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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

An Earthling to an Astronaut: Medical Challenges

Humans can travel safely into space in low Earth orbit (LEO) or to near-Earth objects if several medical, physiological, environmental, and human factors issues risks are mitigated. Research must be performed in order to set standards in these four areas, and current NASA standards are contained in the Space Flight Human System Standards volumes 1 and 2, and crew medical certification standards. These three sets of standards drive all of the clinical, biomedical research and environmental technology development for the NASA human space flight program. These standards also drive the identification of specific risks to crew health and safety, and we currently manage 65 human system risks within the human space flight program. Each risk has a specific program of research, technology development, and development of operational procedures to mitigate the risks. Some of the more important risks tat will be discussed in this talk include exposure to radiation, behavioral health due to confinement in a closed cabin, physiological changes such as loss of bone, muscle and exercise capability, reduction in immune system capability, environmental threats of maintaining an adequate atmosphere and water for drinking, avoidance of toxic or infectious material, protection of hearing, and human factors issues of equipment and task design. A nutritious and varied food supply must also be provided. All of these risks will be discussed and current strategies for mitigating these risks for long-duration human space flight. In mitigating these 65 human system risks, novel approaches to problem solving must be employed to find the most appropriate research and technology based applications. Some risk mitigations are developed internally to NASA while others are found through research grants, technology procurements, and more recently open innovation techniques to seek solutions from the global technical community. Examples and results will be presented from all of these approaches including the more recent use of prizes to stimulate innovation.

Davis, Jeffrey R.↗
NASA NTRS2015

Can We Trust Computational Modeling for Medical Applications?

Operations in extreme environments such as spaceflight pose human health risks that are currently not well understood and potentially unanticipated. In addition, there are limited clinical and research data to inform development and implementation of therapeutics for these unique health risks. In this light, NASA's Human Research Program (HRP) is leveraging biomedical computational models and simulations (M&S) to help inform, predict, assess and mitigate spaceflight health and performance risks, and enhance countermeasure development. To ensure that these M&S can be applied with confidence to the space environment, it is imperative to incorporate a rigorous verification, validation and credibility assessment (VV&C) processes to ensure that the computational tools are sufficiently reliable to answer questions within their intended use domain. In this presentation, we will discuss how NASA's Integrated Medical Model (IMM) and Digital Astronaut Project (DAP) have successfully adapted NASA's Standard for Models and Simulations, NASA-STD-7009 (7009) to achieve this goal. These VV&C methods are also being leveraged by organization such as the Food and Drug Administration (FDA), National Institute of Health (NIH) and the American Society of Mechanical Engineers (ASME) to establish new M&S VV&C standards and guidelines for healthcare applications. Similarly, we hope to provide some insight to the greater aerospace medicine community on how to develop and implement M&S with sufficient confidence to augment medical research and operations.

Mulugeta, Lealem↗
NASA NTRS2015

Credibility Assessment of Deterministic Computational Models and Simulations for Space Biomedical Research and Operations

Human missions beyond low earth orbit to destinations, such as to Mars and asteroids will expose astronauts to novel operational conditions that may pose health risks that are currently not well understood and perhaps unanticipated. In addition, there are limited clinical and research data to inform development and implementation of health risk countermeasures for these missions. Consequently, NASA's Digital Astronaut Project (DAP) is working to develop and implement computational models and simulations (M&S) to help predict and assess spaceflight health and performance risks, and enhance countermeasure development. In order to effectively accomplish these goals, the DAP evaluates its models and simulations via a rigorous verification, validation and credibility assessment process to ensure that the computational tools are sufficiently reliable to both inform research intended to mitigate potential risk as well as guide countermeasure development. In doing so, DAP works closely with end-users, such as space life science researchers, to establish appropriate M&S credibility thresholds. We will present and demonstrate the process the DAP uses to vet computational M&S for space biomedical analysis using real M&S examples. We will also provide recommendations on how the larger space biomedical community can employ these concepts to enhance the credibility of their M&S codes.

