Human Factors Engineering Research Articles

Urban rail transit FAO system: technological development and trends

This paper introduces the worldwide history of fully automatic operation (FAO) system in urban rail transit, followed by the development status in China. Then, the architecture and characteristics of the FAO system are described, and the analysis method of system design requirements is proposed based on the human factors engineering. The key technologies are introduced from the aspects of signaling system, vehicle system, communication system, traffic integrated automation system and reliability, availability, maintainability, and safety (RAMS) assurance. Furthermore, based on the independent practical experience of the FAO system, this paper summarizes the management methods for the construction and operation of FAO lines and prospects its future development trends toward a more intelligent urban rail transit system.

Guiding Transformation: The Role of a Design Philosophy

Unlike renewables such as wind and photovoltaics, nuclear power is a carbon-free source of energy that offers reliable, dispatchable baseload energy. This unique characteristic makes nuclear energy an important component of the U.S. mix of carbon-free energy, and thus, a major contributor to achieving the goals laid out in the Paris Agreement. However, the current fleet of nuclear power plants are being outpriced by other energy sources, such as natural gas. One contributor to the high cost of nuclear is the outdated concept of operations. The current fleet of nuclear reactors employs the same concept of operations they started with over half a century ago. Idaho National Laboratory’s (INL’s) Human Factors Engineering (HFE) team under the U.S. Department of Energy’s Light Water Reactor Sustainability Program is engaged in helping the nuclear fleet modernize their control rooms. The goal is to transform nuclear power plant operators’ perceptions to improve efficient and safe plant operation. A major component to successfully transforming an aged control room with advanced technology is to use a design philosophy that guides the modernization effort. This paper discusses design philosophy and the role it plays. Also discussed is the initial approach to design philosophy and adherence to safety and regulatory requirements. Last, a brief discussion of how INL’s HFE team plans to implement a design philosophy that can be used industry wide.

Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style

The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.

Human Factors Engineering in Infection Prevention & Control: Opportunities, Examples, and the Future

Effective and practical infection prevention and control (IPC) processes and protocols are vital to safety of patients and health care workers (HCWs) as well as improving public health. This interdisciplinary panel, composed of experts in IPC, public health, medicine, and human factors engineering (HFE), will discuss the urgent need for developing partnerships with HFE experts for improving IPC across the continuum of care (hospital-to-home), provide examples for consequences of not using HFE principles, and approaches in health care system design and delivery during both ‘normal’ and extraordinary (e.g., COVID-19 pandemic) times, describe previous successful partnerships among IPC, public health and HFE, and delineate possible ways forward for HFE-informed IPC and public health.

A Perfect Storm Averted: Flawed Systems, a Dropped Ball, and Cognitive Biases Delay a Critical Diagnosis.

This is the first case of Cancer Morbidity, Mortality, and Improvement Rounds, a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. This case highlights how multiple overlapping factors contributed to a delay in diagnosing disseminated tuberculosis in a patient with lung cancer. The discussion focuses on the ways that cognitive biases contributed to the delayed diagnosis in a patient who, with the benefit of hindsight, exhibited several signs and symptoms suggesting tuberculosis.Cancer Morbidity, Mortality, and Improvement Rounds is a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. For purposes of clarity, each case focuses on a single theme, although, as is true for all medical incidents, there are almost always multiple, overlapping, contributing factors. The quality improvement paradigm used here, which focuses on root cause analyses and opportunities to improve care delivery systems, was previously outlined in this journal.1.

Senior Leaders’ Panel on Symbiosis in Aviation – The Human Factors Engineer / Pilot Cooperation

Senior Leaders’ Panel on Symbiosis in Aviation – The Human Factors Engineer / Pilot Cooperation

Communicating Level of Certainty Associated with Human Factors Findings and Recommendations in Healthcare

While there is a need for human factors engineering (HFE) in health systems design, the pace of operations in most healthcare systems often requires deviation from optimal HFE practices. We must provide sufficiently useful and usable findings to the design team and stakeholders to support project decisions while also tempering their expectations and properly calibrating their level of certainty around the findings and recommendations. As members of an HFE team in a series of projects related to the implementation of a new electronic health record (EHR) in a large healthcare system, we describe some early efforts with project teams and initial missteps that limited the effectiveness of HFE work. We also describe communication strategies we are piloting that appear to achieve better results in terms of project team engagement, stakeholder buy-in, and validity and utility of findings.

