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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Closed Loop Control Compact Exercise Device for Use on MPCV

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. To combat spaceflight physiological deconditioning, astronauts will use resistive and aerobic exercise regimens for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the mass and volume available for an exercise device in the next generation of spacecraft is limited. Therefore, compact exercise device prototypes are being developed for human in the loop evaluations. The NASA Human Research Program (HRP) is managing Advanced Exercise Concepts (AEC) requirements development and candidate technology maturation for all exploration mission profiles from Multi-Purpose Crew Vehicle (MPCV) exploration missions (e.g., EM-2, up to 21 day) to Mars Transit (up to 1000 day) missions. Numerous technologies have been considered and evaluated against HRP-approved functional requirements and include flywheel, pneumatic and closed-loop microprocessor-controlled motor driven power plants. Motor driven technologies offer excellent torque density and load accuracy characteristics as well as the ability to create custom mechanical impedance (the dynamic relationship between force and velocity) and custom load versus position exercise algorithms. Further, closed-loop motor-driven technologies offer the ability to monitor exercise dose parameters and adapt to the needs of the crewmember for real time optimization of exercise prescriptions. A simple proportional-integral-derivative (PID) controller is demonstrated in a prototype motor driven exercise device with comparison to resistive static and dynamic load set points and aerobic work rate targets. The resistive load term in the algorithm includes a constant force component (Fcmg) as well as inertial component (Fima) and a discussion of system tuning is presented in terms of addressing key functional requirements and human interfaces. The device aerobic modality is modelled as a rowing exercise using ground data sets obtained from Concept 2 rowers as well as competitive rowing1. A discussion of software and electronic implementations are presented which demonstrate unique approaches to meeting the constrained mass, volume and power requirements of the MPCV. . In addition to utilizing traditional PID control, controllers utilizing state feedback with gains solved using a Linear Quadratic Regulator will be developed. Controllability and observability will be utilized to investigate the need for state measurement in the design. As the control system directly interacts with human test subjects, robust methods such as H-infinity are also being investigated.1. Kleshnev V. Biomechanics. In: Rowing, Handbook of Sports Medicine and Science. ed. by Secher N., Voliantis S. IOC Medical Commission, Blackwell Pub. pp. 22-34, 2007

microgravity↗
NASA NTRS2018

Next-Generation Fluids-Related Biology Research Utilizing the Zero Gravity Research Facility at NASA Glenn Research Center

In order to gain insight into how cells sense gravity, NASA has developed a platform to investigate the transient (short-term) response of biological cells to a sudden exposure to microgravity. Utilizing NASA's Zero Gravity Research Facility offers unique capabilities and opportunity to investigate this phenomena. A review of current literature indicates that it remains unclear how biological cells sense and respond to gravitational forces. It is believed that a combination of bio-structural and fluid transport mechanisms are at play. This Technical Memorandum outlines a pathway to address this fundamental biological challenge. A series of low-cost systematic drop tower experiments were conducted to observe the biomechanical behavior of cell membranes (such as vestibular hair, endothelial, and bone cells) that are known to exhibit sensitivity to gravity. These experiments demonstrated a useful, low cost experiment concept that can potentially be employed by researchers interested in observing, identifying and characterizing changes in biological cell morphology.

Fluids for Biology↗
NASA NTRS2018

High-precision Method for Cyclic Loading of Small-Animal Vertebrae to Assess Bone Quality

One potentially important bone quality characteristic is the response of bone to cyclic (repetitive) mechanical loading. In small animals, such as in rats and mice, cyclic loading experiments are particularly challenging to perform in a precise manner due to the small size of the bones and difficult-to-eliminate machine compliance. Addressing this issue, we developed a precise method for ex vivo cyclic compressive loading of isolated mouse vertebral bodies. The method has three key characteristics: 3D-printed support jigs for machining plano-parallel surfaces of the tiny vertebrae; pivotable loading platens to ensure uniform contact and loading of specimen surfaces; and specimen-specific micro-CT-based finite element analysis to measure stiffness to prescribe force levels that produce the same specified level of strain for all test specimens. To demonstrate utility, we measured fatigue life for three groups (n = 5-6 per group) of L5 vertebrae of C57BL/6J male mice, comparing our new method against two methods commonly used in the literature. We found reduced scatter of the mechanical behavior for this new method compared to the literature methods. In particular, for a controlled level of strain, the standard deviation of the measured fatigue life was up to 5-fold lower for the new method (F-ratio = 4.9; p < 0.01). The improved precision for this new method for biomechanical testing of small-animal vertebrae may help elucidate aspects of bone quality.

