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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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135 records · Page 8
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NASA NTRS2017

Risk of Cardiac Rhythm Problems During Spaceflight

NASA has concerns regarding the incidence and clinical significance of cardiac arrhythmias that could occur during long-term exposure to the spaceflight environment, such as on the International Space Station (ISS) or during a prolonged (e.g., up to 3 years) sojourn to Mars or on the Moon. There have been some anecdotal reports and a few documented cases of cardiac arrhythmias in space, including one documented episode of non-sustained ventricular tachycardia. The potential catastrophic nature of a sudden cardiac death in the remote space environment has led to concerns from the early days of the space program that spaceflight might be arrhythmogenic. Indeed, there are known and well-defined changes in the cardiovascular system with spaceflight: a) plasma volume is reduced, b) left ventricular mass is decreased, and c) the autonomic nervous system adapts to the weightless environment. Combined, these physiologic adaptations suggest that changes in cardiac structure and neuro-humoral environment during spaceflight could alter electrical conduction, although the evidence supporting this contention consists mostly of minor changes in QT interval (the time between the start of the Q wave and the end of the T wave on an electrocardiogram tracing) in a small number of astronauts after long-duration spaceflight. Concurrent with efforts by NASA Medical Operations to refine and improve screening techniques relevant to arrhythmias and cardiovascular disease, as NASA enters the era of exploration-class missions it will be critical to determine with the highest degree of certainty whether spaceflight by itself alters cardiac structure and function sufficiently to increase the risk of arrhythmias.

Lee, Stuart M. C.↗
NASA NTRS2018

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗
NASA NTRSDate not supplied

Collaborative Communications Between a Human and a Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACC to which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced Air Mobility,↗
NASA NTRS2021

Collaborative Communications Between A Human and A Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced air mobility↗
NASA NTRS2021

Chapter 5: Extravehicular Activity Metabolic Rate Model: Metabolic Rate Estimated from Heart Rate

In-flight monitoring of crew metabolic rates during extravehicular activity (EVA) provides crucial information in mitigating injury. The purpose of this study was to investigate the relationship of crewmember heart rate (HR) and metabolic rate (MR) during EVA operations to develop a predictive linear model. HR and MR data was collected from 132 EVAs from Shuttle and International Space Station (ISS) missions. MR was collected every 2-min from portable life support system delta oxygen decay, while HR was collected every 20-sec via electrocardiogram. HR was down sampled to every 2-min to match MR during EVA for evaluation. Further, a new metric was observed from direct relations between metabolic rate with HR over EVA time (MR/HR) measured as a BTU/beat. A range of BTU/beat was collected as a conversion scale between MR and HR at different EVA workloads categorized by increased MR. Both HR and MR values were observed to decrease through the duration of EVA. Similarly, HR and MR slopes decreased at start of EVA compared to end of EVA. MR/HR values were used to predict MR from HR over the entire duration of EVA with root mean square error less than 200 BTU/Hr. Additionally, MR was predicted based on HR values during EVA via a calculated simple linear regression. A regression equation was found for each EVA drawing relations between HR and MR (F (2923.84) and P<0.0001) with an R(sup 2) value of 0.402. Individual crew regressions improved prediction and R(sup 2) to greater than 0.82. Two models are presented to determine metabolic rate from heart rate during EVA. Results draw correlations for heart rate and metabolic rate fluctuations during EVA for individualized crew predictions during future operations. The linear models correlate to Apollo prediction data during historic EVAs.

Metabolic rate predictions↗
NASA NTRSDate not supplied

Preparation for an Earth Independent Medical Operations Demonstration using the Tempus ALS™ Medical Device

NASA’s exploration-class missions have severe resource constraints, long return trip durations, significant communication delays and limited resupply opportunities. Validation on the International Space Station (ISS) of medical devices that fit within Earth-Independent Medical Operations (EIMO) systems is a necessary preparation step. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. The Human Research Program’s (HRP) Exploration Medical Capability (ExMC) Element and the Exploration Medical Integrated Product Team (XM-IPT) are planning an ISS technology demonstration to determine the feasibility of including a multifunctional medical device into an EIMO medical system. Demonstration Preparations: The Tempus ALS (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) is a commercial-off-the-shelf medical device, with United States Food and Drug Administration clearance and is Conformité Européene marked in Europe. Several thousand units have been sold and are successfully operating in pre-hospital and in remote settings, such as by European Space Agency (ESA) flight surgeons and some of NASA’s commercial partners during post-flight medical operations. The Tempus ALS provides vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature. The device has ultrasound imaging and video laryngoscopy capabilities and has automatic or manual defibrillation modes for treating cardiac arrhythmias. It includes procedural guidance capabilities to assist in the collection of the vital sign measurements and it has various data transmission and report generation features. NASA’s HRP ExMC and XM-IPT are partnering with the ESA to demonstrate the Tempus ALS on ISS, with ESA manifesting the Tempus ALS and its accessories. ESA will compare performance of periodic health status exams and medical contingency drills performed nominally and with the Tempus ALS. NASA’s EIMO demonstration will include the use of Tempus ALS to diagnose a complaint of abdominal pain under increasingly independent circumstances. The caregiver must assess the present illness, collect vital sign measurements, and perform an abdominal ultrasound, under one of three communication situations, including real-time, with a several second delay and with a delay on the order of minutes. Expected Outcomes: Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis instead of separate devices with singular functionalities. Information will also be collected about performance differences as communication delays increase and available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities which takes the EIMO construct into consideration.

Beth Lewandowski↗
NASA NTRSDate not supplied

A Multi-Faceted Approach to Demonstrating Multi-Functional Integrated Medical Devices to Advance Earth-Independent Medical Operations

INTRODUCTION TO MIM DEVICES Multi-functional Integrated Medical (MIM) devices conveniently incorporate multiple medical system capabilities within one device. The NASA Exploration Medical Integrated Product Team (XM-IPT) sponsored a market survey and trade study which identified the Tempus ProTM and the LifeBot 10® as the MIM devices that best met the evaluation criteria of the trade study. The Tempus ProTM (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) and LifeBot 10® (LifeBot Health, Chicago, IL) both provide vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature along with ultrasound imaging. A video laryngoscopy capability is unique to the Tempus ProTM, while the LifeBot 10® supports connectivity with a digital stethoscope, otoscope, eye exam camera, and dermatoscope. Both devices include procedural guidance capabilities and have various data transmission and report generation features. TECHNOLOGY DEMONSTRATIONS NASA’s exploration-class missions will have severe resource constraints, long return trip durations, significant communication delays, and limited resupply opportunities. The medical systems of these missions will need to fit within an Earth-Independent Medical Operations (EIMO) construct. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. Evaluations are underway to determine if it will be beneficial to include MIM devices within exploration medical systems by conducting a series of planned technical demonstrations. Exploration Atmosphere Chamber studies are being performed to determine MIM functionality in a high oxygen concentration atmosphere. A side-by-side comparison of the Tempus ProTM and LifeBot 10® will be performed during ground-based demonstrations. Use of the MIM devices within an EIMO medical scenario simulation will be practiced during ground-based demonstrations in preparation for International Space Station (ISS) demonstrations of the MIM device. These various demonstrations are designed to gather evidence for or against the inclusion of MIM devices within an EIMO medical system. EXPECTED DEMONSTRATION OUTCOMES Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis. Information will also be collected about performance differences as available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities, which take the EIMO construct into consideration.

B. E. Lewandowski↗