction hierarchy can be used to inform future screening tools and patient-centered care interventions for addressing SDOH for patients with type 2 diabetes.
Designing Human-Robotic Interactions for an interactive Home+Exercise (iHE) Environment
Authors: Mokhtar Tarek H. , Manganelli Joseph
Published: October 2022

This research investigated how home exercise systems may evolve when augmented with human-robot-interaction technologies. In a covid/post-covid era, families seek options for play and exercise at home. How will the homes of tomorrow accommodate the dynamic, intensive, and social nature of human play, exercise, and sports? What does a home play/exercise system entail that is usable by individuals or groups of all ages and that fosters developing the physical, cognitive, social, and distributed dimensions of sports activities? This research explores an interactive “Home+Exercise” (iHE) concept. iHE incorporates a non-humanoid social robotic environment providing game-based, structured play for individuals and groups to foster athletic and team skills. This research used three theoretical frames: (1) embodied interaction, (2) activity spaces, and (3) neuro-ergonomics. The analysis usefully maps relevant design concerns and identified the following challenges: (1) the criteria of evaluation are mainly qualitative, the complexity of interactions with non-humanoid social robots, and limitations mitigating external threats to validity.
On the Level of Measurement of Subjective Psychometric Ratings
Authors: Bolton Matthew L. , Biltekoff Elliot , Wei Jiajun , Humphrey Laura
Published: October 2022

Subjective psychometric ratings are critical tools in human factors engineering. Despite widespread use, there is controversy about whether such ratings can be treated at cardinal levels of measurement. Answering this question is important given that a measure’s level determines what mathematical and statistical operations can be meaningfully applied to them. This paper synthesizes results from an effort (published over several papers) that developed a method for assessing the level of measurement of subjective ratings and used it to evaluate common trust, situation awareness, and workload metrics. This paper synthesizes these results to determine that subjective measures should rarely, if ever, be treated as ratio. It also found that, in a population analysis, some measures (like all the ones considered) can be treated as interval. In all other situations, and especially in analyses or modeling efforts for individuals or small sample sizes, ordinal is the safest default.
Inclusive Recycling: Challenges And Needs Of Wheelchair Users In Hong Kong
Authors: WONG Yi Lin , SIU Kin Wai Michael , LO Chi Hang
Published: October 2022

Recycling activities are common in Hong Kong households because of the establishment of different campaigns and promotions organized by the Government and non-government organizations. However, wheelchair users are excluded from the recycling activities, and the current facilities do not cater for their needs. To address the issues of wheelchair users participating in recycling, this paper examines the design of public recycling facilities in Hong Kong and investigates how these facilities facilitate or hinder wheelchair users from recycling. A model of addressing design considerations of wheelchair users, the AC-AD model is developed based on the empirical data. The importance of self-efficacy of wheelchair persons and the connection between public and private are discussed. Improvements on the facilities are then suggested in the paper.
Using Gaze-based Interaction to Alleviate Situational Mobility Impairment in Extended Reality
Authors: Ghasemi Yalda , Jeong Heejin
Published: October 2022

Significant advancements of eye-tracking technology in extended reality (XR) head-mounted displays have increased the interest in gaze-based interactions. The benefits of gaze interaction proved that it could be a suitable alternative for hand-based interactions when users face situations where they must maintain their position due to mobility impairment. This study aims to assess the user experience of the gaze-based interaction, compared to hand-based interaction, in two movement conditions of static and dynamic. Twenty-four participants took part in this study, and their experience was evaluated in terms of perceived workload, usability, and performance. The results show that gaze-based interactions significantly outperform the hand-based interaction in terms of perceived workload and usability in case of limited mobility. Also, the user performance is significantly higher in gaze-based modes under situational impairment. The findings of this study can be used for designing XR interfaces considering the situation in which the task is performed.
Speeding Behavior when Using Automation: A Descriptive Analysis of Naturalistic Driving Data
Authors: Haus Samantha H. , Gershon Pnina , Mehler Bruce , Reimer Bryan
Published: October 2022

Speeding is a prevalent and risky behavior. This study leveraged the MIT Advanced Vehicle Technology naturalistic driving data to identify and characterize speeding behavior across automation levels including Manual Driving, Adaptive Cruise Control (ACC), and Pilot Assist (PA) that supports both longitudinal and lateral vehicle control. We analyzed 146 hours of motorway driving from 15 participants who each drove an instrumented vehicle for one month. Speeding prevalence, magnitude, and duration distributions were compared across automation levels using logistic mixed effect models. Findings indicated that although PA was the most prevalent driving state during free flow motorway driving, drivers were more likely to speed with ACC compared to during Manual Driving or with PA. Automation, ACC and PA, were associated with longer speeding durations and lower speeding magnitudes compared to driving manually. These findings can inform the development of automation systems that may help reduce speeding behaviors and promote safe driving.
Metrics for Assessing the Quality of NFL Announcers
Authors: Sanaei Mohammadamin , Sepich Nathan C. , Schaffhausen Kristina M. , Gilbert Stephen B.
Published: October 2022