Mulugeta, Lealem↗
NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 1

A small, portable, relatively inexpensive computer system was developed for on-line use in clinical or laboratory situations. The system features an integrated hardware-software package that permits use of all peripherals, such as analog-to-digital converter, oscilloscope, plotter, digital bus, with an interpreter constructed around the BASIC programming language. The system is conceptually similar to the LINC system developed in 1962, but is more compact and powerful due to intervening advances in integrated circuit technology. A description of the hardware of the system was given. A reference manual, user manual, and programming guides were also presented. Finally, a stereo display system for vectorcardiograms was described.

Mark, R. G.↗
NASA NTRS1978

Biomagnetic instrumentation and measurement

The instruments and techniques of biomagnetic measurement have progressed greatly in the past 15 years and are now of a quality appropriate to clinical applications. The paper reports on recent developments in the design and application of SQUID (Superconducting Quantum Interference Device) magnetometers to biomagnetic measurement. The discussion covers biomagnetic field levels, magnetocardiography, magnetic susceptibility plethysmography, ambient noise and sensor types, principles of operation of a SQUID magnetometer, and laboratory techniques. Of the many promising applications of noninvasive biomagnetic measurement, magnetocardiography is the most advanced and the most likely to find clinical application in the near future.

Iufer, E. J.↗
NASA NTRS2020

Medics: Medical Decision Support System for Long-Duration Space Exploration

The Autonomous Medical Operations (AMO) group at NASA Ames is developing a “medical decision support system” to enable astronauts on long-duration exploration missions to operate autonomously. The system will support clinical actions by providing medical interpretation advice and procedural recommendations during emergent care and clinical work performed by crew. The current state of development of the system, called MedICS (Medical Interpretation Classification and Segmentation) includes two separate aspects: a set of machine learning diagnostic models trained to analyze organ images and patient health records, and an interface to ultrasound diagnostic hardware and to medical repositories. Three sets of images of different organs and medical records were utilized for training machine learning models for various analyses, as follows: 1. Pneumothorax condition (collapsed lung). The trained model provides a positive or negative diagnosis of the condition. 2. Carotid artery occlusion. The trained model produces a diagnosis of 5 different occlusion levels (including “normal”). 3. Ocular retinal images. The model extracts optic disc pixels (image segmentation). This is a precursor step for advanced autonomous fundus clinical evaluation algorithms to be implemented in FY20. 4. Medical health records. The model produces a differential diagnosis for any particular individual, based on symptoms and other health and demographic information. A probability is calculated for each of 25 most common conditions. The same model provides the likelihood of survival. All results are provided with a confidence level. Item 1 images were provided by the US Army and were part of a data set for the clinical treatment of injured battlefield soldiers. This condition is relevant to possible space mishaps, due to pressure management issues. Item 2 images were provided by Houston Methodist Hospital, and item 3 health records were acquired from the MIT laboratory of computational physiology. The machine learning technology utilized is deep multilayer networks (Deep Learning), and new models will continue to be produced, as relevant data is made available and specific health needs of astronaut crews are identified. The interfacing aspects of the system include a GUI for running the different models, and retrieving and storing data, as well as support for integration with an augmented reality (AR) system deployed at JSC by Tietronix Software Inc. (HoloLens). The AR system provides guidance for the placement of an ultrasound transducer that captures images to be sent to the MedICS system for diagnosis. The image captured and the associated diagnosis appear in the technician’s AR visual display.