Design of Smart Head–Mounted Display Technology: A Convergent Mixed-Methods Study

Introduction: The purpose of this study was to characterize functional impairments and human factor considerations that affect perceptions and preferences for head-mounted display (HMD) technology for adults with low vision and chronic eye disease. Methods: Through a convergent mixed-methods design, participants with visual impairments (age-related macular degeneration, diabetic retinopathy, glaucoma, or retinitis pigmentosa) were recruited. Participants completed the Impact of Vision Impairment (IVI) questionnaire, used commercially available HMDs (eSight, NuEyes, and Epson Moverio), and were interviewed. The IVI was used to identify groups with low, moderate, and high vision–related quality of life (VRQOL). Transcribed interviews were analyzed using a thematic approach. The survey and qualitative findings were integrated using mixed-methods joint display analysis. Results: Twenty-one participants were enrolled (mean age of 58.2 years, 57% male, median Snellen acuity of 20/40 [range: 20/20–hand movement]). An equal number ( n = 9) expressed a preference for eSight and NuEyes, while ( n = 3) preferred the Moverio. Participants emphasized ease of use, including HMD controls and screen, as common reasons for preference. Those with lower IVI well-being scores preferred eSight due to vision improvement. Those with moderate IVI well-being scores preferred NuEyes due to comfort and size. Those with high IVI well-being scores cited usability as the most important feature. Discussion: User preferences for HMD features were associated with VRQOL. A mixed-methods approach explained how varying degrees of visual impairment and HMD preferences were qualitatively related to usability at the individual level. Implications for Practitioners: To increase acceptance, new HMD development for low vision should focus on performance, usability, and human factors engineering. Although HMD technology can benefit individuals with low vision, device features and functions vary in meaningful ways based on vision parameters. Practitioners should be aware of how patient and device variations influence preferences when they recommend wearable systems and optimize training to harness these systems.

On the Level of Measurement of Subjective Psychometric Ratings

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.

How Safe Is Cancer Care?

Cancer Morbidity, Mortality, and Improvement Rounds is a series of articles intended to explore the unique safety risks experienced by oncology patients through the lens of quality improvement, systems and human factors engineering, and cognitive psychology. For purposes of clarity, each case focuses on a single theme, although, as is true for all medical incidents, there are almost always multiple, overlapping, contributing factors. The quality improvement paradigm used here, which focuses on root cause analyses and opportunities to improve care delivery systems, was previously outlined in this journal.

In the Face of New Challenges; Effective Human Factors Engineering for Software as Medical Device Products

This paper tackles challenges facing human factors professionals when transitioning into working with Software as Medical Device products. Specifically, it outlines the challenges Novo Nordisk A/S has faced when it comes to applying human factors considerations when developing Software as Medical Device products and ensuring regulatory compliance. It showcases the efforts Novo Nordisk A/S has implemented to meet these challenges and conclude on the learnings Novo Nordisk A/S has had with the proposed solutions.

In the Face of New Challenges; Effective Human Factors Engineering for Software as Medical Device Products

This paper tackles challenges facing human factors professionals when transitioning into working with Software as Medical Device products. Specifically, it outlines the challenges Novo Nordisk A/S has faced when it comes to applying human factors considerations when developing Software as Medical Device products and ensuring regulatory compliance. It showcases the efforts Novo Nordisk A/S has implemented to meet these challenges and conclude on the learnings Novo Nordisk A/S has had with the proposed solutions.

An EEG study of human trust in autonomous vehicles based on graphic theoretical analysis.

With the development of autonomous vehicle technology, human-centered transport research will likely shift to the interaction between humans and vehicles. This study focuses on the human trust variation in autonomous vehicles (AVs) as the technology becomes increasingly intelligent. This study uses electroencephalogram data to analyze human trust in AVs during simulated driving conditions. Two driving conditions, the semi-autonomous and the autonomous, which correspond to the two highest levels of automatic driving, are used for the simulation, accompanied by various driving and car conditions. The graph theoretical analysis (GTA) is the primary method for data analysis. In semi-autonomous driving mode, the local efficiency and cluster coefficient are lower in car-normal conditions than in car-malfunction conditions with the car approaching. This finding suggests that the human brain has a strong information processing ability while facing predictable potential hazards. However, when it comes to a traffic light with a car malfunctioning under the semi-autonomous driving mode, the characteristic path length is higher for the car malfunction manifesting a weak information processing ability while facing unpredictable potential hazards. Furthermore, in fully automatic driving conditions, participants cannot do anything and need low-level brain function to take emergency actions as lower local efficiency and small worldness for car malfunction. Our results shed light on the design of the human-machine interaction and human factor engineering on the high level of an autonomous vehicle.

