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Clinical Decision Support Project

As NASA plans for exploration missions into deep space, significant challenges are realized due to the distance from Earth. Beside the effects of microgravity and radiation exposure, the astronauts face the additional constraints of isolation, lack of resupply, increasingly difficult evacuation, and delayed and disrupted communication with ground-based medical care providers. These constraints require a paradigm shift from current medical care where crews rely on the real-time communications with ground-based medical care providers toward Earth-independent medical operations for astronaut medical care. Medical expertise and decision-making are ground-based for current International Space Station and planned Lunar missions. However, a deep space exploration crew will need to autonomously perform the detection, diagnosis, treatment, and prevention of medical conditions. One approach to provide Earth-independent medical operations is to augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained crew—operating under stressful conditions, combatting fatigue, and facing a potential medical crisis—with a robust clinical decision support system (CDSS). The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/data bases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that maintain a flexible platform for integrating new technology in the future. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addressed ap Medical-701 within the Inflight Medical Conditions risk: “We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology advances in this decade and beyond. Hence, data, software, and computational resources will play an essential and synergistic role in maintaining crew health, wellness, and performance in deep space missions. The focus of the CDS project was to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance, and medical care during exploration missions. In fiscal year 2022 (FY22), the CDS project was chartered to baseline and/or revise all CDS project related documentation and update the CDS project model to include the revised CDSS Concept of Operations, revised systems-based modeling language (SysML) activity diagrams, and baseline requirements. The focus of this presentation will be an overview of the CDS products and CDS model content.

Decision Support↗

Cognitive signal processing

Unsupervised signal pattern recognition - computer simulation of noisy signal pattern format, and construction of asymptotic Bayes decision boundary form

BAYESIAN STATISTICS↗

HERRO Mission to Mars Using Telerobotic Surface Exploration from Orbit

This paper presents a concept for a human mission to Mars orbit that features direct robotic exploration of the planet s surface via teleoperation from orbit. This mission is a good example of Human Exploration using Real-time Robotic Operations (HERRO), an exploration strategy that refrains from sending humans to the surfaces of planets with large gravity wells. HERRO avoids the need for complex and expensive man-rated lander/ascent vehicles and surface systems. Additionally, the humans are close enough to the surface to effectively eliminate the two-way communication latency that constrains typical robotic space missions, thus allowing real-time command and control of surface operations and experiments by the crew. Through use of state-of-the-art telecommunications and robotics, HERRO provides the cognitive and decision-making advantages of having humans at the site of study for only a fraction of the cost of conventional human surface missions. It is very similar to how oceanographers and oil companies use telerobotic submersibles to work in inaccessible areas of the ocean, and represents a more expedient, near-term step prior to landing humans on Mars and other large planetary bodies. Results suggest that a single HERRO mission with six crew members could achieve the same exploratory and scientific return as three conventional crewed missions to the Mars surface.

Oleson, Steven R.↗

Pictorial communication: Pictures and the synthetic universe

Principles for the design of dynamic spatial instruments for communicating quantitative information to viewers are considered through a brief review of the history of pictorial communication. Pictorial communication is seen to have two directions: (1) from the picture to the viewer; and (2) from the viewer to the picture. Optimization of the design of interactive instruments using pictorial formats requires an understanding of the manipulative, perceptual, and cognitive limitations of human viewers.

Ellis, Stephen R.↗

Expressing Functionality Using Design Patterns, A Real-World Example

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting tacit knowledge from existing systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. This study enables such a technique by demonstrating the use of architectural theory in expressing tacit knowledge from existing systems and presenting that knowledge according to the model-based view offered by the Functional Architecture of Systems methodology. By validating the functional information expressed by the design pattern, this work solidifies design patterns as a critical component of a technical architecture and proposes a functional architecture viewpoint for describing mined knowledge in a usable, model-based, way suitable for archival in a modern knowledge management system.

Systems Engineering↗

The Emphasis of Design Patterns in Expressing Expert Knowledge From A Technical Solution – A Framework for Continued Research

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting expert knowledge from proven systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. Motivated by performance gains observed during a multi-year, sequential development activity, this survey reviews knowledge, architecture, and pattern literature to establish a framework for research of architectural methods for expert knowledge identification and description using Model Based System Engineering. The multi-year sequential development activity is offered as the experimental system of interest for this research. This work aims to enable a digital engineering strategy that improves concept phase decision making, accelerates knowledge acquisition from lessons learned repositories, and eases the burden of generational knowledge loss.

