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At least 1,171 records · Page 65

Low-Cost Miniaturized Laser Heterodyne Radiometer for Highly Sensitive Detection of CO2 and CH4 in the Atmospheric Column

We present a new passive ground-network instrument capable of measuring carbon dioxide (CO2) at 1.57 microns and methane (CH4) at 1.62 microns -- key for validation of OCO-2, ASCENDS, OCO-3, and GOSAT. Designed to piggy-back on an AERONET sun tracker (AERONET is a global network of more than 450 aerosol sensing instruments), this instrument could be rapidly deployed into the established AERONET network of ground sensors. Because aerosols induce a radiative effect that influences terrestrial carbon exchange, this simultaneous measure of aerosols and carbon cycle gases offers a uniquely comprehensive approach. This instrument is a variation of a laser heterodyne radiometer (LHR) that leverages recent advances in telecommunications lasers to miniaturize the instrument (the current version fits in a carry-on suitcase). In this technique, sunlight that has undergone absorption by the trace gas is mixed with laser light at a frequency matched to a trace gas absorption feature in the infrared (IR). Mixing results in a beat signal in the RF (radio frequency) region that can be related to the atmospheric concentration. By dividing this RF signal into a filter bank, concentrations at different altitudes can be resolved. For a one second integration, we estimate column sensitivities of 0.1 ppmv for CO2, and <1 ppbv for CH4.

Wilson, Emily L.↗

Psychophysiological Monitoring of Aerospace Crew State

As next-generation space exploration missions necessitate increasingly autonomous systems, there is a critical need to better detect and anticipate crewmember interactions with these systems. The success of present and future autonomous technology in exploration spaceflight is ultimately dependent upon safe and efficient interaction with the human operator. Optimal interaction is particularly important for surface missions during highly coordinated extravehicular activity (EVA), which consists of high physical and cognitive demands with limited ground support. Crew functional state may be affected by a number of variables including workload, stress, and motivation. Real-time assessments of crew state that do not require a crewmember’s time and attention to complete will be especially important to assess operational performance and behavioral health during flight. In response to the need for objective, passive assessment of crew state, the aim of this work is to develop an accurate and precise prediction model of human functional state for surface EVA using multi-modal psychophysiological sensing. The psychophysiological monitoring approach relies on extracting a set of features from physiological signals and using these features to classify an operator’s cognitive state. This work aims to compile a non-invasive sensor suite to collect physiological data in real-time. Training data during cognitive and more complex functional tasks will be used to develop a classifier to discriminate high and low cognitive workload crew states. The classifier will then be tested in an operationally relevant EVA simulation to predict cognitive workload over time. Once a crew state is determined, further research into specific countermeasures, such as decision support systems, would be necessary to optimize the automation and improve crew state and operational performance.

Wusk, Grace C.↗

Assimilation of SMAP and ASCAT Soil Moisture Retrievals into the JULES Land Surface Model Using the Local Ensemble Transform Kalman Filter

A land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) land surface model (LSM) using the Local Ensemble Transform Kalman Filter (LETKF). The system assimilates microwave soil moisture retrievals from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT) after bias correction based on cumulative distribution function fitting. The soil moisture assimilation estimates are evaluated with ground-based soil moisture measurements over the continental U.S. for five consecutive warm seasons (May–September of 2015–2019). The result shows that both SMAP and ASCAT retrievals improve the accuracy of soil moisture estimates. Especially, the SMAP single-sensor assimilation experiment shows the best performance with the increase of temporal anomaly correlation by ΔR ~ 0.05 for surface soil moisture and ΔR ~ 0.03 for root-zone soil moisture compared with the LSM simulation without satellite data assimilation. SMAP assimilation is more skillful than ASCAT assimilation primarily because of the greater skill of the assimilated SMAP retrievals compared to the ASCAT retrievals. The skill improvement also depends significantly on the region; the higher skill improvement in the western U.S. compared to the eastern U.S. is explained by the Kalman gain in the two experiments. Additionally, the regional skill differences in the single-sensor assimilation experiments are attributed to the number of assimilated observations. Finally, the soil moisture assimilation estimates provide more realistic land surface information than model-only simulations for the 2015 and the 2016 western U.S. droughts, suggesting the advantage of using satellite soil moisture retrievals in the current drought monitoring system.