Announcers are one of the most important factors that can affect viewers’ enjoyment of televised sports. Discovering metrics for announcer quality would be useful for predicting future announcer performance and possibly lead to improvement of announcers. The authors tried to extract useful metrics for announcer quality by using behavioral coding of American football game videos. Initial data was gathered by watching the first half of twelve NFL football games of CBS, ESPN, NBS, and FOX, and metrics were compared with the number of viewers of the different channels. While non-weighted metrics had no correlation with the number of viewers, weighting the metrics showed that announcers’ excitement building, context building, and real-time visual analysis have the strongest potential correlation with viewers’ enjoyment.
Beyond Control Room Modernization - Nuclear Concept of Operations Development for Novel Systems Using Operator-In-The-Loop Control Room Simulations
Authors: Ulrich Thomas A. , Boring Ronald L. , Falls Idaho
Published: October 2022

Existing regulations supporting control room modernization activities do not fully address novel system development activities in nuclear process control. The need for the additional guidance is evident in novel system development for new functionality intended for existing nuclear power plants as well as entirely new control systems intended for advanced reactor designs. In particular, the evaluation and use of simulation to support the design process differences between the human factors activities performed for traditional control room modernization and a representative novel system that changes the fundamental concept of operations. We review such an example, namely a thermal power dispatch system intended for an existing commercial reactors that supports steam uses beyond electricity generation. We present the more expansive scope of human factors activities and the reliance on multiple types of simulation-based evaluations needed to support the design process.
Strategy-Specific Decision Making with Incomplete Information
Authors: Sealy William I.N. , Feigh Karen M.
Published: October 2022

Decision making rarely occurs in perfect environments with unlimited time and complete information. Additionally, individual variations in decision strategy are nuanced and time-evolving. It is therefore important to understand the effects of distributions of information under uncertainty, and that we do so with respect to a range of decision strategies. In this study we assess decision making in three decision environments covering both heuristic and analytic strategies. We find that the amount of information presented to the participant and the way in which that information is structured within each cue (across options) significantly affects decision performance in all environments. Additionally, the participants’ information access trends indicate that decision performance is linked with an adaptation of decision strategy to match the environment.
Learning From Failure: A Case Study Of Human Driven Risk Assessment In Medical Simulator Design
Authors: Bartuska Rachel , Tzamaras Haroula , Moore Jason , Miller Scarlett
Published: October 2022

Failure Modes and Effects Analysis (FMEA) is a qualitative and quantitative approach to measuring and analyzing risk that compiles and ranks failure modes, their effects, and their corrective actions. Though widely used, traditional FMEA has been criticized for the lack of a scientific basis behind the Risk Priority Number calculation. To combat this, researchers have argued that Multiple Criteria Decision Making (MCDM) methods should be used to rank failure modes instead. As such, the current paper was developed to present a case study that applies FMEA and MCDM to a Central Venous Catheterization (CVC) training simulator called the Dynamic Haptic Robotic Trainer (DHRT). FMEA was needed because while a beta prototype exists for research purposes, there are several failure modes that prevent this system from wide spread deployment. Our results provide insight into how FMEA can be used to identify a system’s highest priority failure modes and maximize improvement recommendations.
Influencing IoT Device User Privacy Behaviors: An Empirical Study
Authors: Osman Maria Chaparro , Prior Tricia , Rebensky Summer , Nakushian Andrew , Carroll Meredith
Published: October 2022

The prevalence of Internet of Things (IoT) devices is increasing in both volume and variety (Fagan, Megas, Scarfone, & Smith, 2019). Therefore, ensuring users take appropriate measures to protect their privacy is important to guarantee their safety expectations are met. Unfortunately, device users are generally unaware of how devices work and therefore how to properly set up their device’s privacy features (Olmstead & Smith, 2017). The present study evaluated two interventions designed to address these needs. First, in an attempt to increase access and understanding of the terms and conditions by users, a Terms and Conditions Guru was designed that presented important information throughout the IoT device set up. Second, in an attempt to encourage users to adjust their settings in an appropriate manner, user settings profiles were created. This paper presents the methods, results, and recommendations for IoT interface design.
Incorporating driver expectations into a taxonomy of transfers of control for automated vehicles
Authors: Lee Joonbum , Lee Jessica R. , Koenig Madeline L. , Douglas John R. , Domeyer Joshua E. , Lee John D. , Toyoda Heishiro
Published: October 2022

This study expands existing taxonomies for transfer of control (TOC) with driving automation. A TOC taxonomy is necessary to categorize types of TOC, interpret drivers’ behavior during a transition, and assess the safety implications of each TOC type. However, existing taxonomies do not capture important aspects of the driver’s reaction to the transfer because they often only focus on the initiator and receiver. Thus, we synthesized relevant literature and suggested factors for expanding a TOC taxonomy. The literature synthesis revealed that temporal attributes (e.g., urgency) and predictability of TOC are dimensions that can extend existing taxonomies. Based on the findings, we developed a new TOC taxonomy using four factors (initiator, receiver, system predictability, and driver expectation) with relevant use cases. The new taxonomy distinguishes 16 different types of TOCs and enhances our understanding of TOC types and their implications for safety.