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At least 73 records · Page 4

Behavioral Medicine Risks and Mitigations in Isolated, Confined, and Extreme Environments

Human spaceflight beyond low Earth orbit will present unique environmental challenges to astronauts’ operational performance and well-being. Crews will need to work and live in confined and hazardous environments for prolonged missions that involve variable workloads and limitations to privacy, food options, exercise capabilities, leisure outlets, and communication with ground support personnel and loved ones. Currently, behavioral and cognitive risks of spaceflight are mitigated by selecting exceptionally resilient crews and providing extensive individual and team skills training pre-mission, as well as in-mission crew support via a suite of countermeasures targeting sleep and performance optimization, stress management, family support, and team cohesion. However, current countermeasures are difficult or impossible to implement in long-distance exploration as they require real-time communication with Earth and routine resupply. New countermeasure approaches are needed to adapt and enhance the current complement for the new challenges ahead. NASA therefore conducts research at ground-based spaceflight analogs to aid in characterizing the behavioral and cognitive risks of living and working in isolated, confined, and extreme (ICE) operational environments. Antarctic research stations are among the few long-duration ICE analogs in existence and are therefore uniquely positioned to support behavioral medicine research to enable human exploration beyond Earth. In this review, we will discuss previous and ongoing efforts to better understand spaceflight behavioral medicine risks, as well as validate new countermeasure approaches for future missions to the moon and Mars.

Behavioral Health↗

Human Factors in Accidents Involving Remotely Piloted Aircraft

This presentation examines human factors that contribute to RPA mishaps and provides analysis of lessons learned. RPA accident data from U.S. military and government agencies were reviewed and analyzed to identify human factors issues. Common contributors to RPA mishaps fell into several major categories: cognitive factors (pilot workload), physiological factors (fatigue and stress), environmental factors (situational awareness), staffing factors (training and crew coordination), and design factors (human machine interface).

Merlin, Peter William↗

Stabilized NADH as a Countermeasure for Jet Lag

Current remedies for jet lag (phototherapy, melatonin, stimulant, and sedative medications) are limited in efficacy and practicality. The efficacy of a stabilized, sublingual form of reduced nicotin amide adenine dinucleotide (NADH, ENADAlert, Menuco Corp.) as a countermeasure for jet lag was examined. Because NADH increases cellular production of ATP and facilitates dopamine synthesis, it may counteract the effects of jet lag on cognitive functioning and sleepiness. Thirty-five healthy, employed subjects participated in this double-blind, placebo-controlled study. Training and baseline testing were conducted on the West Coast before subjects flew overnight to the East Coast, where they would experience a 3-hour time difference. Upon arrival, individuals were randomly assigned to receive either 20 mg of sublingual stabilized ADH (n=18) or identical placebo tablets (n=17). All participants completed computer-administered tests (including CogScreen7) to assess changes in cognitive functioning, mood, and sleepiness in the morning and afternoon. Jet lag resulted in increased sleepiness for over half the participants and deterioration of cognitive functioning for approximately one third. The morning following the flight, subjects experienced lapses of attention in addition to disruptions in working memory, divided attention, and visual perceptual speed. Individuals who received NADH performed significantly better on 5 of 8 cognitive and psychomotor test measures (P less than or equal to 0.5) and showed a trend for better performance on the other three measures (P less than or equal to .l0). Subjects also reported less sleepiness compared with those who received placebo. No adverse effects were observed with NADH treatment. Stabilized NADH significantly reduced jet lag-induced disruptions of cognitive functioning, was easily administered, and was found to have no adverse side effects.