Bone quality↗
NASA NTRS2019

Assessment of Upper Body Posture and Shape with Garment-Embedded Flexible Strain Sensors

Spacesuits are critical to performing spacewalks or EVA, however can increase injury risks due to - Spacesuit Fit Concerns: Astronauts come from a diverse population; Improper suit fit will result in persistent contact and mechanical pressure on the body. - Altered Biomechanics: Mechanical constraints and pressurization can make it difficult due to - Reduced range of motion, Reduced strength capability. To improve suit design and mitigate injuries, kinematic and geometric measurements are required during EVA evaluations - Human motions inside a spacesuit may not coincide with the suit motions: Spacesuit configurations do not exactly match with human anatomical joints; Gaps/paddings inside the suit induce lags between human motion and suit motion - Conventional motion capture or 3-D scanning techniques are difficult to use to measure internal motion: Optical occlusions; Volume restrictions; Ferrous magnetic interference.

Vu, Linh↗
NASA NTRS2019

Development of Human-Spacesuit Interaction Models

Today’s astronaut corps represents a wide range of various anthropometric dimensions. Accommodating this wide range of anthropometry and protecting for size variations in future crews, makes spacesuit sizing and fit a challenging and necessary aspect of suit development. Spacesuit fit can play an important role in performance, but a suit fit assessment, especially in dynamic postures, is difficult without extensive human-in-the-loop testing. One approach to address this issue is to model and simulate the human-spacesuit interactions for a target population early in the design process. The Anthropometry and Biomechanics Facility (ABF) at the NASA Johnson Space Center has been working to incorporate parametric human models based on 3D full-body scan data with spacesuit CAD models that can be driven by the user or imported motion capture data. An articulated spacesuit model combined with a poseable high-fidelity human model allows comparisons to be made between spacesuit capabilities and normal human ranges of motion. Furthermore, predictions can be made as to how a specific individual or population may perform in the suit from the perspective of reach and mobility. In this paper, we will present case study examples of reach, mobility, and fit analyses that can be done with these models and the methodology developed thus far. These models have the potential to become powerful tools for evaluating future spacesuit design architectures from the perspective of optimizing fit and performance.

Jarvis, Sarah↗
NASA NTRS2021

Analysis of Exercise Loads to Inform Vibration Isolation System Design

BACKGROUND: This study was conducted with the primary interest of providing data that would inform Vibration Isolation and Stabilization (VIS) system design and performance for the European Enhanced Exploration Exercise Device (E4D). In preparation for the International Space Station (ISS) in-flight demonstration, a list of critical Human Health Countermeasures (HHC) exercises was compiled [1]. The goal of this study was to assess the ground reaction forces and moments imposed by an exercising subject in each of the six VIS Degrees of Freedom (DOFs) during a comprehensive set of these critical exercises performed on the E4D. METHODS AND RESULTS: The ISS in-flight demonstration list of critical exercises included seated aerobic rowing, bent-over rowing, cycling, front squats, back squats, conventional deadlifts, Romanian deadlifts, heel raises, overhead presses, reverse chops, and power clean presses. At the NASA Johnson Space Center (JSC) Prototype Immersive Technology (PIT) laboratory, motion capture data were collected on critical E4D exercises for six subjects. At the NASA JSC Active Response Gravity Offload System (ARGOS) facility, additional motion capture and load cell data were collected on offloaded trials for four subjects. Select data were extrapolated to represent a 5th percentile female subject and a 95th percentile male subject. A previous investigation comparing the forces obtained from the load cell and from motion capture based data found a satisfactory level of agreement between the two measurements [2]. The motion capture based data were analyzed for this study since it is driven by the subject’s trajectory alone, automatically excluding any forces exerted on the subject by the ARGOS offloading harness. The OpenSim [3, 4] biomechanical simulation inverse kinematics tool was used to calculate the joint angles based on the locations of motion capture markers placed at key positions on the subject’s body. An OpenSim plugin was then used to obtain the forces and moments generated by the subject during each trial, with the moments computed relative to the equilibrium location of the subject’s feet [5]. The force of gravity was also removed to simulate the loads generated by the exercise when performed in microgravity. The load plots for each trial were generated and visually analyzed to obtain the magnitudes of the peak loads for each exercise in each DOF. The typical period of exercise for each trial was also estimated and used to calculate the frequency for each trial. The exercise loads data was then organized in multiple ways to capture different aspects of the data. As a result of this study, we present a summary of the load magnitudes observed during these critical exercises utilizing the E4D.

