Predicting human performance in space environments
Predicting human performance in space environments
Olson, D.↗
SEARCH · Search NASA
Results for “Human Performance”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Human performance benefits gained by dynamic instructions compared to smart PDFs
Human performance benefits gained by dynamic instructions compared to smart PDFs In recent years multiple nuclear utilities have deployed an electronic work management solution to replace the traditional paper-based processes. There are many benefits of electronic work management solutions compared to paper processes, such as a more streamlined review and approval process of work packages and a better way to track and resolve any potential bottlenecks causing delays in the review process. These benefits have been recognized where electronic work management solutions have been successfully deployed. However the utilities also hoped the new solution would help the field worker conduct his/her job more efficiently, correctly, and safely. Unfortunately, the industry is now realizing that the deployed solutions did not fully help them reach that goal. The electronic work management solutions present the work instructions as an electronic copy (i.e., a portable document format (PDF)) of the paper instruction. The PDF versions used in these electronic work management solutions have some ability for data input, notes, and mark-ups, but are unable to provide many additional benefits compared to using paper. In fact, conducting work using a PDF on a tablet can be more cumbersome than with a paper instruction. For example, flipping back and forth in a paper instruction can be time consuming, but it is not at all as frustrating as scrolling back and forth on a tablet or continuously having to navigate between tabs. The researchers at Idaho National Laboratory (INL) approached the next step beyond smart PDFs from a human factors perspective. In close collaboration with multiple utilities they investigated how to present instruction content and how to design the interaction with the instruction to improve the workers performance and efficiency. Their solution is a dynamic presentation of the instruction that guides the worker through the correct path as well as ensuring the worker is on the correct component. The solution also automatically validates input and provides guidance if unexpected conditions are identified. A well-designed solution has the opportunity to vastly reduce the risk of human errors in the field, such as preventing actions on incorrect component or unintentionally skipping steps. The human factors researchers at INL leveraged their expertise, existing human performance tools, and a great amount of involvement from field workers in multiple utilities to develop and evaluate design concepts that will provide the human performance and efficiency benefits that the electronic work management solutions fall short to deliver. This paper will describe in detail how these new design concepts improve human performance.
47 OTHER INSTRUMENTATION↗
Computational Models of Human Performance: Validation of Memory and Procedural Representation in Advanced Air/Ground Simulation
The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.
Corker, Kevin M.↗
Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)
Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.
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Human performance models for computer-aided engineering
This report discusses a topic important to the field of computational human factors: models of human performance and their use in computer-based engineering facilities for the design of complex systems. It focuses on a particular human factors design problem -- the design of cockpit systems for advanced helicopters -- and on a particular aspect of human performance -- vision and related cognitive functions. By focusing in this way, the authors were able to address the selected topics in some depth and develop findings and recommendations that they believe have application to many other aspects of human performance and to other design domains.
Elkind, Jerome I.↗
An Experimental Analysis on the CNS Simulator Comparing Human Performance between Operators and Students
This study, as a previous study of the SHEEP project, aims to identify differences in human performance data through experiments with students and operators using CNS (Compact Nuclear Simulator). To achieve this goal, this experiment seeks to analyze the correlation of measured human performance between students and operators through a randomized factorial experiment design. Five human performances are measured. In addition, several scenarios and related procedures have been developed for the CNS experiments.