Kay, Gary G.↗

Crew State and Risk Model Development to Predict Hydration Status During Extravehicular Activity Training Events

Introduction: Hydration is critical for optimal human health and performance and dehydration can lead to impaired cardiovascular function, thermal dysregulation, decreased blood plasma volume, and cognitive impacts, particularly during physical activity. Prolonged and repeated extravehicular activities (EVA) without sufficiently available drinking water may increase risk for dehydration, which could impair crew health and impact mission success. Understanding hydration needs and potential effects on health and performance are necessary to optimize crew well-being and enable successful EVA objectives. This study aims to develop a model of hydration status during EVA using water balance techniques. Methods: Water balance measures were collected on 15 healthy astronauts who performed ≈6-hour simulated microgravity extravehicular activity (EVA) training in the NASA Neutral Buoyancy Laboratory (NBL). Data collected included pre-and post-EVA nude body weight (BW), maximum absorption garment (MAG) weight, Disposable In-suit Drink Bag (DIDB) weight, urine specific gravity (USG), and extra pre-EVA intake (W). Variables were combined to create the water balance model as pre-EVA (Hn)= BWn+ MAGn+ DIDBn+ Wnand post EVA (Hn+1) = BWn+1+ MAGn+1+ DIDBn+1. Urine specific gravity values were used to refine water balance measures into hydration categories: Hydrated, Marginally Hydrated, and Dehydrated. Results: Pre-EVA modeling indicated53% of crew were hydrated, 20% were marginally hydrated, and 27% were dehydrated. Alternately, Hn+1 showed 13% of crew remained hydrated, 47% were marginally hydrated, and 40% were dehydrated at the end of the EVA. Furthermore, 75% of the crewmembers who started sufficiently hydrated finished the run marginally hydrated or dehydrated. According to USG indices presented by Casa and Lawrence, et al. (2000), only 25% of the crew started and remained hydrated throughout the EVA, and those who were dehydrated at the outset stayed dehydrated. Conclusion: Model outcomes assessing hydration status during 6-hour simulated microgravity EVAs demonstrate the necessity to further address hydration requirements for optimal human performance during spaceflight and EVA. This study enables additional baseline development of the Crew State and Risk Model Hydration, Nutrition, and Waste Management component that aims to provide individualized crew state and risk predictions during EVAs. Reference: Casa, D. J., Armstrong, L. E., et al. (2000). National Athletic Trainers’ Association Position Statement: Fluid Replacement for Athletes. Journal of Athletic Training, 35:212-224.

L Cooper↗

Team Performance and Error Management in Chinese and American Simulated Flight Crews: The Role of Cultural and Individual Differences

This report describes results of a study conducted for NASA-Langley Research Center. This study is part of a program of research conducted for NASA-LARC that has focused on identifying the influence of national culture on the performance of flight crews. We first reviewed the literature devoted to models of teamwork and team performance, crew resource management, error management, and cross-cultural psychology. Davis (1999) reported the results of this review and presented a model that depicted how national culture could influence teamwork and performance in flight crews. The second study in this research program examined accident investigations of foreign airlines in the United States conducted by the National Transportation Safety Board (NTSB). The ability of cross-cultural values to explain national differences in flight outcomes was examined. Cultural values were found to covary in a predicted way with national differences, but the absence of necessary data in the NTSB reports and limitations in the research method that was used prevented a clear understanding of the causal impact of cultural values. Moreover, individual differences such as personality traits were not examined in this study. Davis and Kuang (2001) report results of this second study. The research summarized in the current report extends this previous research by directly assessing cultural and individual differences among students from the United States and China who were trained to fly in a flight simulator using desktop computer workstations. The research design used in this study allowed delineation of the impact of national origin, cultural values, personality traits, cognitive style, shared mental model, and task workload on teamwork, error management and flight outcomes. We briefly review the literature that documents the importance of teamwork and error management and its impact on flight crew performance. We next examine teamwork and crew resource management training designed to improve teamwork. This is followed by discussion of the potential influence of national culture on teamwork and crew resource management. We then examine the influence of other individual and team differences, such as personality traits, cognitive style, shared mental model, and task workload. We provide a heuristic model that depicts the influence of national culture and individual differences on teamwork, error management and flight outcomes. The results demonstrate the usefulness of the model for future research.

