Nathan Lau

Measurement Sufficiency Versus Completeness: Integrating Safety Cases into Verification and Validation in Nuclear Control Room Modernization

This paper reviews verification and validation (V&V) as applied in the context of nuclear power plant control room modernization. A common approach for V&V is summative or late-stage evaluation of the finalized design through a process called integrated system validation. Yet, common practice in user-centered design is to conduct evaluations early on in-progress system prototypes. Iterative, early-stage evaluation can form the basis of a safety case argument to ensure the regulatory acceptability of the new human-machine interface in the control room. It is argued that a series of formative evaluations provide more complete evidence of the safety of the new system than does a single summative evaluation.

The Role of HCI in Cross-Sector Research on Grand Challenges

Cross-sector or collaborative research between government, academia, industry, and public stakeholders is essential to find innovative solutions to 21st century grand challenges. The proliferation of cyberinfrastructure and cyber physical systems will play critical roles in managing information and large scale human machine systems. While available data, processing power, and model complexities grow at an accelerating rate, the information processing capacity of human cognition does not. Human computer interaction research is needed to bridge this gap and enable the development, operation, and analytics of emerging, integrated, large-scale, multi-user, realtime systems.

Eye tracking in surgical education: gaze-based dynamic area of interest can discriminate adverse events and expertise

BackgroundEye-gaze metrics derived from areas of interest (AOIs) have been suggested to be effective for surgical skill assessment. However, prior research is mostly based on static images and simulated tasks that may not translate to complex and dynamic surgical scenes. Therefore, eye-gaze metrics must advance to account for changes in the location of important information during a surgical procedure.MethodsWe developed a dynamic AOI generation technique based on eye gaze collected from an expert viewing surgery videos. This AOI updated as the gaze of the expert moved with changes in the surgical scene. This technique was evaluated through an experiment recruiting a total of 20 attendings and residents to view 10 videos associated with and another 10 without adverse events.ResultsDwell time percentage (i.e., gaze duration) inside the AOI differentiated video type (U = 13508.5, p < 0.001) between videos with the presence (Mdn = 16.75) versus absence (Mdn = 19.95) of adverse events. This metric also differentiated participant group (U = 14029.5, p < 0.001) between attendings (Mdn = 15.45) and residents (Mdn = 19.80). This indicates that our dynamic AOIs reflecting the expert eye gaze was able to differentiate expertise, and the presence of unexpected adverse events.ConclusionThis dynamic AOI generation technique produced dynamic AOIs for deriving eye-gaze metrics that were sensitive to expertise level and event characteristics.

Selecting, evaluating, and translating psychophysiological measures into clinical settings: From lab to practice

Physiological data collection methods are unobtrusive, passive, continuous, and objective. The information afforded by sensors collecting physiological data can be transformed to represent operator performance estimates and stress state visualizations in real time. This technology is conducive to healthcare settings, creating the potential to inform healthcare operators of their current performance and physiological statuses. Despite the broad and pervasive utility of sensor technology, its applications in healthcare are underutilized and misunderstood. This is likely due to the combination of a lack of understanding of the full capabilities of sensor technology, a scarcity of demonstrated uses in healthcare, and an uncertainty surrounding translation and implementation into practice. Implementing findings from providers’ physiological data can be met with challenges, especially in the healthcare setting. Clinicians are most frequently concerned with patient care, and may not always recognize the importance of their own physiological state. While transitioning sensor technology from personal monitoring purposes to a data collection tool can be challenging, passive data collection via sensor technology may have significant value for learners and experienced practitioners. The goals of this paper are to: 1. raise awareness of sensor technology and its utility in clinical settings; 2. provide empirical examples of how to use sensor technology to answer basic and applied questions pertaining to clinical workflow; and 3. exemplify scalability and translatability of findings from sensor technology studies in clinical settings.

Human Factors in Cybersecurity – Perspectives from Industries

Today, cybersecurity is impacting every individual and industry, but the level of effort from the human factors community seems negligible compared to the magnitude of the current security challenge. This panel invites professionals in the healthcare, computer and network, higher education, and automotive industries to share experiences, lessons learned and solutions. The panel characterizes the security landscape in different industries and facilitate discussion on human factors research and applications to address the formidable security challenge.

