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At least 451 records · Page 25

Autonomous Diagnostic Imaging Performed by Untrained Operators using Augmented Reality as a Form of "Just-in-Time" Training

We will address the Human Factors and Performance Team, "Risk of performance errors due to training deficiencies" by improving the JIT training materials for ultrasound and OCT imaging by providing advanced guidance in a detailed, timely, and user-friendly manner. Specifically, we will (1) develop an audio-visual tutorial using AR that guides non-experts through an abdominal trauma ultrasound protocol; (2) develop an audio-visual tutorial using AR to guide an untrained operator through the acquisition of OCT images; (3) evaluate the quality of abdominal ultrasound and OCT images acquired by untrained operators using AR guidance compared to images acquired using traditional JIT techniques (laptop-based training conducted before image acquisition); and (4) compare the time required to complete imaging studies using AR tutorials with images acquired using current JIT practices to identify areas for time efficiency improvements. Two groups of subjects will be recruited to participate in this study. Operator-subjects, without previous experience in ultrasound or OCT, will be asked to perform both procedures using either the JIT training with AR technology or the traditional JIT training via laptop. Images acquired by inexperienced operator-subjects will be scored by experts in that imaging modality for diagnostic and research quality; experts will be blinded to the form of JIT used to acquire the images. Operator-subjects also will be asked to submit feedback to improve the training modules used during the scans to improve future training modules. Scanned-subjects will be a small group individuals from whom all images will be acquired.

Martin, D. S.↗

Autonomous Diagnostic Imaging Performed by Untrained Operator Using Augmented Reality as a Form of "Just-in-Time" Training

We will address the Human Factors and Performance Team, "Risk of performance errors due to training deficiencies" by improving the JIT training materials for ultrasound and OCT imaging by providing advanced guidance in a detailed, timely, and user-friendly manner. Specifically, we will (1) develop an audio-visual tutorial using AR that guides non-experts through an abdominal trauma ultrasound protocol; (2) develop an audio-visual tutorial using AR to guide an untrained operator through the acquisition of OCT images; (3) evaluate the quality of abdominal ultrasound and OCT images acquired by untrained operators using AR guidance compared to images acquired using traditional JIT techniques (laptop-based training conducted before image acquisition); and (4) compare the time required to complete imaging studies using AR tutorials with images acquired using current JIT practices to identify areas for time efficiency improvements. Two groups of subjects will be recruited to participate in this study. Operator-subjects, without previous experience in ultrasound or OCT, will be asked to perform both procedures using either the JIT training with AR technology or the traditional JIT training via laptop. Images acquired by inexperienced operator-subjects will be scored by experts in that imaging modality for diagnostic and research quality; experts will be blinded to the form of JIT used to acquire the images. Operator-subjects also will be asked to submit feedback to improve the training modules used during the scans to improve future training modules. Scanned-subjects will be a small group individuals from whom all images will be acquired.

Martin, David S.↗

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Feiveson, Alan↗

Altitude deviations: Breakdowns of an error-tolerant system

Pilot reports of aviation incidents to the Aviation Safety Reporting System (ASRS) provide a window on the problems occurring in today's airline cockpits. The narratives of 10 pilot reports of errors made in the automation-assisted altitude-change task are used to illustrate some of the issues of pilots interacting with automatic systems. These narratives are then used to construct a description of the cockpit as an information processing system. The analysis concentrates on the error-tolerant properties of the system and on how breakdowns can occasionally occur. An error-tolerant system can detect and correct its internal processing errors. The cockpit system consists of two or three pilots supported by autoflight, flight-management, and alerting systems. These humans and machines have distributed access to clearance information and perform redundant processing of information. Errors can be detected as deviations from either expected behavior or as deviations from expected information. Breakdowns in this system can occur when the checking and cross-checking tasks that give the system its error-tolerant properties are not performed because of distractions or other task demands. Recommendations based on the analysis for improving the error tolerance of the cockpit system are given.

Palmer, Everett A.↗

Air Traffic Management-eXploration Testbed for Urban Air Mobility Research and Development

The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.