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Effect of Changing Weight and Mass on Human Performance in a Lunar Prototype Spacesuit
Physical effort, compensation, and controllability in a spacesuit can be affected by suit mass and gravity level. Because of limitations in certain reduced-gravity simulators and the finite selection of lunar prototype suits, it is difficult to ascertain how a change in suit mass affects suited human performance. One method of simulating a change in mass is to vary the total gravity-adjusted weight (TGAW), which is defined as the sum of the suit mass and subject mass, multiplied by the gravity level. PURPOSE: To determine if two methods of changing TGAW during parabolic flight - changing suit mass or gravity level - affect subjective ratings of suited human performance equally. METHODS: A custom weight support structure was connected to a lunar prototype spacesuit, allowing the addition of mass to the suit while maintaining a near-constant center of mass. In the varied-weight (VW) series, suit mass (120 kg) was constant at 0.1 G, 0.17 G, and 0.3 G, yielding TGAWs of 196, 333, and 588 N, assuming an 80-kg subject. In the varied-mass (VM) series, gravity level was constant at 0.17 G and suit mass was 89, 120, and 181 kg, yielding TGAWs of 282, 333, and 435 N. The 333 N condition was common to both series. Direct comparison was not possible due to limited adjustability of suit mass and limited options for parabolic profiles. Five astronaut subjects (80.3 11.8 kg) completed 4 different tasks (walk, bag pickup, lunge, and shoveling) in all conditions and provided ratings of perceived exertion (RPE) and the gravity compensation and performance scale (GCPS) upon completion of each task. RESULTS: Where VM and VW series overlapped, RPE and GCPS trendlines were similar. Mean RPE and GCPS at 333 N was 8.4 and 3.7. Mean RPE and GCPS for VM was 7.8 and 3.8 for 282 N and 9.8 and 4.1 for 435 N. Extrapolation of the VM trend to match VW TGAWs 196 and 588 N predicts an RPE of 6.5 and 12.3 and GCPS of 4.4 and 5.9, whereas the measured VW values for RPE were 8.1 and 9.8 and GCPS were 4.4 and 3.7. CONCLUSION: Modeling a change in suit mass by altering weight alone may be an adequate simulation through a limited range when looking at gross metrics of subjective suited human performance. Whether altering weight alone will be sufficient for more precise metrics of human performance, and across a wider range of activities, still needs further study.
Norcross, Jason R.↗
Effect of Changing Weight and Mass on Human Performance in a Lunar Prototype Spacesuit
Physical effort, compensation, and controllability in a spacesuit can be affected by suit mass and gravity level. Because of limitations in certain reduced-gravity simulators and the finite selection of lunar prototype suits, it is difficult to ascertain how a change in suit mass affects suited human performance. One method of simulating a change in mass is to vary the total gravity-adjusted weight (TGAW), which is defined as the sum of the suit mass and subject mass, multiplied by the gravity level. PURPOSE: To determine if two methods of changing TGAW during parabolic flight - changing suit mass or gravity level - affect subjective ratings of suited human performance equally.METHODS: A custom weight support structure was connected to a lunar prototype spacesuit, allowing the addition of mass to the suit while maintaining a near-constant center of mass. In the varied-weight (VW) series, suit mass (120 kg) was constant at 0.1-g, 0.17-g, and 0.3-g, yielding TGAWs of 196, 333, and 588 N, assuming an 80-kg subject. In the varied-mass (VM) series, gravity level was constant at 0.17-g and suit mass was 89, 120, and 181 kg, yielding TGAWs of 282, 333, and 435 N. The 333 N condition was common to both series. Direct comparison was not possible due to limited adjustability of suit mass and limited options for parabolic profiles. Five astronaut subjects (80.311.8 kg) completed 4 different tasks (walk, bag pickup, lunge, and shoveling) in all conditions and provided ratings of perceived exertion (RPE) and the gravity compensation and performance scale (GCPS) upon completion of each task. RESULTS: Where VM and VW series overlapped, RPE and GCPS trend lines were similar. Mean RPE and GCPS at 333 N was 8.4 and 3.7. Mean RPE and GCPS for VM was 7.8 and 3.8 for 282 N and 9.8 and 4.1 for 435 N. Extrapolation of the VM trend to match VW TGAWs 196 and 588 N predicts an RPE of 6.5 and 12.3 and GCPS of 4.4 and 5.9, whereas the measured VW values for RPE were 8.1 and 9.8 and GCPS were 4.4 and 3.7. CONCLUSION: Modeling a change in suit mass by altering weight alone may be an adequate simulation through a limited range when looking at gross metrics of subjective suited human performance. Whether altering weight alone will be sufficient for more precise metrics of human performance, and across a wider range of activities, still needs further study
Chappell, Steve↗
Surface EVA Readiness and Performance Optimization (SERPO): An Integrated Human Performance Approach
Explore the source record for details and available documents.