C A Bell↗
NASA NTRS2021

Feasibility of Earthbound Motion in Lunar Gravity

BACKGROUND: Marginal stability of astronaut movement while performing lunar surface tasks has been well documented, and is clearly demonstrated in videos of falls, and near falls, during Apollo Lunar Extravehicular Activities. Referencing mission reports from Apollo 15 and 16 [1, 2], suspected causes for falls include: surface conditions, visibility, and gravitational effects (hypogravity). In this preliminary test, we employ the open-source biomechanical tool OpenSim [3, 4] to analyze the impact of lunar gravity (Lg) on two object-pickup motions performed by a single shirt-sleeved subject. Specifically, we attempt to answer the following questions based on an estimation of the Center of Mass Projection (CoMP) and ground reaction force Center of Pressure (COP) as it relates to the astronaut Base of Support (BOS) for 1g and Lg conditions: 1. Is the task motion, as performed in 1g, dynamically feasible in 1g and Lg? 2. Can we make the motion dynamically feasible in Lg by slowing it down? 3. Is the Lg COP equal to the 1g COP at a theoretically predicted reduction in motion speed? METHODS AND RESULTS: To answer the first question, the gravitational acceleration in the OpenSim model is modified from a nominal 9.81 m/s2 to 1.64 m/s2, and the 1g joint trajectory is input to an OpenSim based method [5] for estimating ground reaction forces and moments. From this method, the position of the CoMP and COP can be estimated and checked to see if they remain within a simulated BOS formed from the footprint of the OpenSim model to determine whether the motion is dynamically feasible. As expected, both of the motions were estimated to be feasible in a 1g environment, however, both motions had periods of infeasibility in Lg. It is well known that crew members make adjustments to motion trajectories in altered gravity fields to maintain balance. As a first step, we considered the simple adjustment of slowing the motion in Lg by a constant factor. This was accomplished by scaling the time stamps in the motion trajectory file by that factor. For the two motions considered, it was found that scale factors of 1.3 and 1.4 kept the COP just within the subject BOS. The CoMP is unchanged by the gravity field. Simple analysis of an inverted pendulum in the Lg environment, which generalizes to a general multibody system, leads to a theoretical prediction that a reduction in speed factor of √1g/Lg, or 2.445, will make the COP trajectory in Lg equivalent to that in 1g. When the above procedure was performed with a factor of 2.445, the estimated COP in Lg, was observed to be very close to that in 1g. In summary, we have developed a method for estimating the CoMP and COP in Lg, for subject motion collected in 1g. We believe this method can prove to be a valuable check and balance for simulated Lg training and testing by exposing potential simulator-induced artifacts that make the simulated task motion seem possible, when in fact, it would violate the above criteria. We also note that a reduction in task speed should tend the task motion towards stability, with a theoretical slowdown factor of √1g/Lg making the motion stability equal to that in 1g according to the CoMP and COP criteria.