Testbed↗

Air Traffic Management-eXploration Testbed for Urban Air Mobility Research and Development

The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements- (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.

Simulation↗

An auditory display in a dual-axis tracking task.

Results of a study in which subjects were presented concurrently with the primary task of controlling a second-order plant and the secondary task of controlling a first-order plant. The plant errors for the two tasks were shown on separate visual displays. An auditory display, whose output varied in frequency and volume with the error, was used to supplement the secondary task in half of the runs. To study the effects of the auditory display, two performance measures were obtained: (1) the integral of the squared error (ISE) and (2) the describing functions of the human operator. Statistical analysis of the ISE measures indicated that when the secondary task was supplemented with an auditory display, there was a significant improvement in performance on the secondary task. The performance on the primary task improved on the average, but not significantly. The variances of the ISE values decreased for both the tasks, indicating a more consistent behavior with the auditory display. The describing function analysis showed that supplementing the secondary task with the auditory display increased the low frequency gain of the human operator for this task. The describing functions for the primary task did not show any apparent changes.

Mirchandani, P. B.↗

Fuzzy logic based robotic controller

Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.

Attia, F.↗

HDF-EOS 5 Validator

A computer program partly automates the task of determining whether an HDF-EOS 5 file is valid in that it conforms to specifications for such characteristics as attribute names, dimensionality of data products, and ranges of legal data values. ["HDF-EOS" and variants thereof are defined in "Converting EOS Data From HDF-EOS to netCDF" (GSC-15007-1), which is the first of several preceding articles in this issue of NASA Tech Briefs.] Previously, validity of a file was determined in a tedious and error-prone process in which a person examined human-readable dumps of data-file-format information. The present software helps a user to encode the specifications for an HDFEOS 5 file, and then inspects the file for conformity with the specifications: First, the user writes the specifications in Extensible Markup Language (XML) by use of a document type definition (DTD) that is part of the program. Next, the portion of the program (denoted the validator) that performs the inspection is executed, using, as inputs, the specifications in XML and the HDF-EOS 5 file to be validated. Finally, the user examines the output of the validator.

Ullman, Richard↗

Stage Cylindrical Immersive Display

Panoramic images with a wide field of view intend to provide a better understanding of an environment by placing objects of the environment on one seamless image. However, understanding the sizes and relative positions of the objects in a panorama is not intuitive and prone to errors because the field of view is unnatural to human perception. Scientists are often faced with the difficult task of interpreting the sizes and relative positions of objects in an environment when viewing an image of the environment on computer monitors or prints. A panorama can display an object that appears to be to the right of the viewer when it is, in fact, behind the viewer. This misinterpretation can be very costly, especially when the environment is remote and/or only accessible by unmanned vehicles. A 270 cylindrical display has been developed that surrounds the viewer with carefully calibrated panoramic imagery that correctly engages their natural kinesthetic senses and provides a more accurate awareness of the environment. The cylindrical immersive display offers a more natural window to the environment than a standard cubic CAVE (Cave Automatic Virtual Environment), and the geometry allows multiple collocated users to simultaneously view data and share important decision-making tasks. A CAVE is an immersive virtual reality environment that allows one or more users to absorb themselves in a virtual environment. A common CAVE setup is a room-sized cube where the cube sides act as projection planes. By nature, all cubic CAVEs face a problem with edge matching at edges and corners of the display. Modern immersive displays have found ways to minimize seams by creating very tight edges, and rely on the user to ignore the seam. One significant deficiency of flat-walled CAVEs is that the sense of orientation and perspective within the scene is broken across adjacent walls. On any single wall, parallel lines properly converge at their vanishing point as they should, and the sense of perspective within the scene contained on only one wall has integrity. Unfortunately, parallel lines that lie on adjacent walls do not necessarily remain parallel. This results in inaccuracies in the scene that can distract the viewer and subtract from the immersive experience of the CAVE.

Abramyan, Lucy↗

Data Comm Flight Deck Human-in-the-Loop Simulation

This presentation discusses an upcoming simulation for data comm in the terminal area. The purpose of the presentation is to provide the REDAC committee with a summary of some of the work in Data Comm that is being sponsored by the FAA. The focus of the simulation is upon flight crew human performance variables, such as crew procedures, timing and errors. The simulation is scheduled to be conducted in Sept 2012.

