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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

BioSentinel: Build your own BioSentinel Model!

BioSentinel will conduct the first study of the biological response to space radiation outside LEO since the Apollo missions. The project will investigate the biological effects of space radiation, and will provide an adaptable platform to perform human relevant measurements in multiple space environments in the future, including on lunar and Mars landers and orbiters.

BioSentinel↗
NASA NTRS2024

Determining Simulation Fidelity Necessary for Evaluating Onboard Vehicle Capabilities and Crew Roles on Long Duration Exploration Missions Beyond Low-Earth Orbit

Identification of onboard vehicle capabilities and crew roles and responsibilities necessary for achieving effective human-systems collaboration will require iterative cycles of concept development and empirical evaluation of human performance in complex operations. This report presents the results of an effort to lay the groundwork for determining the level of fidelity of simulated environments most suitable for validating concepts and evaluating implementations of a new Human Systems Integration Architecture (HSIA) that will support the flight crew on long duration exploration missions beyond low-Earth orbit. To do that, we conducted a literature review on simulation fidelity and surveyed simulation capabilities inside and outside of NASA used in NASA-sponsored research. We also analyzed two International Space Station (ISS) vehicle anomalies to identify the types of scenario events and crew activities that may need to be simulated. Our survey findings reveal that most NASA simulation facilities are designed to achieve high physical fidelity while HSIA risk mitigation requires simulation emphasizing task and functional fidelity aspects. A trade analysis shows that, for standard and requirement development, evaluation conducted using synthetic task environments with inexperienced participants will support testing a wide variety of conditions and yield findings robust enough to be generalized to a wide variety of designs on which developed standards and requirements might be levied while allowing human performance standard measures to be collected using consistent methods across tasks and conditions. For technology/tool development, because findings will only need to be generalized to the actual target environment in which the technology/tool will be used, it is more suitable to evaluate the prototypes in a scaled world that preserves functional relationships present in the actual target environment with intended user populations. To wrap up, we give an overview of a well-known synthetical task environment in the space domain and discuss what it takes to construct a synthetic task environment.

simulation fidelity↗
NASA NTRS2013

Relating Standardized Visual Perception Measures to Simulator Visual System Performance

Human vision is quantified through the use of standardized clinical vision measurements. These measurements typically include visual acuity (near and far), contrast sensitivity, color vision, stereopsis (a.k.a. stereo acuity), and visual field periphery. Simulator visual system performance is specified in terms such as brightness, contrast, color depth, color gamut, gamma, resolution, and field-of-view. How do these simulator performance characteristics relate to the perceptual experience of the pilot in the simulator? In this paper, visual acuity and contrast sensitivity will be related to simulator visual system resolution, contrast, and dynamic range; similarly, color vision will be related to color depth/color gamut. Finally, we will consider how some characteristics of human vision not typically included in current clinical assessments could be used to better inform simulator requirements (e.g., relating dynamic characteristics of human vision to update rate and other temporal display characteristics).

Kaiser, Mary K.↗
NASA NTRSDate not supplied

Utilizing Gaps and Performance Measures to Inform NASA Environmental Control and Life Support Systems and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring multiple capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for future exploration architectures is defined as a capability gap. Capability gaps are not technology specific. Each capability gap may be closed with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is very important. KPP definition for reliability, dormancy, and integration needs are hard to define but critical. Outside of technical considerations, the programmatic factors of the estimated time to develop the technology and how the technology validation objectives are matured are strong considerations in which technologies should be pursued and how they should leverage earlier mission elements. The Environmental Control and Life Support (ECLSS) and Crew Health and Performance (CHP) capability areas are decomposed to high level gaps. While KPPs should be technology agnostic, they can be used to both compare technologies and measure progress of technology development over time. KPPs help define when the gap is closed, and the core mission objectives can be accomplished. Proposed technology improvements to enhance a capability should balance improved KPPs and against investments in other capabilities that are not yet closed. A selection of gaps, KPPs, and validation objectives and their formulation, current state, and how they inform capability roadmap planning are discussed.

Life Support↗
NASA NTRS2003

Optoelectronic Apparatus Measures Glucose Noninvasively

An optoelectronic apparatus has been invented as a noninvasive means of measuring the concentration of glucose in the human body. The apparatus performs polarimetric and interferometric measurements of the human eye to acquire data from which the concentration of glucose in the aqueous humor can be computed. Because of the importance of the concentration of glucose in human health, there could be a large potential market for instruments based on this apparatus.

Ansari, Rafat R.↗
NASA NTRS2012

Conceptual Design Standards for eXternal Visibility System (XVS) Sensor and Display Resolution

NASA is investigating eXternal Visibility Systems (XVS) concepts which are a combination of sensor and display technologies designed to achieve an equivalent level of safety and performance to that provided by forward-facing windows in today s subsonic aircraft. This report provides the background for conceptual XVS design standards for display and sensor resolution. XVS resolution requirements were derived from the basis of equivalent performance. Three measures were investigated: a) human vision performance; b) see-and-avoid performance and safety; and c) see-to-follow performance. From these three factors, a minimum but perhaps not sufficient resolution requirement of 60 pixels per degree was shown for human vision equivalence. However, see-and-avoid and see-to-follow performance requirements are nearly double. This report also reviewed historical XVS testing.

