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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Two measures of performance in a peg-in-hole manipulation task with force feedback

The results are described from two manipulators on a peg-in-hole task, which is part of a continued effort to develop models for human performance with remote manipulators. Task difficulty is varied by changing the diameter of the peg to be inserted in a 50 mm diameter hole. An automatic measuring system records the distance between the tool being held by the manipulator and the receptacle into which it is to be inserted. The data from repeated insertions are processed by computer to determine task times, accumulated distances, and trajectories. Experiments with both the MA-11 cable-connected master-slave manipulator common to hot cell work and the MA-23 servo-controlled manipulator (with and without force feedback) are described. Comparison of these results with previous results of the Ames Manipulator shows that force feedback provides a consistent advantage.

Hill, J. W.↗
NASA NTRS2007

Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks

Geostationary Operational Environmental Satellite (GOES) Image Navigation and Registration (INR) performance is specified at the 3- level, meaning that 99.7% of a collection of individual measurements must comply with specification thresholds. Landmarks are measured by the Replacement Product Monitor (RPM), part of the operational GOES ground system, to assess INR performance and to close the INR loop. The RPM automatically discriminates between valid and invalid measurements enabling it to run without human supervision. In general, this screening is reliable, but a small population of invalid measurements will be falsely identified as valid. Even a small population of invalid measurements can create problems when assessing performance at the 3-sigma level. This paper describes an additional layer of quality control whereby landmarks of the highest quality ("platinum") are identified by their self-consistency. The platinum screening criteria are not simple statistical outlier tests against sigma values in populations of INR errors. In-orbit INR performance metrics for GOES-12 and GOES-13 are presented using the platinum landmark methodology.

Carr, James L.↗
NASA NTRS2016

Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation

Attention-related human performance limiting states (AHPLS) can cause pilots to lose airplane state awareness (ASA), and their detection is important to improving commercial aviation safety. The Commercial Aviation Safety Team found that the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness, and that distraction of various forms was involved in all of them. Research on AHPLS, including channelized attention, diverted attention, startle / surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors has been implemented to simultaneously measure their physiological markers during high fidelity flight simulation human subject studies. Pilot participants were asked to perform benchmark tasks and experimental flight scenarios designed to induce AHPLS. Pattern classification was employed to distinguish the AHPLS induced by the benchmark tasks. Unimodal classification using pre-processed electroencephalography (EEG) signals as input features to extreme gradient boosting, random forest and deep neural network multiclass classifiers was implemented. Multi-modal classification using galvanic skin response (GSR) in addition to the same EEG signals and using the same types of classifiers produced increased accuracy with respect to the unimodal case (90 percent vs. 86 percent), although only via the deep neural network classifier. These initial results are a first step toward the goal of demonstrating simultaneous real time classification of multiple states using multiple sensing modalities in high-fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Harrivel, Angela R.↗
NASA NTRS2017

Prediction of Cognitive States During Flight Simulation Using Multimodal Psychophysiological Sensing

The Commercial Aviation Safety Team found the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness (ASA), and distraction was involved in all of them. Research on attention-related human performance limiting states (AHPLS) such as channelized attention, diverted attention, startle/surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors was implemented to simultaneously measure their physiological markers during a high fidelity flight simulation human subject study. Twenty-four pilot participants were asked to wear the sensors while they performed benchmark tasks and motion-based flight scenarios designed to induce AHPLS. Pattern classification was employed to predict the occurrence of AHPLS during flight simulation also designed to induce those states. Classifier training data were collected during performance of the benchmark tasks. Multimodal classification was performed, using pre-processed electroencephalography, galvanic skin response, electrocardiogram, and respiration signals as input features. A combination of one, some or all modalities were used. Extreme gradient boosting, random forest and two support vector machine classifiers were implemented. The best accuracy for each modality-classifier combination is reported. Results using a select set of features and using the full set of available features are presented. Further, results are presented for training one classifier with the combined features and for training multiple classifiers with features from each modality separately. Using the select set of features and combined training, multistate prediction accuracy averaged 0.64 +/- 0.14 across thirteen participants and was significantly higher than that for the separate training case. These results support the goal of demonstrating simultaneous real-time classification of multiple states using multiple sensing modalities in high fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Harrivel, Angela R.↗
NASA NTRS1985

Evaluation of 16 measures of mental workload using a simulated flight task emphasizing mediational activity

As aircraft and other systems become more automated, a shift is occurring in human operator participation in these systems. This shift is away from manual control and toward activities that tap the higher mental functioning of human operators. Therefore, an experiment was performed in a moving-base flight simulator to assess mediational (cognitive) workload measurement. Specifically, 16 workload estimation techniques were evaluated as to their sensitivity and intrusion in a flight task emphasizing mediational behavior. Task loading, using navigation problems presented on a display, was treated as an independent variable, and workload-measure values were treated as dependent variables. Results indicate that two mediational task measures, two rating scale measures, time estimation, and two eye behavior measures were reliably sensitive to mediational loading. The time estimation measure did, however, intrude on mediational task performance. Several of the remaining measures were completely insensitive to mediational load.