Lithium Ion↗

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop testing plays a crucial role in NASA's mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts' situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA's testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop testing for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive training experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

Simulation Modeling Virtual Reality Immersive Tech↗

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for immersing users in realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop simulations play a crucial role in NASA’s mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments, data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures, and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts’ situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA’s testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop simulations for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive simulation experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

HITL↗

Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations.

Bell, Suzanne T.↗

How Autonomous Intelligent Systems Can Facilitate Earth-independent Medical Care: Going Beyond Telepresence

During the last decade, teleoperated robotic systems have extended humans’ sensorimotor competence to digitally fly beyond the physical barrier of distance and scale and thus transmit sensorimotor skills of the human through direct communication. Telepresence capabilities have enabled tele-physical remote access at small scales thanks to telerobotic mediums. Although the concept was initially motivated by space applications, such technologies quickly have expanded into the medical domain and resulted in teleoperated medical robots, including telerobotic surgical systems (such as the da Vinci surgical system). Effective telepresence fundamentally depends on an agile, reliable, and secure communication medium that can transmit real-time information between the operator and a remote device. However, direct telepresence may not be achievable for long-duration exploration spaceflight missions. Thus, autonomous systems and local intelligence represent potential solutions to the aforementioned issues. One example solution employs demonstration systems which enable learning from the pre-captured inputs of a skilled human operator. These will be computationally modeled and later probabilistically replicated toward the completion of remote physical tasks when direct telepresence is not viable - such as under communication blackout conditions. In other words, trained autonomous systems (e.g., robots) can perform remote operations that mimic the physical performance of experts during remote operations/training. Beyond learning the physics of the task, autonomous agents can also be used to conduct algorithmic decision-making that mimics the higher-level cognition of the expert. Thus, using an autonomous system, pre-trained cognitive and manipulation-based skills can be leveraged (acquired during pre-mission events) to produce digital twins of an intelligent operator. Such systems can be used for the real-time conduction of intricate tasks in complex and unstructured environments. Such systems will operationalize “cognitive digital twins” and can expand the reach of human cognition and manipulation through the power of data-driven learning from demonstration algorithms. This system category will be discussed as a fully autonomous operation in this talk. In addition to the above, we will also propose and discuss the possibility of partial-automation using remote intelligence and remote sensing. In contrast to full automation, partial automation can close the loop through a local operator equipped with augmented sensory awareness through wearable systems. Such technologies will allow the local operator to conduct delicate tasks while being guided using sensory augmentation and being monitored to gauge her/his level of cognitive focus and performance. The difference with the previous category is that a remote human will conduct the task. Further, rather than making a digital twin of human cognition, we will augment the control inputs of the local human to match those of the skilled expert operator who is not accessible in real-time. Going beyond classic telepresence and thus approaching intelligent telepresence, our vision is that autonomous agents will eventually enable the safe, consistent and efficient delivery of complex, remote and smart medical care during space exploration across operators in an Earth-independent fashion. We will discuss our collective vision from NASA and MERIIT@NYU lab in this talk.

Telepresence↗

Teams in Space: Knowledge Gained, but More to Explore

NASA’s Human Research Program oversees the Team Risk (i.e., Risk of Performance and Behavioral Health Decrements due to Inadequate Cooperation, Coordination, Communication and Psychosocial Adaptation within a Team). Research in this area informs all aspects of an astronaut’s career, from hiring to training to mission support, and works to address new challenges related to lunar and Mars missions. NASA’s astronaut selection process creates an astronaut corps of highly qualified, team-oriented individuals, which allows mission planners much flexibility in composing small crews for specific missions. These crews are further developed and supported through extensive training, including team skills training, and countermeasures available to the crew throughout the mission. However, in the high consequence environment of long-duration missions, team composition is complex and is not a one-time concern to be addressed pre-mission. Team factors such as team cohesion, dyadic relationships, and shared team cognition are likely to change dynamically in response to each interaction and event experienced by the individuals and the team as a whole. Thus, monitoring and optimizing team composition at a more micro level (e.g., per task) is one way to support team functioning and performance. Spaceflight teams research also includes the multi-team system of Mission Control and coordination between space-to-ground, adding another avenue in which risk might be introduced, particularly under exploration missions that experience significant communication delays. Spaceflight teams research has recently experienced a concentrated flurry of analog research over the past decade, shedding light on the many unique challenges and potential solutions to mitigate the team risk in long-duration exploration missions. However, questions still remain about how to, for example, create unobtrusive operational measures and how to advance interdisciplinary teams research and countermeasure development. We present an overview of the challenges facing teams in space, our current knowledge, and the next steps for research and spaceflight operations.