Study on Ergonomic Design of Artificial Intelligence Lower Limb Assist Brace for the Elderly.

The ergonomic design study of artificial intelligence lower limb-assisted brace for the elderly is a new design standard of lower limb-assisted brace for the elderly with mobility problems. Based on human factors engineering, this study tested and analyzed the advantages and disadvantages of human lower limb motion mechanics, human gait motion law, and existing lower limb assisted brace design cases at home and abroad and concluded that the common external assisted method is less man-machine efficient than the internal assisted method. Therefore, a new brace joint rotation curvature, component parameters, and other key information were designed based on the structure of the medial assistance method. With the help of the engineering and scientific analysis methods in human factors engineering, the designed machines and systems are made more adaptable to the physiological and psychological characteristics of human beings. This study explores the interaction between humans and machines and the rationality of their mutual integration, which can effectively avoid repetitive strain injuries and other muscle diseases over time for users in the process of assistance and achieve efficiency, health, and safety. Subsequently, Rhino software was used for digital modeling, physical prototyping, experimental testing, and analysis of the design solution and continuous optimization of the design. At the same time, the perceptual engineering design method was utilized to meet the humanized aesthetic design requirements. The prototype of the design study was finally completed, which is more in line with the evaluation criteria of “human-machine-environment system” than the existing market design in terms of functional rationality, human-machine performance, and human experience. This demonstrates the validity of the design method and is an important reference for the design standard of the lower limb support for the elderly.

Traffic Safety Improvement via Optimizing Light Environment in Highway Tunnels

Driving in tunnel areas depends more heavily on light conditions than that on open roadways. Traditional lighting systems in highway tunnels adjust lighting parameters only caring about outside light luminance, and focus is usually on energy conservation; however, little concern is about drivers’ actual physical and psychological needs. How to leverage the enormous research progress of traffic safety, light environment, human factors engineering, and modern lighting sources to create an ideal tunnel light environment that aids with ensuring driving safety and lower interference effects caused by the change of light environment will greatly improve safety level and reduce adverse influence on drivers’ visual health in a tunnel area. An intelligent lighting control system designed with multiple influence factors are systematically considered. Based on sensor data from outside natural light conditions, target lighting parameters are determined per each lighting zone requires; then, lighting commands will be transferred and parsed by adaptive lighting controllers and modules, eventually LED lighting properties are altered step by step. This system helps a lot with optimizing tunnel lighting quality and improving drivers’ visual performance; as a result, it contributes to lower the fluctuation of drivers’ workload and get a smooth traffic flow, and ultimately this technically ensures physical and mental health of drivers in a tunnel area.

Maritime Autonomous Surface Ships: Automation Transparency for Nearby Vessels

In the future, maritime autonomous surface ships (MASS) will become more advanced, and mariners will move from the bridge to remote operation centres. To avoid dangerous situations and frequent intervention from the operators, a MASS needs to perceive the environment and calculate the current state and future intention of nearby ships. Another challenge for a MASS is to explain the decisions of its algorithms and make the artificial intelligence’s decisions transparent to not only the operators, but also external stakeholders, such as passengers, vessel traffic services, and nearby ships. This is called automation transparency. In this paper we focus on how MASS, through various means of maritime communication, can (1) express their own state and intention to other ships and (2) perceive other ships’ state and intention. Towards that, we first analyse current maritime communication methods in terms of how well they can be expressed and perceived by today’s MASS in comparison to traditional ships. Next, we analyse which gaps in their communication should be focused on to maximise safety at sea. Finally, we present multiple design recommendations for naval architects, human factors engineers, and interaction designers who are designing and building the next generation of MASS.

Problem Analysis and Optimization of Public Toilet Design in a University Teaching Building Based on Human Factors Engineering Theory

Based on the collection of 539 questionnaires from different populations that people spend an average of 36 minutes a day in the toilet, which is 14 minutes on average for the toilet, equivalent to more than two years time in the toilet, so the personalized design of toilet has become a big demand of human beings. This study will take the toilets in the West No.1, East No.1 and Wen No.1 teaching buildings of a university as the research objects with personalized and rationalized design of toilets as the main research content. Through the field investigation and issue of questionnaires on the toilets in the three teaching buildings, the characteristics and deficiencies of the toilets in the teaching buildings of universities are explored. On this basis, based on the knowledge and practice of human factors engineering, environmental behavior, psychology and other related disciplines, this paper puts forward some methods and suggestions to solve the toilet problems in teaching buildings of this school.