SMAP↗

Soil Water Percolation Chemistry, April 2017 to March 2019, BR-Ma2, Manaus

Soil water percolation chemistry including major cations, anions and isotope geochemistry. Samples were collected from six passive wick flux meters across three topographic positions (valley, slope and plateau). Data has been processed to compute the monthly mean for each topographic position where two flux meters were installed at each topographic position. All samples were processed at the Geology, Geochemistry and Geomaterials Research Laboratory (GGRL) in Los Alamos, NM USA. The metadata tab included in the .csv has additional information on locations where the sensors were installed, and other installation/maintenance details. Contact ksolander@lanl.gov if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗

Feasibility Study of Radiometry for Airborne Detection of Aviation Hazards

Radiometric sensors for aviation hazards have the potential for widespread and inexpensive deployment on aircraft. This report contains discussions of three aviation hazards - icing, turbulence, and volcanic ash - as well as candidate radiometric detection techniques for each hazard. Dual-polarization microwave radiometry is the only viable radiometric technique for detection of icing conditions, but more research will be required to assess its usefulness to the aviation community. Passive infrared techniques are being developed for detection of turbulence and volcanic ash by researchers in this country and also in Australia. Further investigation of the infrared airborne radiometric hazard detection approaches will also be required in order to develop reliable detection/discrimination techniques. This report includes a description of a commercial hyperspectral imager for investigating the infrared detection techniques for turbulence and volcanic ash.

Gimmestad, Gary G.↗

Three-Dimensional Sensor Forward Modeling of Clouds and Precipitation in the Multi-Instrument Inverse Solver Testbed (MIIST)

Sensor forward models are an essential tool for interpreting remote sensing observations and performing quantitative estimates of geophysical parameters. Our three-dimensional forward modeling and retrieval framework allows us to perform detailed analyses of NASA field campaign datasets for a deeper understanding of the remote sensing of clouds and precipitation. This presentation details the componenets of this radiative transfer model used to simulate active (radar) and passive (microwave radiometer) observations, and we give some relevant examples based on both model precipitation systems and actual observations.

Adams, Ian S.↗

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗

Optoelectronic Docking System

Sensors and computers control approach and coupling. Proposed optoelectronic system with no moving parts automatically controls approach of two spacecraft as they closed from distance of about 1 km to within few cm. System concept modified for use on Earth in robotic assembly, to control docking of large ships, or to guide placement of large structural components. Optoelectronic docking system automatically controls approach of active vehicle or mechanism to passive vehicle or object. Maneuvers of approaching vehicle controlled in response to optoelectronically sensed relative position of approached vehicle.

Ward, S. M.↗

Validation of SMAP Surface Soil Moisture Products with Core Validation Sites

The NASA Soil Moisture Active Passive (SMAP) mission has utilized a set of core validation sites as the primary methodology in assessing the soil moisture retrieval algorithm performance. Those sites provide well calibrated in situ soil moisture measurements within SMAP product grid pixels for diverse conditions and locations.The estimation of the average soil moisture within the SMAP product grid pixels based on in situ measurements is more reliable when location specific calibration of the sensors has been performed and there is adequate replication over the spatial domain, with an up-scaling function based on analysis using independent estimates of the soil moisture distribution. SMAP fulfilled these requirements through a collaborative CalVal Partner program.This paper presents the results from 34 candidate core validation sites for the first eleven months of the SMAP mission. As a result of the screening of the sites prior to the availability of SMAP data, out of the 34 candidate sites 18 sites fulfilled all the requirements at one of the resolution scales (at least). The rest of the sites are used as secondary information in algorithm evaluation. The results indicate that the SMAP radiometer-based soil moisture data product meets its expected performance of 0.04 cu m/cu m volumetric soil moisture (unbiased root mean square error); the combined radar-radiometer product is close to its expected performance of 0.04 cu m/cu m, and the radar-based product meets its target accuracy of 0.06 cu m/cu m (the lengths of the combined and radar-based products are truncated to about 10 weeks because of the SMAP radar failure). Upon completing the intensive CalVal phase of the mission the SMAP project will continue to enhance the products in the primary and extended geographic domains, in co-operation with the CalVal Partners, by continuing the comparisons over the existing core validation sites and inclusion of candidate sites that can address shortcomings.