Colombano, Silvano↗
NASA NTRS2024

Biomedical Research for Human Spaceflight

This invited presentation will offer an overview of the biomedical research – both from a biomedical sciences and engineering perspective – of human physiology and performance during spaceflight. Focused on the unique expertise within the Biomedical Sciences Branch, NASA Johnson Space Center, the talk will elucidate the critical role of biomedical laboratories in synergistic activities in clinical sciences, space physiology, applied research, technology development, and operational support for human space exploration. Together, the efforts within this branch play a crucial role in supporting astronauts' health, performance, and safety. The branch Scientists, Researchers, and Engineers conduct biomedical research in flight on board the International Space Station and on-earth space environment analogs. This dual approach allows for a nuanced understanding of the effects of micro- and planetary gravitation fields on human physiology and the assessment of potential clinical and biomedical interventions (countermeasures) to mitigate astronaut clinical and performance decrements. The talk aims to underscore the synergistic collaborative efforts of biomedical engineers, physiologists, clinicians, and computational researchers, emphasizing these experts' pivotal role in advancing human spaceflight's frontiers.

Biomedical Research↗
NASA NTRS2014

HRP's Healthcare Spin-Offs Through Computational Modeling and Simulation Practice Methodologies

Spaceflight missions expose astronauts to novel operational and environmental conditions that pose health risks that are currently not well understood, and perhaps unanticipated. Furthermore, given the limited number of humans that have flown in long duration missions and beyond low Earth-orbit, the amount of research and clinical data necessary to predict and mitigate these health and performance risks are limited. Consequently, NASA's Human Research Program (HRP) conducts research and develops advanced methods and tools to predict, assess, and mitigate potential hazards to the health of astronauts. In this light, NASA has explored the possibility of leveraging computational modeling since the 1970s as a means to elucidate the physiologic risks of spaceflight and develop countermeasures. Since that time, substantial progress has been realized in this arena through a number of HRP funded activates such as the Digital Astronaut Project (DAP) and the Integrated Medical Model (IMM). Much of this success can be attributed to HRP's endeavor to establish rigorous verification, validation, and credibility (VV&C) processes that ensure computational models and simulations (M&S) are sufficiently credible to address issues within their intended scope. This presentation summarizes HRP's activities in credibility of modeling and simulation, in particular through its outreach to the community of modeling and simulation practitioners. METHODS: The HRP requires all M&S that can have moderate to high impact on crew health or mission success must be vetted in accordance to NASA Standard for Models and Simulations, NASA-STD-7009 (7009) [5]. As this standard mostly focuses on engineering systems, the IMM and DAP have invested substantial efforts to adapt the processes established in this standard for their application to biological M&S, which is more prevalent in human health and performance (HHP) and space biomedical research and operations [6,7]. These methods have also generated substantial interest by the broader medical community though institutions like the National Institutes of Health (NIH) and the Food and Drug Administration (FDA) to develop similar standards and guidelines applicable to the larger medical operations and research community. DISCUSSION: Similar to NASA, many leading government agencies, health institutions and medical product developers around the world are recognizing the potential of computational M&S to support clinical research and decision making. In this light, substantial investments are being made in computational medicine and notable discoveries are being realized [8]. However, there is a lack of broadly applicable practice guidance for the development and implementation of M&S in clinical care and research in a manner that instills confidence among medical practitioners and biological researchers [9,10]. In this presentation, we will give an overview on how HRP is working with the NIH's Interagency Modeling and Analysis Group (IMAG), the FDA and the American Society of Mechanical Engineers (ASME) to leverage NASA's biomedical VV&C processes to establish a new regulatory standard for Verification and Validation in Computational Modeling of Medical Devices, and Guidelines for Credible Practice of Computational Modeling and Simulation in Healthcare.

Mulugeta, Lealem↗
NASA NTRS1998

New Research Methods Developed for Studying Diabetic Foot Ulceration

Dr. Brian Davis, one of the Cleveland Clinic Foundation's researchers, has been investigating the risk factors related to diabetic foot ulceration, a problem that accounts for 20 percent of all hospital admissions for diabetic patients. He had developed a sensor pad to measure the friction and pressure forces under a person's foot when walking. As part of NASA Lewis Research Center's Space Act Agreement with the Cleveland Clinic Foundation, Dr. Davis requested Lewis' assistance in visualizing the data from the sensor pad. As a result, Lewis' Interactive Data Display System (IDDS) was installed at the Cleveland Clinic. This computer graphics program is normally used to visualize the flow of air through aircraft turbine engines, producing color two- and three-dimensional images.