Wierwille, W. W.↗
NASA NTRS1994

An overview of Space Shuttle anthropometry and biomechanics research with emphasis on STS/Mir recumbent seat system design

The Anthropometry and Biomechanics Laboratory (ABL) at JSC conducts multi-disciplinary research focusing on maximizing astronaut intravehicular (IVA) and extravehicular (EVA) capabilities to provide the most effective work conditions for manned space flight and exploration missions. Biomechanics involves the measurement and modeling of the strength characteristics of the human body. Current research for the Space Shuttle Program includes the measurement of torque wrench capability during weightlessness, optimization of foot restraint, and hand hold placement, measurements of the strength and dexterity of the pressure gloved hand to improve glove design, quantification of the ability to move and manipulate heavy masses (6672 N or 1500 lb) in weightlessness, and verification of the capability of EVA crewmembers to perform Hubble Space Telescope repair tasks. Anthropometry is the measurement and modeling of the dimensions of the human body. Current research for the Space Shuttle Program includes the measurement of 14 anthropometric parameters of every astronaut candidate, identification of EVA finger entrapment hazards by measuring the dimensions of the gloved hand, definition of flight deck reach envelopes during launch and landing accelerations, and measurement of anthropometric design parameters for the recumbent seat system required for the Shuttle/Mir mission (STS-71, Spacelab M) scheduled for Jun. 1995.

Klute, Glenn K.↗
NASA NTRS1975

Kalman filter estimation of human pilot-model parameters

The parameters of a human pilot-model transfer function are estimated by applying the extended Kalman filter to the corresponding retarded differential-difference equations in the time domain. Use of computer-generated data indicates that most of the parameters, including the implicit time delay, may be reasonably estimated in this way. When applied to two sets of experimental data obtained from a closed-loop tracking task performed by a human, the Kalman filter generated diverging residuals for one of the measurement types, apparently because of model assumption errors. Application of a modified adaptive technique was found to overcome the divergence and to produce reasonable estimates of most of the parameters.

Schiess, J. R.↗
NASA NTRS1991

The human operator transfer function: Identification of the limb mechanics subsystem

The objective of our research is to decompose the performance of the human operator in terms of the subsystems that determine the operator's responses in order to establish how the dynamics of these component subsystems influence the operator's performance. In the present experiment, the dynamic stiffness of the human elbow joint was measured at rest and under different levels of biceps muscle activation; this work forms part of the analysis of the limb mechanics subsystem.

Jones, Lynette A.↗
NASA NTRSDate not supplied

Sensorimotor Application of Proposed Methods to Combine the Effects of Multiple Countermeasures for PRisM

Risk associated with human systems is challenging to quantify but is critical for the mission planning and decision making required to enable future Lunar and Martian missions. To address this gap, the Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) project is developing an integrated computational model for CHP mission risk. Much like how MEDPRAT is designed to allow medical resource trades informed by medical risk, CHP-PRA will enable analogous trades in human system risks across multiple CHP functions and capabilities. Human performance is one component of the risk intended to be captured by CHP-PRA through the Performance Risk Model (PRisM). The sensorimotor risk area provides a good frame of reference for investigating the structure of a performance model because most tasks that astronauts are expected to perform require input from the sensory system and/or movement/motor control. Additionally, sensorimotor countermeasures are an area of particular concern for NASA’s Human Research Program because of the increased sensorimotor risk associated with surface operations in Lunar and Martian missions. Thus, a tool that can quickly compare risk reductions of potential countermeasures would be beneficial in guiding research and development of effective countermeasures. In this proof of concept, we present a systematic way to combine multiple performance data sets for humans subjected to different countermeasures such that we can predict the countermeasure(s) that optimize astronaut performance on relevant tasks. PRisM assumes that both the tests that are used to measure countermeasure effectiveness (input data) and the tasks we use to represent astronaut performance, can be broken down and represented as a function/vector of the human systems required to perform that test/task. Through mathematical combination, test data are used to predict performance on astronaut tasks that use similar systems. We propose that when combining countermeasures evaluated using the same test, that only one value should be used to represent their combined effectiveness. We start our analysis with the assumption that two countermeasures together will perform better than each countermeasure individually. Our initial implementation of this framework compares various space motion sickness countermeasures and the most up to date analysis will be demonstrated at the IWS.

