Model-Based Usability Analysis of Safety-Critical Systems: A Formal Methods Framework

Complex, safety-critical systems are designed with a broad range of automated and configurable components, and usability problems often emerge for the end user during setup, operation, and troubleshooting procedures. Usability evaluations should consider the entire human-device interface including displays, controls, hardware configurations, and user documentation/procedures. To support the analyst, human factors researchers have developed a set of methods and measures for evaluating human-system interface usability, while formal methods researchers have developed a set of model-based technologies that enable mathematical verification of desired system behaviors. At the intersection of these disciplines, an evolving set of model-based frameworks enable highly automated verification of usability early in the design cycle. Models can be abstracted to enable broad coverage of possible problems, while measures can be formally verified to "prove" that the system is usable. Currently, frameworks cover a subset of the target system and user behaviors that must be modeled to ensure usability: procedures, visual displays, user controls, automation, and possible interactions among them. Similarly, verification methodologies focus on a subset of potential usability problems with respect to modeled interactions. This work provides an integrated formal methods framework enabling the holistic modeling and verification of safety-critical system usability. Building toward the framework, a set of five, novel approaches extend the capabilities of extant frameworks in different ways. Each approach is demonstrated in a medical device case study to show how the methods can be employed to identify potential usability problems in existing systems. A formal approach to documentation navigation models an end user navigating through a printed or electronic document and verifies page reachability. A formal approach to procedures in documentation models an end user executing steps as written and aids in identifying problems involving what device components are identified in task descriptions, what system configurations are addressed, and what temporal orderings of procedural steps could be improved. A formal approach to hardware configurability models end-user motor capabilities, relationships among the user and device components in the spatial environment, and opportunities for the user to physically manipulate components. An encoding tool facilitates the modeling process, while a verification methodology aids in ensuring that configurable hardware supports correct end- user actions and prevents incorrect ones. A formal approach to interface understandability models what information is provided to the end user through visual, audible, and haptic sensory channels, including explanations provided in accompanying documentation. An encoding tools facilitates the development of models and specifications, while the verification methodology aids in ensuring that what is displayed on the device is consistent; and, if needed, an explanation of what is displayed is provided in documentation. A formal approach to controlled actuators leverages an existing modeling technique and data collected from other engineering activities to model actuator dynamics mapping to referent data. An encoding tool facilitates model development, and a verification methodology aids in validating the model with respect to source data. Finally, new methodologies are combined within the integrated framework. A model architecture supports the analyst in representing a broad range of interactions among constituent framework models, and a set of ten specifications is developed to enable holistic usability verification. An implementation of the framework is demonstrated within a case study based on a medical device under development. This application shows how the framework could be utilized early in the design of a safety-critical system, without the need for a fully implemented device or a team of human evaluators.Ph.D., Biomedical Science -- Drexel University, 201

Architecting Integrated System Health Management for Airworthiness

Integrated System Health Management (ISHM) for Unmanned Aerial Systems (UAS) has been a new area of research - seeking to provide situational awareness to mission and maintenance operations, and for improved decision-making with increased self-autonomy. This research effort developed an analytic architecture and an associated discrete-event simulation using Arena to investigate the potential benefits of ISHM implementation onboard an UAS. The objective of this research is two-fold: firstly, to achieve continued airworthiness by investigating the potential extension of UAS expected lifetime through ISHM implementation, and secondly, to reduce life cycle costs by implementing a Condition-Based Maintenance (CBM) policy with better failure predictions made possible with ISHM. Through a series of design experiments, it was shown that ISHM presented the most cost-effective improvement over baseline systems in situations where the reliability of the UAS is poor (relative to manned systems) and the baseline sensor exhibited poor qualities in terms of missed detection and false alarm rates. From the simulation results of the test scenarios, it was observed that failure occurrence rates, sensor quality characteristics and ISHM performance specifications were significant factors in determining the output responses of the model. The desired outcome of this research seeks to provide potential designers with top-level performance specifications of an ISHM system based on specified airworthiness and maintenance requirements for the envisaged ISHM-enabled UAS