R K Huffman↗
NASA NTRS2020

Multibody Based Digital Astronaut Dynamics Simulation

BACKGROUND: This study provides the Software, Robotics, & Simulation Division at the NASA Johnson Space Center with a verification tool for multibody dynamics simulation requiring human motion. The motivation stems from current studies of several Vibration Isolation & Stabilization(VIS)system designs that attenuate the moments and forces which would be transmitted to a spacecraft during an exercise. A multibody dynamics model for a proposed VIS was available previously[1], therefore modeling of the VIS was not needed for this work. The interest here is in creating the multibody dynamics model of an astronaut in motion which may be utilized independently or while attached to a mechanism. An existing simulation [2] that utilizes OpenSim [3,4] and an in-house multibody dynamics package (MBDyn) [5] is used in order to verify the astronaut model. The main advantage this model will have over the existing simulation is that everything will be processed in one tool. METHODS AND RESULTS: Creating the simulation required; estimation of Body Segment Inertial Parameters (BSIP),a multibody model of the human-VIS system, joint acceleration profiles, and input files for MBDyn, which is used for this analysis. The scaling factors provided by Dumas et al. [6] are utilized in estimating the BSIP. Anthropometric data are used for estimating these parameters, the Anthropometric Survey of US Army Personnel (ANSUR II) [7] was the source. The astronaut model consists of 15 bodies, 14 joints and 32 degrees of freedom, with the dynamics topology generated using the center of mass locations and anthropometric data. MBDyn has an option for prescribed joint motion (PJM), which requires joint acceleration data as input. The joint angle data is first obtained from a motion capture system and then processed through code that has been created to generate approximate joint acceleration profiles. The topology tree for the astronaut model begins at the right foot up to the pelvis where there is one branch for going down the left leg and another for the torso. The torso branch leads to branches for the arms and a leaf body for the head/neck segment. For attachment to the VIS, the heel of the right foot is connected to the VIS platform through a fixed joint, resembling a foot restraint. The left foot does not attach to the platform in order to prevent a system with a closed loop. Topology and symmetry of the astronaut model were verified through kinematic analysis. Further verification of the forces and moments transmitted to the VIS were verified against the existing simulation. There was a satisfactory level of agreement when testing a simple motion, for example, rocking back and forth. Full exercise motions are to be tested soon. The main outcome has been a novel application of MBDyn for biomechanics modeling that is now available for dynamic simulations involving human motion. The estimation of BSIP was another useful result of this study, requiring only 15 inputs for generating mass properties of a theoretical astronaut model. Expansion on this work is possible by going through an alternative route in obtaining the joint motion data. Instead of high-tech and often expensive motion capture systems, an individual may watch videos with high focus and at a slow motion for each individual segment in order to determine the initial and final time and angle for that specific degree of freedom. Synthetic trajectories may also be created if there is no video reference available.

F N Matari↗
NASA NTRS2021

Lunar Surface Operations Modeling Using Digital Astronaut Simulation

During Apollo, crew members experienced a number of falls while engaging in extravehicular activity. The Digital Astronaut Simulation (DAS) expanded human biomechanics modeling tools to begin investigating this prospective mission safety and success challenge for the Artemis program. A core capability was developed to detect if a motion is dynamically feasible in a given gravitational environment. Fed by motion capture and mass properties data, this technology enables observation of whether tasks performed in 1G can be performed the same way in lunar gravity or if they require modifications.

Long Duration Health↗
NASA NTRSDate not supplied

Scientific Physical and Operations Characterization (SPOC): Studying Scientists in the Wild to Inform Human Planetary Exploration Operations

The objective of the Scientific Physical and Operational Characterization (SPOC) project is to build an evidence-based description of terrestrial field science to inform the operational, physical, and tool requirements for planetary exploration extravehicular activities (xEVAs). EVAs of the future, including Artemis 2024 and beyond, intend to promote scientific productivity (e.g., LEAG science goals)[1]; however, no clear, objective pathway currently exists to enable this goal, particularly with respect to the desired increase in autonomy imparted to future astronauts. The SPOC project applies expertise in the fields of cognitive systems engineering [2-5], biomechanics, wearable sensors [6-8] and hardware/software to more targetly address these issues. In doing so, a terrestrial fieldwork ground-truth can be established that will benefit human and robotic exploration of other planetary surfaces.