Bailey, Randall E.↗
NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗
NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗
NASA NTRS2014

Biosentinel: Developing a Space Radiation Biosensor

Ionizing radiation presents a major challenge to human exploration and long-term residence in space. The deep-space radiation spectrum includes highly energetic particles that generate double strand breaks (DSBs), deleterious DNA lesions that are usually repaired without errors via homologous recombination (HR), a conserved pathway in all eukaryotes. While progress identifying and characterizing biological radiation effects using Earth-based facilities has been significant, no terrestrial source duplicates the unique space radiation environment.We are developing a biosensor-based nanosatellite to fly aboard NASAs Space Launch System Exploration Mission 1, expected to launch in 2017 and reach a 1AU (astronomic unit) heliocentric orbit. Our biosensor (called BioSentinel) uses the yeast S. cerevisiae to measure DSBs in response to ambient space radiation. The BioSentinel strain contains engineered genetic defects that prevent growth until and unless a radiation-induced DSB near a reporter gene activates the yeasts HR repair mechanisms. Thus, culture growth and metabolic activity directly indicate a successful DSB-and-repair event. In parallel, HR-defective and wild type strains will provide survival data. Desiccated cells will be carried within independent culture microwells, built into 96-well microfluidic cards. Each microwell set will be activated by media addition at different time points over 18 months, and cell growth will be tracked continuously via optical density. One reserve set will be activated only in the occurrence of a solar particle event. Biological measurements will be compared to data provided by onboard physical dosimeters and to Earth-based experiments.BioSentinel will conduct the first study of biological response to space radiation outside Low Earth Orbit in over 40 years. BioSentinel will thus address strategic knowledge gaps related to the biological effects of space radiation and will provide an adaptable platform to perform human-relevant measurements in multiple space environments. We hope that it can therefore be used on the ISS, on and around other planetary bodies as well as other exploration platforms as a self-contained system that will allow us to compare and calibrate different radiation environments.BioSentinels results will be critical for improving interpretation of the effects of space radiation exposure, and for reducing the risk associated with long-term human exploration.

space radiation↗
NASA NTRS2025

Measuring Unique Contextual Factors: Group Living Skills

BACKGROUND The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures used to assess behavioral health and performance risks related to future exploration-class space missions. During the HFBP-EM suite development, the importance of assessing unique contextual factors to understand the drivers of team dynamics was identified. Group living skills are a unique workplace skill which applies to those coworkers who live and work together. As mission lengths become longer, the line between work and non-work life may blur. Extreme living conditions such as spaceflight can result in increased stress over time, negatively impact mood and well-being, decrease team cohesion and increase conflict, deteriorate task performance, and potentially reduce mission success [1]. With no breaks in their isolated and confined environment possible, living with a messy, inconsiderate crewmember can add to the stress. Alternatively, crews with good group living skills may support one another, mitigating the negative effects of the extreme environment. There was no direct measure of group living skills. This work sought to fill this measurement gap and collect data related to group living in isolated, confined, extreme (ICE) environments. METHODS Group living skills as an astronaut competency area were developed with the input of experts familiar with ICE environments. Distinct aspects of this competency were reviewed and discussed by a NASA-invited group of spaceflight experts in 2015 to identify individual and team behavioral health and performance measures for operational environments. This work resulted in a 5-item measure focused on group living experiences with each crewmember (or the crew as a whole). A 6th item asks whether an individual would go on another mission with a particular crewmember or crew as a measure of future-oriented group living, or team viability. The measure was deployed in 24 teams living and working together in isolated and confined environments (e.g., International Space Station, space mission simulation analogs). RESULTS & DISCUSSION In this presentation, we will summarize results which indicate the Group Living Skills (GLS) Survey is a reliable, valid, and operationally feasible measure. Reliability was evaluated in several ways. Two-way multilevel mixed models revealed strong repeated measures reliability (ICC2 = .902, Omega between = .954). Reliability of change within teams was strong (Rc = .81). Factor analysis showed a consistent two-factor structure when individuals rated either the whole crew, all individuals, just peers, or a focal roommate. The latter used a sociometric approach to rating the GLS of the roommates. The two factors were tidiness and being considerate of others. We assessed the criterion-related validity of GLS, by examining GLS operationalized as the team-level aggregated GLS Survey scores as a predictor of team viability, team cohesion, and team performance. We used generalized mixed models to account for the repeated measures and longitudinal data. The marginal R2 change was used to determine the extent to which GLS were related to the team outcomes while controlling for mission day and campaign. Results suggested GLS was strongly related to team viability (marginal R2 change = .40), team cohesion (marginal R2 change = 0.28), social cohesion (marginal R2 change = 0.25), and moderately related to task cohesion (marginal R2 change = 0.18). GLS scores had a small relationship with team performance (marginal R2 change = .08). Results support GLS as a measure that can be used to capture group living skills of crews who live and work together in ICE. Because the items were written to be broadly applicable, less extreme environments with teams living and working together for some length of time also benefit from this measure (e.g., college roommates, camps). See Landon et al. (2024) for full results [2]. SUMMARY We report reliability and validity evidence for a new measure that assesses the Group Living Skills for teams that live and work in operational environments such as spaceflight.

J C W Miller↗
NASA NTRS1998

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.↗
NASA NTRS1999

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↗