Distributed Situation Awareness in Patient Flow Management: An Admission Case Study

Managing patient flow can be an effective strategy to reduce idling hospital beds, thereby lowering the healthcare cost without sacrificing quality of care. However, improving patient flow can be a major challenge due to the complex patterns of communication across diverse hospital staff. To identify improvement opportunities, this paper investigates whether the Distributed Situation Awareness (DSA) framework can feasibly and meaningfully model Situation Awareness (SA) in patient flow. The investigation involved a case study on modeling the DSA of the admission phase in patient flow for a level 1 trauma center. A DSA model combining task, knowledge, and social networks was created, showing feasibility of the framework in depicting the distribution and transaction of knowledge across workers and information systems. Further, a true elective admission case was mapped onto the DSA model, verifying its practical merits.

Examining Cybersecurity of Cyberphysical Systems for Critical Infrastructures Through Work Domain Analysis

Objective: The aim of this study was to apply work domain analysis for cybersecurity assessment and design of supervisory control and data acquisition (SCADA) systems. Background: Adoption of information and communication technology in cyberphysical systems (CPSs) for critical infrastructures enables automated and distributed control but introduces cybersecurity risk. Many CPSs employ SCADA industrial control systems that have become the target of cyberattacks, which inflict physical damage without use of force. Given that absolute security is not feasible for complex systems, cyberintrusions that introduce unanticipated events will occur; a proper response will in turn require human adaptive ability. Therefore, analysis techniques that can support security assessment and human factors engineering are invaluable for defending CPSs. Method: We conducted work domain analysis using the abstraction hierarchy (AH) to model a generic SCADA implementation to identify the functional structures and means–ends relations. We then adopted a case study approach examining the Stuxnet cyberattack by developing and integrating AHs for the uranium enrichment process, SCADA implementation, and malware to investigate the interactions between the three aspects of cybersecurity in CPSs. Results: The AHs for modeling a generic SCADA implementation and studying the Stuxnet cyberattack are useful for mapping attack vectors, identifying deficiencies in security processes and features, and evaluating proposed security solutions with respect to system objectives. Conclusion: Work domain analysis is an effective analytical method for studying cybersecurity of CPSs for critical infrastructures in a psychologically relevant manner. Application: Work domain analysis should be applied to assess cybersecurity risk and inform engineering and user interface design.

Human performance measures for the evaluation of process control human-system interfaces in high-fidelity simulations

We reviewed the available literature on measuring human performance to evaluate human-system interfaces (HSIs), focused on high-fidelity simulations of industrial process control systems, to identify best practices and future directions for research and operations. We searched the available literature and then conducted in-depth review, structured coding, and analysis of 49 articles, which described 42 studies. Human performance measures were classified across six dimensions: task performance, workload, situation awareness, teamwork/collaboration, plant performance, and other cognitive performance indicators. Many studies measured performance in more than one dimension, but few studies addressed more than three dimensions. Only a few measures demonstrated acceptable levels of reliability, validity, and sensitivity in the reviewed studies in this research domain. More research is required to assess the measurement qualities of the commonly used measures. The results can provide guidance to direct future research and practice for human performance measurement in process control HSI design and deployment.

Application of Work Domain Analysis for Cybersecurity

Cyber Physical Systems (CPSs) are pervasive in businesses and critical infrastructures that are becoming targets of cyber attack by our adversaries. The presence of advanced persistent threats or zero-day attacks suggests that cyber defense must include recovery response from cyber intrusions. Recovery response must rely on adaptive ability of the CPS as the impact of zero-day attacks cannot be anticipated. In unanticipated situations, human adaptive ability can contribute greatly to the recovery from cyber intrusions. This paper presents Work Domain Analysis (WDA) as a human factors engineering tool for evaluating system and identifying solutions supporting operators in their response to cyber threats. The cyber attack on Australian Maroochy Water Services is used as illustrative case study to demonstrate the potential of WDA in enhancing cyber security of CPS.

System-Task Analytical Framework for Monitor Assessment

User interfaces of modern control rooms in process plants are mostly designed around computer monitors paired with mice and keyboards; thus, the number of monitors can have practical significance in shaping operator behaviors and performance, at least in terms access to displays and controls. For this reason, the number of monitors available to the operators is an important consideration in workstation design. This paper presents the System-Task Analytical Framework for Monitor Assessment (STAFMA) - a systematic, analytical method for determining the number of monitors required for operating a process. Adapting Cognitive Work Analysis, STAFMA consists of six phases of analysis - work domain, control tasks, strategies/plant procedures, control room crews, operators, and monitor allocation. The goal of this adaptation is to provide a systematic and analytical basis for guiding practitioners on the number of monitors for operating a process. The six phases of analysis also illustrate the interaction between various design choices and the required number of monitors.