Rachel L. Thompson↗
INL Human Performance Improvement Guide, GDE-863
Guidance on Integrating Human Performance Improvement including guidance on Developing Area Specific Implementation Plans, Tool Usage, and Building the Capacity for Resiliency aka Failing Safely.
99 GENERAL AND MISCELLANEOUS↗
Cognition and procedure representational requirements for predictive human performance models
Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods including procedural backtracking with concurrent search, temporal reasoning, and constraint checking for partial ordering of procedures. Finally, the representation is being linked to models of human decision making processes that include heuristic, propositional and prescriptive judgement models that are sensitive to the procedural content in which the valuative functions are being performed.
Corker, K.↗
Human performance measurement: Validation procedures applicable to advanced manned telescience systems
As telescience systems become more and more complex, autonomous, and opaque to their operators it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed as they relate to total system validation. The assumption is made that human interaction with the automated system will be required well into the Space Station Freedom era. Candidate human performance measurement-validation techniques are discussed for selected ground-to-space-to-ground and space-to-space situations. Most of these measures may be used in conjunction with an information throughput model presented elsewhere (Haines, 1990). Teleoperations, teleanalysis, teleplanning, teledesign, and teledocumentation are considered, as are selected illustrative examples of space related telescience activities.
Haines, Richard F.↗
Feature extraction of event-related potentials using wavelets: an application to human performance monitoring
This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.
Evoked Potentials↗
Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring
This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.
Trejo, Leonard J.↗
Human Performance in Simulated Reduced Gravity Environments
NASA is currently designing a new space suit capable of working in deep space and on Mars. Designing a suit is very difficult and often requires trade‐offs between performance, cost, mass, and system complexity. Our current understanding of human performance in reduced gravity in a planetary environment (the moon or Mars) is limited to lunar observations, studies from the Apollo program, and recent suit tests conducted at JSC using reduced gravity simulators. This study will look at our most recent reduced gravity simulations performed on the new Active Response Gravity Offload System (ARGOS) compared to the C‐9 reduced gravity plane. Methods: Subjects ambulated in reduced gravity analogs to obtain a baseline for human performance. Subjects were tested in lunar gravity (1.6 m/sq s) and Earth gravity (9.8 m/sq s) in shirt‐sleeves. Subjects ambulated over ground at prescribed speeds on the ARGOS, but ambulated at a self‐selected speed on the C‐9 due to time limitations. Subjects on the ARGOS were given over 3 minutes to acclimate to the different conditions before data was collected. Nine healthy subjects were tested in the ARGOS (6 males, 3 females, 79.5 +/- 15.7 kg), while six subjects were tested on the C‐9 (6 males, 78.8 +/- 11.2 kg). Data was collected with an optical motion capture system (Vicon, Oxford, UK) and was analyzed using customized analysis scripts in BodyBuilder (Vicon, Oxford, UK) and MATLAB (MathWorks, Natick, MA, USA). Results: In all offloaded conditions, variation between subjects increased compared to 1‐g. Kinematics in the ARGOS at lunar gravity resembled earth gravity ambulation more closely than the C‐9 ambulation. Toe‐off occurred 10% earlier in both reduced gravity environments compared to earth gravity, shortening the stance phase. Likewise, ankle, knee, and hip angles remained consistently flexed and had reduced peaks compared to earth gravity. Ground reaction forces in lunar gravity (normalized to Earth body weight) were 0.4 +/- 0.2 on the ARGOS, but only 0.2 +/- 0.1 on the C‐9. Discussion: Gait analysis showed differences in joint kinematics and temporal‐spatial parameters between the reduced gravity simulators and with respect to earth gravity. Although most of the subjects chose a somewhat unique ambulation style as a result of learning to ambulate in a new environment, all but two were consistent with keeping an Earth‐like gait. Learning how reduced gravity affects ambulation will help NASA to determine optimal suit designs, influence mission planning, help train crew, and may shed light on the underlying methods the body uses to optimize gait for energetic efficiency. Conclusion: Kinematic and kinetic analysis demonstrated noteworthy differences between an offloaded environment and 1‐g, as would be expected. The analysis showed a trend to change the ambulation style in an offloaded environment to a rolling‐loping walk (resembling crosscountry skiing) with increased swing time. This ambulation modification, particularly in the ARGOS, indicated that the relative kinetic energy of the subject was increased, on average, per the static body weight compared to the 1‐g condition. How much of this was influenced by the active offloading of the ARGOS system is unknown.