Davis, Donald D.↗

Human factors issues for interstellar spacecraft

Developments in research on space human factors are reviewed in the context of a self-sustaining interstellar spacecraft based on the notion of traveling space settlements. Assumptions about interstellar travel are set forth addressing costs, mission durations, and the need for multigenerational space colonies. The model of human motivation by Maslow (1970) is examined and directly related to the design of space habitat architecture. Human-factors technology issues encompass the human-machine interface, crew selection and training, and the development of spaceship infrastructure during transtellar flight. A scenario for feasible instellar travel is based on a speed of 0.5c, a timeframe of about 100 yr, and an expandable multigenerational crew of about 100 members. Crew training is identified as a critical human-factors issue requiring the development of perceptual and cognitive aids such as expert systems and virtual reality.

Cohen, Marc M.↗

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

Toward an embedded training tool for Deep Space Network operations

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Hill, Randall W., Jr.↗

Autogenic-feedback training exercise is superior to promethazine for control of motion sickness symptoms

Motion sickness symptoms affect approximately 50% of the crew during space travel and are commonly treated with intramuscular injections of promethazine. The purpose of this paper is to compare the effectiveness of three treatments for motion sickness: intramuscular injections (i.m.) of promethazine, a physiological training method (autogenic-feedback training exercise [AFTE]), and a no-treatment control. An earlier study tested the effects of promethazine on cognitive and psychomotor performance and motion sickness tolerance in a rotating chair. For the present paper, motion sickness tolerance, symptom reports, and physiological responses of these subjects were compared to matched subjects selected from an existing database who received either AFTE or no treatment. Three groups of 11 men, between the ages of 33 and 40 years, were matched on the number of rotations tolerated during their initial rotating-chair motion sickness test. The motion sickness test procedures and the 7-day interval between tests were the same for all subjects. The drug group was tested under four treatment conditions: baseline (no injections), a 25 mg dose of promethazine, a 50 mg dose of promethazine, and a placebo of sterile saline. AFTE subjects were given four 30-minute AFTE sessions before their second, third, and fourth motion sickness tests (6 hours total). The no-treatment control subjects were only given the four rotating-chair tests. Motion sickness tolerance was significantly increased after 4 hours of AFTE when compared to either 25 mg (p < 0.00003) or 50 mg (p < 0.00001) of promethazine. The control and promethazine groups did not differ. AFTE subjects reported fewer or no symptoms at higher rotational velocities than subjects in the control or promethazine groups. The primary physiological effect of promethazine was an inhibition of skin conductance level. The AFTE group showed significantly less heart rate and skin conductance variability during motion sickness tests administered after training.

Clinical Trial↗

A Preliminary Data Model for Orbital Flight Dynamics in Shuttle Mission Control

The Orbital Flight Dynamics group in Shuttle Mission Control is investigating new user interfaces in a project called RIOTS [RIOTS 2000]. Traditionally, the individual functions of hardware and software guide the design of displays, which results in an aggregated, if not integrated interface. The human work system has then been designed and trained to navigate, operate and integrate the processors and displays. The aim of RIOTS is to reduce the cognitive demands of the flight controllers by redesigning the user interface to support the work of the flight controller. This document supports the RIOTS project by defining a preliminary data model for Orbital Flight Dynamics. Section 2 defines an information-centric perspective. An information-centric approach aims to reduce the cognitive workload of the flight controllers by reducing the need for manual integration of information across processors and displays. Section 3 describes the Orbital Flight Dynamics domain. Section 4 defines the preliminary data model for Orbital Flight Dynamics. Section 5 examines the implications of mapping the data model to Orbital Flight Dynamics current information systems. Two recurring patterns are identified in the Orbital Flight Dynamics work the iteration/rework cycle and the decision-making/information integration/mirroring role relationship. Section 6 identifies new requirements on Orbital Flight Dynamics work and makes recommendations based on changing the information environment, changing the implementation of the data model, and changing the two recurring patterns.