Lauren Blackwell Landon↗

Learning about primates' learning, language, and cognition

Results are presented of many years of research on the methods of teaching primates the language and cognitive skills which were long considered to be unteachable to particular species of primates. It was found that chimpanzee subjects could not only learn a number of 'stock sentences' but to use them in variations and several combinations for the purpose of solving various problems. Apes placed in different rooms could be taught to communicate via computer, and collaborate with each other on doing specific tasks. Contrary to expectations, young rhesus monkeys proved to be able to learn as much as the chimpanzee species.

Rumbaugh, Duane M.↗

Self-Healing RF/Microwave Communications Circuits/Systems for NASA Missions - A Review

The success of current and future NASA missions relies in great part on the performance reliability and robustness of the communication circuits and systems of said missions. Some of the manifestations of reliability and robustness are comprised by properties such as graceful degradation, which provide redundancy and potentially longer life to the mission, and the ability to perform efficiently in harsh environments destinations such as Venus and the Jovian and Saturnian moons Europa and Enceladus, respectively. While several approaches have been considered or are currently underway to develop communications circuitry capable of performing in harsh environments, they lack the flexibility to enable reconfigurability to preserve functionality under adverse or contingency scenarios. This paper discusses some examples of self-healing RF/Microwave communications circuits and systems that could provide advantageous options in support of NASA missions.

Self-healing↗

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.↗

Capturing Safety Requirements to Enable Effective Task Allocation Between Humans and Automaton in Increasingly Autonomous Systems

There is a current drive towards enabling the deployment of increasingly autonomous systems in the National Airspace System (NAS). However, shifting the traditional roles and responsibilities between humans and automation for safety critical tasks must be managed carefully, otherwise the current emergent safety properties of the NAS may be disrupted. In this paper, a verification activity to assess the emergent safety properties of a clearly defined, safety critical, operational scenario that possesses tasks that can be fluidly allocated between human and automated agents is conducted. Task allocation role sets were proposed for a human-automation team performing a contingency maneuver in a reduced crew context. A safety critical contingency procedure (engine out on takeoff) was modeled in the Soar cognitive architecture, then translated into the Hybrid Input Output formalism. Verification activities were then performed to determine whether or not the safety properties held over the increasingly autonomous system. The verification activities lead to the development of several key insights regarding the implicit assumptions on agent capability. It subsequently illustrated the usefulness of task annotations associated with specialized requirements (e.g., communication, timing etc.), and demonstrated the feasibility of this approach.

Neogi, Natasha A.↗

Considerations for the Next Revision of NASA's Space Telecommunications Radio System Architecture

Development of NASA's Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for National Aeronautics and Space Administration (NASA) space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module - which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions.

transmitters receivers↗

Considerations for the Next Revision of STRS

Development of NASAs Software Defined Radio architecture, the Space Telecommunication Radio System (STRS), was initiated in 2004 with a goal of reducing the cost, risk and schedule when implementing Software Defined Radios (SDR) for NASA space missions. Since STRS was first flown in 2012 on three Software Defined Radios on the Space Communication and Navigation (SCaN) Testbed, only minor changes have been made to the architecture. Multiple entities have since implemented the architecture and have provided significant feedback for consideration for the next revision of the standard. The focus for the first set of updates to the architecture is items that enhance application portability. Items that require modifications to existing applications before migrating to the updated architecture will only be considered if there is compelling reasons to make the change. The significant suggestions that were further evaluated for consideration include expanding and clarifying the timing Application Programming Interfaces (APIs), improving handle name and identification (ID) definitions and use, and multiple items related to implementation of STRS Devices. In addition to ideas suggested while implementing STRS, SDR technology has evolved significantly and this impact to the architecture needs to be considered. These include incorporating cognitive concepts - learning from past decisions and making new decisions that the radio can act upon. SDRs are also being developed that do not contain a General Purpose Module which is currently required for the platform to be STRS compliant. The purpose of this paper is to discuss the comments received, provide a summary of the evaluation considerations, and examine planned dispositions

waveforms↗

Human Performance in Space

Human factors is a critical discipline for human spaceflight. Nearly every human factors research area is relevant to space exploration -- from the ergonomics of hand tools used by astronauts, to the displays and controls of a spacecraft cockpit or mission control workstation, to levels of automation designed into rovers on Mars, to organizational issues of communication between crew and ground. This chapter focuses more on the ways in which the space environment (especially altered gravity and the isolated and confined nature of long-duration spaceflight) affects crew performance, and thus has specific novel implications for human factors research and practice. We focus on four aspects of human performance: neurovestibular integration, motor control and musculo-skeletal effects, cognitive effects, and behavioral health. We also provide a sampler of recent human factors studies from NASA.

Jones, Patricia M.↗