SMAP↗

An active role of the amyloplasts and nuclei of root statocytes in graviperception

Three main phases are discerned in the gravitropic reaction: perception of a gravitational stimulus, its transduction, and fixation of the reaction resulting in bending of an organ. According to the starch-statolith hypothesis of Nemec and Haberlandt, amyloplasts in the structurally and functionally specialized graviperceptive cells (statocytes) sediment in the direction of a gravitational vector in the distal part of a cell while a nucleus is in the proximal one. If amyloplasts appear to act as gravity sensors, the receptors, which interact with sedimented amyloplasts, and next signaling are still unclear. An analysis of the structural-functional organization of cells in different root cap layers of such higher plants as pea, Arabidopsis thaliana, and Brassica rapa grown under 1 g, on the clinostats, and in microgravity, allows us to support the hypothesis that amyloplasts function as statoliths in statocytes, but they may not be only the passive statolithic mass. We propose that amyloplasts fulfill a more complex function by interacting with a receptor, which is a nucleus, in transduction of some signal to it. Gravity-induced statolith movement in certain order leads to a new functional connection between gravity susceptors--amyloplasts and a receptor--a nucleus receiving some signal presumedly of a mechanical or biochemical nature from the amyloplasts. During gravitropism, sugar signaling could induce expression of genes encoding auxin transport proteins in a nucleus giving the nucleus an intermediate role in signal trunsduction following perception. c 2001 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

short duration↗

Plant Water Management in Microgravity

The NASA Plant Water Management (PWM) technology demonstrations aboard ISS apply recent advances in microgravity capillary fluidics research towards the mundane yet problematic challenges of simply watering plants in space. Plant growth in a low-g environment is often hampered by inadequate aeration and over-saturation of the root zone. The present effort aims to exploit the passive capillary forces of poorly wetting liquids (i.e., contaminated water) within unique system geometries that effectively replace the role of gravity in providing sufficient aeration and hydration for simulated plants. Several flight demonstrations have been completed on ISS, including soil and hydroponic models in single and parallel channel networks. Two future demonstrations are still in work and plan to further develop the system to handle sustained plant growth with additional sensors to monitor the growth environment. The results to date demonstrate proof-of-concept, system stability, limits of operation, and more, for simulated plant models. Eventually, real plants will be incorporated into these systems and tested on orbit. The implications are discussed in relation to plant growth facilities for further near-term microgravity plant science research as well as for automated food production for long duration human exploration missions.

microgravity↗

Collaborative Supervised Learning for Sensor Networks

Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.

Wagstaff, Kiri L.↗

Deployable Fresnel Rings

Deployable Fresnel rings (DFRs) significantly enhance the realizable gain of an antenna. This innovation is intended to be used in combination with another antenna element, as the DFR itself acts as a focusing or microwave lens element for a primary antenna. This method is completely passive, and is also completely wireless in that it requires neither a cable, nor a connector from the antenna port of the primary antenna to the DFR. The technology improves upon the previous NASA technology called a Tri-Sector Deployable Array Antenna in at least three critical aspects. In contrast to the previous technology, this innovation requires no connector, cable, or other physical interface to the primary communication radio or sensor device. The achievable improvement in terms of antenna gain is significantly higher than has been achieved with the previous technology. Also, where previous embodiments of the Tri-Sector antenna have been constructed with combinations of conventional (e.g., printed circuit board) and conductive fabric materials, this innovation is realized using only conductive and non-conductive fabric (i.e., "e-textile") materials, with the possible exception of a spring-like deployment ring. Conceptually, a DFR operates by canceling the out-of-phase radiation at a plane by insertion of a conducting ring or rings of a specific size and distance from the source antenna, defined by Fresnel zones. Design of DFRs follow similar procedures to those outlined for conventional Fresnel zone rings. Gain enhancement using a single ring is verified experimentally and through computational simulation. The experimental test setup involves a microstrip patch antenna that is directly behind a single-ring DFR and is radiating towards a second microstrip patch antenna. The first patch antenna and DFR are shown. At 2.42 GHz, the DFR improves the transmit antenna gain by 8.6 dB, as shown in Figure 2, relative to the wireless link without the DFR. A figure illustrates the relative strength of power coupling between the first and second microstrip antennas with and without the DFR. Typically, a DFR is designed for use at a particular frequency; however, testing of a DFR indicated a relatively wide operational bandwidth of approximately 8.2%. Wider bandwidth operation and multi-band operation are anticipated by extending the known art of conventional Fresnel rings to the DFRs. Increasing the number of rings used to construct a DFR antenna increases the gain, with the upper bound limited often by the largest practical dimensions that can be tolerated for a given application. The maximum theoretical improvement in gain for a single ring is 9.5 dB. Experimental results are within 0.9 dB of this theoretical value. Adding rings increases gain, and theoretically, improvements of 10 to 13 dB above that of the primary antenna gain can be achieved with two- and three-ring versions.