Lozito, Sandra↗

Identifying Outside Influences as Latent Factors to Risk in Human Performance

During the Acquisition Life Cycle for a program, there are several opportunities for the system in design to be adjusted in accordance with its changing landscape as it is being shaped by evolving policy and organizational culture. Human Systems Integration is integral to identifying these opportunities of change as there are a set number of activities that may account for altered operational states, human performance deviations, and overall component engagement if HSI is enacted early enough in the life cycle. Some changes that occur in the operational environment may not be accounted for since the organizational culture and practices are not currently a part of the HSI focus. Likewise, policy changes themselves from a top-to-bottom analysis may not have the appearance of effecting human performance until having gone through a trail-and-error period. Workarounds to adjust for unforeseen policy affects become the system's solution that usually includes changes in the training and education of the operators, maintainers, and support personnel. A system full of workarounds and off-normal practices, that cause operators to disregard the purpose of the design, coupled with the false notion that these activities are proven for successful system operation, is the very definition of “an accident waiting to happen”. Unforeseen changes in policies and practices that cause new and unusual activities to successfully and keep the system running, should be considered latent factors that may cause a potential mishap, and not part of the resilience that humans provide to the successful operation of the system. This presentation will explore how latent factors may find their way into system operations and how they can be identified and addressed.

Human Systems Integration↗

Development of Human System Integration at NASA

Human Systems Integration seeks to design systems around the capabilities and limitations of the humans which use and interact with the system, ensuring greater efficiency of use, reduced error rates, and less rework in the design, manufacturing and operational deployment of hardware and software. One of the primary goals of HSI is to get the human factors practitioner involved early in the design process. In doing so, the aim is to reduce future budget costs and resources in redesign and training. By the preliminary design phase of a project nearly 80% of the total cost of the project is locked in. Potential design changes recommended by evaluations past this point will have little effect due to lack of funding or a huge cost in terms of resources to make changes. Three key concepts define an effective HSI program. First, systems are comprised of hardware, software, and the human, all of which operate within an environment. Too often, engineers and developers fail to consider the human capacity or requirements as part of the system. This leads to poor task allocation within the system. To promote ideal task allocation, it is critical that the human element be considered early in system development. Poor design, or designs that do not adequately consider the human component, could negatively affect physical or mental performance, as well as, social behavior. Second, successful HSI depends upon integration and collaboration of all the domains that represent acquisition efforts. Too often, these domains exist as independent disciplines due to the location of expertise within the service structure. Proper implementation of HSI through participation would help to integrate these domains and disciplines to leverage and apply their interdependencies to attain an optimal design. Via this process domain interests can be integrated to perform effective HSI through trade-offs and collaboration. This provides a common basis upon which to make knowledgeable decisions. Finally, HSI must be considered early in the requirements development phase of system design and acquisition. This will provide the best opportunity to maximize return on investment (ROI) and system performance. HSI requirements must be developed in conjunction with capability ]based requirements generation through functional. HSI requirements will drive HSI metrics and embed HSI issues within the system design. After a system is designed, implementation of HSI oversights can be very expensive. An HSI program should be included as an integral part of a total system approach to vehicle and habitat development. This would include, but not limited to, workstation design, D&C development, volumetric analysis, training, operations, and human -robotic interaction. HSI is a necessary process for Human Space Flight programs to meet the Agency Human ]System standards and thus mitigate human risks to acceptable levels. NASA has been involved in HSI planning, procedures development, process, and implementation for many years, and has been building several internal and publicly accessible products to facilitate HSI fs inclusion in the NASA Systems Engineering Lifecycle. Some of these products include: NASA STD 3001 Volumes 1 and 2, Human Integration Design Handbook, NASA HSI Implementation Plan, NASA HSI Implementation Plan Templates, NASA HSI Implementation Handbook, and a 2 ]hour short course on HSI delivered as part of the NASA Space and Life Sciences Directorate Academy. These products have been created leveraging industry best practices and lessons learned from other Federal Government agencies.