“Don't drop the patient:” Health information in a postpandemic world

Building on technological advances and existing currents of a healthcare system in flux, the COVID-19 pandemic has brought about perhaps the most rapid transformation in human health and healthcare seen in our times. Even as new opportunities such as telemedicine, remote care, and rapid precision health practices are poised to improve access and care for populations, the increasing sophistication of this transformation has brought with it new levels of complexity, fragmentation, and silos. The singular outcome of this system is the vast number of novel ways for miscommunication, loss of information in transition, and breakdowns in the cognitive continuity of care. We refer to these failure modes as “dropping the patient” and adopt a mantra of “don't drop the patient” which examines our emerging health system in the context of patient-centered continuity. In this light, we investigate bright spots and pitfalls, and we offer insights from Human Factors Engineering, Human Centered Design, and Human System Integration, which provide tools and methods to codesign and codevelop continuous and resilient services that are inclusive, sustainable, and effective.

Room of Hazards: A Comparison of Differences in Safety Hazard Recognition Among Various Hospital-Based Healthcare Professionals and Trainees in a Simulated Patient Room.

Adverse events in hospitals are common. While studies have used simulated patient rooms to assess healthcare trainees' skills in detecting safety hazards, few have explored the characteristics of safety hazards that make them more or less identifiable to healthcare workers. We sought to determine differences in hospital-based safety hazard identification among physicians, nurses, and other staff members. Healthcare workers were invited to identify safety hazards in a simulated patient room with intentionally placed hazards. Responses were transcribed and compared between physicians (MD), nurses (RN), and other hospital-based healthcare professionals and trainees (other). Data were analyzed using nonparametric statistical analysis. Twelve physicians, 29 nurses, and 26 other staff members participated in this study. Different professions identified different numbers of total hazards with nurses identifying more hazards than other professions (RN: 9.59, MD: 9.17, other: 6.35; P = 0.001). All professions had difficulty identifying hazards associated with omission (e.g., no precaution sign: MD: 8.3%, RN: 3.4%, other: 0%) or hazards requiring 2-step logical thinking (e.g., intravenous heparin for patient with head laceration: MD: 0%, RN: 6.9%, other: 0%). Physicians, nurses, and others identified different numbers of total hazards, and few participants identified hazards associated with omission or 2-step logical thinking. While previous studies have found differences in types of hazards identified among different healthcare members, we identified hazards that were collectively challenging for all participants to identify. Future studies should target identification of these types of hazards, using human factor engineering to decrease risk of patient harm.

Development of a human factors-based tool for evaluating and improving infection prevention and control protocols

Background: Infection prevention and control (IPC) protocols and guidelines are important quality management tools for educating care professionals and standardizing care processes. However, most of the actual care (ie, work as done) differ from protocol recommendations (ie, work as imagined). No tool or set of criteria has been established for how to develop human-centered IPC protocols. The goal of this research was to develop a standardized human-factors analysis method to provide healthcare organizations with a tangible framework to improve protocol usefulness and usability. Methods: The proposed analysis method combines principles from human-factors engineering (ie, usability heuristics, systems ambiguity framework) and instructional design. Relevant literature was analyzed by experts in human factors and clinical experts to develop a tool with criteria such as visualization and method ambiguity. Overall, 5 IPC-related protocols from a large academic hospital were selected from an electronic database and were evaluated using the proposed criteria. Results: During application of the analysis method, 70 human-factors–related problems were identified across 5 IPC protocols (eg, heater cooler cleaning), including violation of design heuristics and the presence of ambiguity. Frequently violated human-factors design principles included appearance and/or visibility (ie, visual display of content), visualization (ie, providing illustrative examples), and method ambiguity (ie, lack of clarity on how to complete a task). Figure 1 provides a sample of the human-factors problems identified and suggested solutions. Only minor modifications (ie, clarification of criteria definitions) were needed on the final tool. Conclusions: The human-factors–based tool developed in this study can be used both to develop new IPC protocols and to evaluate and improve existing protocols.Funding: The CDC funded this work. This material is based upon work supported by the Naval Sea Systems Command under Contract No. N00024-13-D-6400, Task Order NH076. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Naval Sea Systems Command (NAVSEA) or the US CDC.Disclosures: None