Kennedy, Timothy F.↗

Passivation of Flexible YBCO Superconducting Current Lead With Amorphous SiO2 Layer

Adiabatic demagnetization refrigerators (ADR) are operated in space to cool detectors of cosmic radiation to a few 10s of mK. A key element of the ADR is a superconducting magnet operating at about 0.3 K that is continually energized and de-energized in synchronism with a thermal switch, such that a piece of paramagnetic salt is alternately warm in a high magnetic field and cold in zero magnetic field. This causes the salt pill or refrigerant to cool, and it is able to suck heat from an object, e.g., the sensor, to be cooled. Current has to be fed into and out of the magnets from a dissipative power supply at the ambient temperature of the spacecraft. The current leads that link the magnets to the power supply inevitably conduct a significant amount of heat into the colder regions of the supporting cryostat, resulting in the need for larger, heavier, and more powerful supporting refrigerators. The aim of this project was to design and construct high-temperature superconductor (HTS) leads from YBCO (yttrium barium copper oxide) composite conductors to reduce the heat load significantly in the temperature regime below the critical temperature of YBCO. The magnet lead does not have to support current in the event that the YBCO ceases to be superconducting. Cus - tomarily, a normal metal conductor in parallel with the YBCO is a necessary part of the lead structure to allow for this upset condition; however, for this application, the normal metal can be dispensed with. Amorphous silicon dioxide is deposited directly onto the surface of YBCO, which resides on a flexible substrate. The silicon dioxide protects the YBCO from chemically reacting with atmospheric water and carbon dioxide, thus preserving the superconducting properties of the YBCO. The customary protective coating for flexible YBCO conductors is silver or a silver/gold alloy, which conducts heat many orders of magnitude better than SiO2 and so limits the use of such a composite conductor for passing current across a thermal gradient with as little flow of heat as possible to make an efficient current lead. By protecting YBCO on a flexible substrate of low thermal conductivity with SiO2, a thermally efficient and flexible current lead can be fabricated. The technology is also applicable to current leads for 4 K superconducting electronics current biasing. A commercially available thin-film YBCO composite tape conductor is first stripped of its protective silver coating. It is then mounted on a jig that holds the sample flat and acts as a heat sink. Silicon dioxide is then deposited onto the YBCO to a thickness of about 1 micron using PECVD (plasma-enhanced chemical vapor deposition), without heating the YBCO to the point where degradation occurs. Since SiO2 can have good high-frequency electrical properties, it can be used to coat YBCO cable structures used to feed RF signals across temperature gradients. The prime embodiment concerns the conduction of DC current across the cryogenic temperature gradient. The coating is hard and electrically insulating, but flexible.

Johannes, Daniel↗

Pyroelectric Applications of the VDF-TrFE Copolymer

VDF/TrFe pyroelectric sensors have now definitely reached the level of a product. Based on a bidimensional staring array, it can be considered as a whole system with a monolithic technology processed on a silicon substrate provided with the integrated read out circuit. The paper will describe the main procedure dealing with the elaboration of a 32 x 32 focal plane array developed, in the context of the PROMETHEUS PROCHIP European Program (EUREKA), as a passive infrared obstacle detection applied to automotive. Additional experimental data suggest that this microsystem could operate in space environment.

Simonne, J. J.↗

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

clouds↗

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S. Faragalla↗

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S Faragalla↗