Source record↗
NASA NTRS2014

Analysis of Advanced Respiratory Support Onboard ISS and CCV

NASA is collaborating with private entities for the development of commercial space vehicles. The Space and Clinical Operations Division was tasked to review the oxygen and respiratory support system and recommend what capabilities, if any, the vehicle should have to support the return of an ill or injured crewmember. The Integrated Medical Model (IMM) was utilized as a data source for the development of these recommendations. The Integrated Medical Model (IMM) was used to simulate a six month, six crew, International Space Station (ISS) mission. Three medical system scenarios were considered based on the availability of (1) oxygen only, (2) oxygen and a ventilator, or (3) neither oxygen nor ventilator. The IMM analysis provided probability estimates of medical events that would require either oxygen or ventilator support. It also provided estimates of crew health, the probability of evacuation, and the probability of loss of crew life secondary to medical events for each of the three medical system scenarios. These IMM outputs were used as objective data to enable evidence‐based decisions regarding oxygen and respiratory support system requirements for commercial crew vehicles. The IMM provides data that may be utilized to support informed decisions regarding the development of medical systems for commercial crew vehicles.

Shah, Ronak V.↗
NASA NTRS1989

Interactive displays in medical art

Medical illustration is a field of visual communication with a long history. Traditional medical illustrations are static, 2-D, printed images; highly realistic depictions of the gross morphology of anatomical structures. Today medicine requires the visualization of structures and processes that have never before been seen. Complex 3-D spatial relationships require interpretation from 2-D diagnostic imagery. Pictures that move in real time have become clinical and research tools for physicians. Medical illustrators are involved with the development of interactive visual displays for three different, but not discrete, functions: as educational materials, as clinical and research tools, and as data bases of standard imagery used to produce visuals. The production of interactive displays in the medical arts is examined.

Mcconathy, Deirdre Alla↗
NASA NTRS1990

A CLIPS expert system for clinical flow cytometry data analysis

An expert system is being developed using CLIPS to assist clinicians in the analysis of multivariate flow cytometry data from cancer patients. Cluster analysis is used to find subpopulations representing various cell types in multiple datasets each consisting of four to five measurements on each of 5000 cells. CLIPS facts are derived from results of the clustering. CLIPS rules are based on the expertise of Drs. Stewart, Duque, and Braylan. The rules incorporate certainty factors based on case histories.

Salzman, G. C.↗
NASA NTRS2006

Midodrine Exacerbates Promethazine-induced Akathisia

The study of physiological changes during spaceflight, and the pursuit of remedies to counteract those changes, often requires unique research protocols that lead to unexpected findings; some with important clinical implications. In our research into the development of treatments to counteract the detrimental cardiovascular effects of spaceflight, we have discovered an important drug interaction between promethazine and midodrine.

Platts, Steven H.↗
NASA NTRS2004

Creating a Scenario Suitable for Multiple Caregivers

The HPS can be utilized for the training of a wide variety of caregivers, ranging from physicians to laypeople. Methods: A single scenario was developed and adapted for a number of clinical scenarios and operational environments, ranging from in-flight to the immediate postflight timeline. In this way, different caregivers, from astronauts to search and rescue forces to specialty-boarded physicians, could make use of a single clinical situation. Five crew medical officer analogs and sixty anesthesia residents, serving as flight surgeon analogs, and, were briefed on space medicine and physiology, then were exposed to the scenario and asked to manage the patient as if they were part of the in-flight or recovery team. Results: Basic themes, such as crisis resource management, were standard across the student audiences. Discussion: A single clinical script can easily be adapted for multiple uses.