ONeill, John↗

Enabling computer decisions based on EEG input

Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

Validation Studies↗

Cognitive Grid Optimization

This project laid the foundation to include a security constrained economic dispatch (SCED) within one of the leading simulators which is used to train system operators who keep the lights on for over 150 million people in USA. The SCED is designed to handle very high penetrations of renewable generation as well as battery storage. As a follow on the this project, a Trusted Source Model of the North American Electric Interconnections will be built from public GIS data. The various North American Markets will be emulated. This Trusted Source Model will grow the software developers for the next generation of power applications that are needed to transition to all green generation while everything is electrified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Research opportunities in human behavior and performance

Extant information on the subject of psychological aspects of manned space flight are reviewed; NASA's psychology research program is examined; significant gaps in knowledge are identified; and suggestions are offered for future research program planning. Issues of human behavior and performance related to the United States space station, to the space shuttle program, and to both near and long term problems of a generic nature in applicable disciplines of psychology are considered. Topics covered include: (1) human performance requirements for a 90 day mission; (2) human perceptual, cognitive, and motor capabilities and limitations in space; (3) crew composition, individual competencies, crew competencies, selection criteria, and special training; (4) environmental factors influencing behavior; (5) psychosocial aspects of multiperson space crews in long term missions; (6) career determinants in NASA; (7) investigational methodology and equipment; and (8) psychological support.

Christensen, J. M.↗

Alerting prefixes for speech warning messages

A major question posed by the design of an integrated voice information display/warning system for next-generation helicopter cockpits is whether an alerting prefix should precede voice warning messages; if so, the characteristics desirable in such a cue must also be addressed. Attention is presently given to the results of a study which ascertained pilot response time and response accuracy to messages preceded by either neutral cues or the cognitively appropriate semantic cues. Both verbal cues and messages were spoken in direct, phoneme-synthesized speech, and a training manipulation was included to determine the extent to which previous exposure to speech thus produced facilitates these messages' comprehension. Results are discussed in terms of the importance of human factors research in cockpit display design.

Bucher, N. M.↗

Development of interactive multimedia applications

Multimedia is making an increasingly significant contribution to our informational society. The usefulness of this technology is already evident in education, business presentations, informational kiosks (e.g., in museums), training and the entertainment environment. Institutions, from grade schools to medical schools, are exploring the use of multifaceted electronic text books and teaching aids to enhance course materials. Through multimedia, teachers and students can take full advantage of the cognitive value of animation, audio, video and other types in a seamless application. The Software Technology Branch at NASA Johnson Space Center (NASA/JSC) is taking similar approaches to apply the state-of-the-art technology to space training, mission operations and other applications. This paper discusses the characteristics and development of multimedia applications at the NASA/JSC.

Leigh, Albert↗

Exercise-training protocols for astronauts in microgravity

Based on physical working requirements for astronauts during intra- and extravehicular activity and on the findings from bed-rest studies that utilized exercise training as a countermeasure for the reduction of aerobic power, deterioration of muscular strength and endurance, decrements in mood and cognitive performance, and possibly for bone loss, two exercise protocols are proposed. One assumes that, during microgravity, astronaut exercise physiological functions should be maintained at 100 percent of ground-based levels. The other assumes that maximal aerobic power in flight can be reduced by 10 percent of the ground-based level.

Greenleaf, J. E.↗

Scenario-Based Task Design for Airline Pilot Anticipatory Behaviors: Asynchronous Assessment of Complex Cognitive Skills

Airline pilots must anticipate potential threats to passenger safety and efficient flight. Such anticipation needs to occur at both the system and individual levels, yet no formal training for these anticipatory behaviors currently exists. The emerging field of resilience engineering provides a framework to explore this problem. Given the complex nature of this problem, the assessment portion of the project constituted a challenge. Simulator time is expensive as simulators are costly to run, and they are extremely limited in number. Also, by the nature of their work, pilots as a group are hard to connect with in person; thus, asynchronous methods were adopted. Further, to ensure that authentic pilot behaviors were observed, task-based scenarios were used rather than focus group or interview protocols. This session explores the design of asynchronous learning and a measure for assessing pilot anticipatory behaviors outside of a simulator to help design learning opportunities for pilots. The scenario-based and active assessment items will be discussed in detail, and demonstrations of these items will be shared. These items constitute the bulk of the challenge for this work. At the time of this writing, data is being collected to assess the effectiveness of the interactive training module and validate the measures. This data will be analyzed and presented as part of the session. This will include any linkages between the scenario-based and traditional assessment items.

task design↗