Whitmore, Mihriban↗

Digital Elevation Map Parametric Error Analysis Using Corresponding NAC Images

Future lunar landing systems, particularly those used to land humans on the lunar surface aspart of the ARTEMIS program, will require precision navigation relative to the lunar surface. The most common way to meet these stringent navigation require-ments is through terrain relative navigation (TRN), which localizes a spacecraft by comparing descent im-agery with a predefined map of the surface. The accu-racy achievable using TRN is limited by the accuracy of the reference Digital Elevation Map (DEM). It is therefore critical for future lunar missions that potential errors in DEMs be quantified. This paper describes one of NASA’s current efforts to develop a process for evaluating lunar DEM quality.

Chris R Gnam↗

Preliminary Characterization Results from the DebriSat Project

The DebriSat project is a continuing effort sponsored by NASA and DoD to update existing break-up models using data obtained from two separate hypervelocity impact tests used to simulate on-orbit collisions. To protect the fragments resulting from the impact tests, "soft-catch" arenas made of polyurethane foam panels were utilized. After each impact test, the test chamber was cleaned and debris resulting from the catastrophic demise of the test article were collected and shipped to the University of Florida for post-impact processing. The post-impact processing activities include collecting, characterizing, and cataloging of the fragments. Since the impact tests, a team of students has been working to characterize the fragments in terms of their mass, size, shape, color and material content. The focus of the 20 months since the impact tests has been on the collection of 2 millimeters- and larger fragments resulting from impact test on the 56 kilogram-representative LEO (Low Earth Orbit) satellite referred to as DebriSat. To date we have recovered in excess of 115,000 fragments, 30,000 more than the prediction of 85,000 fragments from the existing model. We continue to collect fragments but have transitioned to the characterization phase of the post-impact activities. Since the start of the characterization phase, the focus has been to utilize automation to (i) expedite fragment characterization process and (ii) minimize human-in-the- loop. We have developed and implemented such automated processes; e.g., we have automated the data entry process to reduce operator errors during transcription of the measurement data. However, at all steps of the process, there is human oversight to ensure the integrity of the data. Additionally, we have developed and implemented repeatability and reproducibility tests to ensure that the instrumentation used in the characterization process is accurate and properly calibrated. In this paper, the implemented processes are described and preliminary results presented. Additionally, lessons learned from the implemented automations and their impacts on the integrity of the results are discussed.

Rivero, M.↗

System-Wide Error Attribution in Multi-Vehicle Operations: Theoretical Explanation, Implications, and Applications

In multi-vehicle aerial operation contexts, a single or several human operators (m) are responsible for managing multiple uncrewed vehicles (N). This is referred to as the m:N operational paradigm. When automation error occurs during m:N operations, especially if multiple vehicles exhibit automation error, a question is raised: What level of system globality will the error be attributed to? Globality refers to the levels within the conceptual hierarchy of a perceptual object. Significant costs could be incurred if the error is falsely attributed to a higher globality level than it should be (e.g., multiple groups of vehicles as opposed to a single vehicle), and those vehicles are subsequently subject to grounding and evaluation/maintenance. Likewise, it could be problematic if error is falsely attributed to a component (i.e., a lower globality level), resulting in ongoing, unsafe operation of vehicles that should be grounded or evaluated. Thus, to meet required safety standards and facilitate commercial viability, multi-vehicle operators must be capable of appropriately attributing the level of globality of automation error within the system they are responsible for.

Error↗

Input noise approximation in tracker modeling

The validity of approximating random Gaussian distributed inputs used in human response modeling by sums of discrete sine waves is studied. An ideal rectangular power density spectrum is simulated using both filtered Gaussian white noise and sums-of-discrete sine waves with three different input cutoff frequencies in the same compensatory tracking task. Resulting normalized tracking error and quality operator observations are used to investigate apparent discrepancies in human operator characteristics. Results show that discrete and continuous input tracking data compare favorable when the power in the crossover region is taken into account.

Torrey, P. F.↗