Cowley, Matthew↗
Integrating Mindfulness with Human Performance in High Complexity Environments - 19498
This paper includes a survey of both scientific and technical literature studies of mindfulness interventions in a variety of industries and populations and proposes potential applications in complex nuclear waste operations. Mindfulness training techniques have been utilized in various forms for decades in high consequence work in both public and private enterprise. The traditional safety nomenclature has simply used different words to describe many of the same concepts that mindfulness practice addresses. Historically, human performance improvement (HPI) has focused on task, mission and error-likely conditions. These safety programs recognize that human behavior is the source of most errors and focus on identification of specific error precursors (mind not on task, incorrect mental picture, etc.). Workers in nuclear and related industries have been trained to recognize these error precursors but have received little training on what to do about them. The techniques of mindfulness align well with HPI programs currently utilized in commercial and government nuclear operations. Indeed, Chapter 5 of the Department of Energy Human Performance Improvement Handbook (DOE-HDBK-1028-2009) includes a discussion of mindfulness with respect to human performance. Mindfulness training supplements current performance improvement efforts by giving workers the tools to not just recognize error-likely conditions within themselves, but also gives them methods to mitigate them. The mindfulness practices presented here focus on self-awareness rather than task-awareness. Workers can apply these techniques in all aspects of their lives which in turn addresses many of the distractions previously identified as error precursors (stress at home or at work, physical discomforts, mind not on task, etc.). The application of mindfulness techniques through integration with established Integrated Safety Management Systems (ISMS) has the potential to improve the safe performance of nuclear waste operations and increase the breadth of organizational safety culture. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
EVA Health and Human Performance Benchmarking Study
Multiple HRP Risks and Gaps require detailed characterization of human health and performance during exploration extravehicular activity (EVA) tasks; however, a rigorous and comprehensive methodology for characterizing and comparing the health and human performance implications of current and future EVA spacesuit designs does not exist. This study will identify and implement functional tasks and metrics, both objective and subjective, that are relevant to health and human performance, such as metabolic expenditure, suit fit, discomfort, suited postural stability, cognitive performance, and potentially biochemical responses for humans working inside different EVA suits doing functional tasks under the appropriate simulated reduced gravity environments. This study will provide health and human performance benchmark data for humans working in current EVA suits (EMU, Mark III, and Z2) as well as shirtsleeves using a standard set of tasks and metrics with quantified reliability. Results and methodologies developed during this test will provide benchmark data against which future EVA suits, and different suit configurations (eg, varied pressure, mass, CG) may be reliably compared in subsequent tests. Results will also inform fitness for duty standards as well as design requirements and operations concepts for future EVA suits and other exploration systems.
Abercromby, A. F.↗
Comparison of Human Performance between Operators and Students Using Rancor Microworld Simulator: A Preliminary Result
This paper describes an experiment using the Rancor Microworld simulator to probe into differences in human performance between students and actual operators. Six human performance measures – 1) time, 2) error, 3) workload, 4) situational awareness, 5) attention patterns, and 6) number of manipulations – are measured from experiments. The experiment has been conducted for 11 operators and 20 students so far. More experiments and analyses will be continued. Further experimental studies using Rancor Microworld are expected to be able to collect additional data that may be missing from full-scope studies and contribute to items that can support human reliability data.
99 GENERAL AND MISCELLANEOUS↗