Usability Challenges with Insulin Pump Devices in Diabetes Care: What Trainers Observe with First-Time Pump Users

Insulin pumps are designed for the self-management of diabetes mellitus in patients and are known for their complexity of use. Pump manufacturers engage trainers to teach patients how to use the devices correctly to control the symptoms of their disease. Usability research related to insulin pumps and other infusion pumps with first-time users as participants has centered on the relationship between user interface design and the effectiveness of task completion. According to prior research, the characteristics of system behavior in a real life environment remain elusive. A suitable approach to acquire information about potential usability problems encountered by first-time users is to obtain this information from the health care professionals who train them. The purpose of the study was to discover the lived experiences and shared impressions of insulin pump trainers during training sessions with first-time users. Interpretative Phenomenological Analysis (IPA) was used to uncover the phenomena associated with usability challenges that first-time users of insulin pumps face when learning to use the device. Six participants representing a homogeneous sample were recruited from a wide geographic area in the United States, and semi-structured interviews containing open-ended questions were conducted with the respondents. The data from the lived experiences and shared impressions of the participants were used to develop the following five super-ordinate themes: Emotion-charged Environment, Personalized Training, Safety Issues and Disaster Planning, Professional Dedication, and The Voice. The essence of participants’ experience was described around the pivotal moment when the training sessions are successfully completed and insulin pump therapy becomes alive. The findings of this study have implications for information systems professionals who conduct research on the safe design and usability of safety critical medical devices. In addition, the findings from this study create opportunities for practice to improve the initiation of insulin pump therapy in patients with diabetes

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications

A.S.P.E.N. Parenteral Nutrition Safety Consensus Recommendations

Parenteral nutrition (PN) serves as an important therapeutic modality that is used in adults, children, and infants for a variety of indications. The appropriate use of this complex therapy aims to maximize clinical benefit while minimizing the potential risks for adverse events. Complications can occur as a result of the therapy and as the result of the PN process. These consensus recommendations are based on practices that are generally accepted to minimize errors with PN therapy, categorized in the areas of PN prescribing, order review and verification, compounding, and administration. These recommendations should be used in conjunction with other A.S.P.E.N. publications, and researchers should consider studying the questions brought forth in this document

Data management and Data Pipelines: An empirical investigation in the embedded systems domain

Context: Companies are increasingly collecting data from all possible sources to extract insights that help in data-driven decision-making. Increased data volume, variety, and velocity and the impact of poor quality data on the development of data products are leading companies to look for an improved data management approach that can accelerate the development of high-quality data products. Further, AI is being applied in a growing number of fields, and thus it is evolving as a horizontal technology. Consequently, AI components are increasingly been integrated into embedded systems along with electronics and software. We refer to these systems as AI-enhanced embedded systems. Given the strong dependence of AI on data, this expansion also creates a new space for applying data management techniques. Objective: The overall goal of this thesis is to empirically identify the data management challenges encountered during the development and maintenance of AI-enhanced embedded systems, propose an improved data management approach and empirically validate the proposed approach.Method: To achieve the goal, we conducted this research in close collaboration with Software Center companies using a combination of different empirical research methods: case studies, literature reviews, and action research.Results and conclusions: This research provides five main results. First, it identifies key data management challenges specific to Deep Learning models developed at embedded system companies. Second, it examines the practices such as DataOps and data pipelines that help to address data management challenges. We observed that DataOps is the best data management practice that improves the data quality and reduces the time tdevelop data products. The data pipeline is the critical component of DataOps that manages the data life cycle activities. The study also provides the potential faults at each step of the data pipeline and the corresponding mitigation strategies. Finally, the data pipeline model is realized in a small piece of data pipeline and calculated the percentage of saved data dumps through the implementation.Future work: As future work, we plan to realize the conceptual data pipeline model so that companies can build customized robust data pipelines. We also plan to analyze the impact and value of data pipelines in cross-domain AI systems and data applications. We also plan to develop AI-based fault detection and mitigation system suitable for data pipelines

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research