Doerr, Harold↗
NASA NTRSDate not supplied

Evaluation of the Spaceflight Cardiovascular Disease Risk using the Clinical Prediction Model Astro-Charm and the NASA Radiation Risk Model

Exposure to space radiation and other spaceflight hazards may pose an increased risk for cardiovascular diseases (CVD) during and after spaceflight [1], that should be quantified to plan future long-duration space missions such as the flight to Mars. The first CVD clinical prediction models (CPMs) for individuals were developed by the Framingham Heart Study investigators in the 1960’s. Since then, many CPMs have been developed and refined. The CPMs consider cardiovascular risk factors such as blood pressure, diabetes, cholesterol, and smoking. As there is a relationship between radiation-induced CVD risk and the background (non-exposed) CVD risk, it is possible to use CPMs to calculate a personalized risk for astronauts.

I. Plante↗
NASA NTRSDate not supplied

Integration of the Cardiovascular Clinical Risk Prediction Model Astro-CHARM Into the NASA Radiation Risk Model

Space radiation poses an increased risk for cardiovascular diseases (CVD) during and after spaceflight, that should be quantified to plan future space missions such as the flight to Mars. The radiation-induced CVD risk is evaluated using a linear no-threshold dose response excess relative risk (ERR) model, so that the risk is function of the radiation dose and of the background (i.e., non-exposed) incidence rate. The background CVD risk can be evaluated using clinical prediction models (CPMs). The first CPMs developed in the 1960’s have identified CVD risk factors such as blood pressure, diabetes, cholesterol, and smoking. In this work, the steps used to integrate the CVD risk provided by a CPM into the NASA Radiation Risk Model are described. Simulation results calculated using available data for relevant mission scenarios are also shown, and the challenges in CVD risk predictions are discussed.

I Plante↗
NASA NTRS2024

Integration of the Cardiovascular Risk Model Astro-CHARM in the NASA Radiation Risk Model

Space radiation poses an increased risk for cardiovascular diseases (CVD) during and after spaceflight, that should be quantified to plan future space missions such as the flight to Mars. The radiation-induced CVD risk is evaluated using a linear no-threshold dose response excess relative risk (ERR) model, so that the risk is function of the radiation dose and of the background (i.e., non-exposed) incidence rate. The background CVD risk can be evaluated using clinical prediction models (CPMs). The first CPMs developed in the 1960’s have identified CVD risk factors such as blood pressure, diabetes, cholesterol, and smoking. In this work, the steps used to integrate the CVD risk provided by a CPM into the NASA Radiation Risk Model are described. Simulation results calculated using available data for relevant mission scenarios are also shown, and the challenges in CVD risk predictions are discussed.

Space radiation↗
NASA NTRS2007

Scheduling Accessory Assists Patients with Cognitive Disorders

Recom Technologies Inc. received initial funding from NASA to research the commercial potential of an artificially intelligent planning reaction model to serve as a tool to help individuals suffering from various forms and levels of brain impairment. In 1993, the chief of the Artificial Intelligence Research Branch at Ames Research Center suggested collaborative research with Santa Clara Valley Medical Center. This partnership led to further development of the technology and funding to support clinical research from the U.S. Department of Education's National Institute on Disability and Rehabilitation Research. In 1996, Attention Control Systems Inc. was founded to market the finished device, called the Planning and Execution Assistant and Trainer (PEAT). PEAT is a pocket-sized PDA-like device with a graphical display, touchscreen controls, an electronic calendar, an address book, and a built-in phone, that cues users to start or stop scheduled activities, monitors their progress, and adjusts schedules as necessary in response to delays or calendar changes. It uses an automatic planning model developed for NASA to adjust daily plans when a situation changes. PEAT is sold as a complete system that includes software, hardware, documentation, and technical support. In addition to the flagship Pocket PEAT device, there is PEAT Phone, PC PEAT, and PEAT Link. Clinical studies of PEAT continue at Santa Clara Valley Medical Center

Source record↗