Caroline R Austin↗
NASA NTRS2004

Comparing Methods for UAV-Based Autonomous Surveillance

We describe an approach to evaluating algorithmic and human performance in directing UAV-based surveillance. Its key elements are a decision-theoretic framework for measuring the utility of a surveillance schedule and an evaluation testbed consisting of 243 scenarios covering a well-defined space of possible missions. We apply this approach to two example UAV-based surveillance methods, a TSP-based algorithm and a human-directed approach, then compare them to identify general strengths, and weaknesses of each method.

Freed, Michael↗
NASA NTRSDate not supplied

Reach Performance Using Touchscreens Under G and Vibration Conditions

This presentation summarizes prior results from human-in-the-loop experiments that measured the accuracy and precision of human reaches to a touchscreen under a range of altered gravitational and vibrational conditions. From the data, this presentation proposes a method for estimating the worst-case reach accuracy and precision during lunar landings with an eye towards supporting engineering design decisions about human control interfaces and crew operations for lunar missions.

human performance↗
NASA NTRS2014

EMU Suit Performance Simulation

Introduction: Designing a planetary suit is very complex and often requires difficult trade‐offs between performance, cost, mass, and system complexity. To verify that new suit designs meet requirements, full prototypes must be built and tested with human subjects. However, numerous design iterations will occur before the hardware meets those requirements. Traditional draw‐prototype‐test paradigms for research and development are prohibitively expensive with today's shrinking Government budgets. Personnel at NASA are developing modern simulation techniques that focus on a human‐centric design paradigm. These new techniques make use of virtual prototype simulations and fully adjustable physical prototypes of suit hardware. This is extremely advantageous and enables comprehensive design down‐selections to be made early in the design process. Objectives: The primary objective was to test modern simulation techniques for evaluating the human performance component of two EMU suit concepts, pivoted and planar style hard upper torso (HUT). Methods: This project simulated variations in EVA suit shoulder joint design and subject anthropometry and then measured the differences in shoulder mobility caused by the modifications. These estimations were compared to human‐in‐the‐loop test data gathered during past suited testing using four subjects (two large males, two small females). Results: Results demonstrated that EVA suit modeling and simulation are feasible design tools for evaluating and optimizing suit design based on simulated performance. The suit simulation model was found to be advantageous in its ability to visually represent complex motions and volumetric reach zones in three dimensions, giving designers a faster and deeper comprehension of suit component performance vs. human performance. Suit models were able to discern differing movement capabilities between EMU HUT configurations, generic suit fit concerns, and specific suit fit concerns for crewmembers based on individual anthropometry

Cowley, Matthew S.↗
NASA NTRS1988

Steady-state evoked potentials possibilities for mental-state estimation

The use of the human steady-state evoked potential (SSEP) as a possible measure of mental-state estimation is explored. A method for evoking a visual response to a sum-of-ten sine waves is presented. This approach provides simultaneous multiple frequency measurements of the human EEG to the evoking stimulus in terms of describing functions (gain and phase) and remnant spectra. Ways in which these quantities vary with the addition of performance tasks (manual tracking, grammatical reasoning, and decision making) are presented. Models of the describing function measures can be formulated using systems engineering technology. Relationships between model parameters and performance scores during manual tracking are discussed. Problems of unresponsiveness and lack of repeatability of subject responses are addressed in terms of a need for loop closure of the SSEP. A technique to achieve loop closure using a lock-in amplifier approach is presented. Results of a study designed to test the effectiveness of using feedback to consciously connect humans to their evoked response are presented. Findings indicate that conscious control of EEG is possible. Implications of these results in terms of secondary tasks for mental-state estimation and brain actuated control are addressed.

Junker, Andrew M.↗
NASA NTRS1986

The effects of acceleration stress on human workload and manual control

The effects of +Gz stress on operator task performance and workload were assessed. Subjects were presented a two dimensional maze and were required to solve it as rapidly as possible (by moving a light dot through it via a trim switch on a control stick) while under G-stress at levels from +1 Gz to +6 Gz. The G-stress was provided by a human centrifuge. The effects of this stress were assessed by two techniques; (1) objective performance measures on the primary maze-solving task, and (2) subjective workload measures obtained using the subjective workload assessment technique (SWAT). It was found that while neither moderate (+3 Gz) nor high (+5 Gz and +6 Gz) levels of G-stress affected maze solving performance, the high G levels did increase significantly the subjective workload of the maze task.

Gill, R. T.↗
NASA NTRS2016

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

airport surface traffic↗