M J Miller↗
NASA NTRSDate not supplied

Modeling and Simulation Efforts to Support Improved Comfort in ARGOS

BACKGROUND: The Active Response Gravity Offload System (ARGOS) provides an analog environment for extravehicular activity (EVA) testing and training. Discomfort has been observed during longer suited test sessions. While the subject’s core is offloaded during surface EVA evaluations, his/her arms experience full Earth gravity and can become overly fatigued, especially during suited tests which involve reaching and prolonged arm extensions. A device (ARGOS Negation of Gravitational Effects on the Limbs: ANGEL) to offload the weight of the arms and suit sleeves is being developed by JSC’s Flight Systems Branch, and here we present preliminary modeling of that device using the open-source biomechanical tool OpenSim [1,2] with an in-house developed plugin. We analyze a series of motions performed by a single shirt-sleeved subject with goals of characterizing the device, validating the model, and predicting whether reduced gravity conditions (i.e., lunar gravity (Lg) or Martian gravity (Mg)) can be accurately simulated with the device, as well as providing comfort to the ARGOS user. METHODS AND RESULTS: To model the offload device, we augment the OpenSim human model topology with the offload mechanism components and joints, using CAD models to represent the mechanism graphically. The joint angles of the device are either obtained from (1) inverse kinematics (IK) using motion capture markers on the various components of the device or (2) calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. Given the joint angles of the device, the resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) in order to enable study of overall shoulder joint torques as well as offload achieved. We verify the calculated joint angles by using the inverse kinematic data and the forces from manual measurements of the spring both independently and integrated within the device. We found that calculated joint angles generally represent the angles measured and computed with IK, supporting a possible analysis workflow inputting human motion data and observing system behavior under varied design parameters. In two different device configurations in which the maximum applied force was 131 N, our current model accurately captured force with a difference of 2-3 N from measured loads. Though our initial test was performed with a shirt-sleeve subject, arm weights were added to emulate the weight of the suit sleeve and the subject was positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup. Arm range of motion tasks were performed outside of the HUT, inside the HUT, and inside the HUT while using the device. A variety of other upper body tasks were completed as well. In summary, we have developed a model to investigate and verify an upper limb offload device currently in development. We believe this model will be a valuable tool not only for device characterization but also to predict proper configurations to simulate Lg or Mg conditions, investigate range of motion concerns, predict limitations such as internal collisions and contacts, and inform future design improvements.

L B Nilsson↗
NASA NTRSDate not supplied

Accuracy of Center of Pressure Determination via Motion Capture

BACKGROUND: This study was conducted to support the stability assessment for tasks in lunar gravity and exercises on a Vibration Isolation and Stabilization (VIS) system in microgravity based on the dynamic feasibility criterion of whether the calculated position of the center of pressure (COP) falls within the base of support (BOS) which outlines the subject’s feet. Motion capture data combined with biomechanical modeling and simulation allows the forces and moments between the human and the VIS platform to be computed and the position of the COP as well as the location and shape of the BOS to be determined. The goal of this study was to assess the accuracy of the COP trajectory calculated using motion capture-based data. METHODS AND RESULTS: To obtain the dynamic quantities from which COP is calculated, motion capture data is first collected in the 1g lab environment by recording the trajectories of passive retroreflective markers placed on a subject during exercise or performance of a given task. The OpenSim [1] inverse kinematics (IK) tool is used to fit a scaled subject model to recorded marker trajectories while minimizing marker error to obtain joint angles. Then, a custom OpenSim plugin [2] is used to determine the subject’s time-varying moment of inertia and its time derivative, center of mass (CM) position, velocity, and acceleration, as well as the angular momentum and its time derivative relative to the subject’s CM. Some of these quantities are not needed for modeling tasks performed on a stationary lunar surface but, due to the moving exercise platform, are needed to model VIS response to the subject’s motion. Hand positions, used in calculating a cable force if present, are recorded as well. These quantities are used to calculate the total force (F ⃗^((plate) )) and moment (M ⃗^((plate) )) exerted by the lunar surface or the VIS plate on the subject’s shoe soles. COP is then calculated from the following equations: r_x^((cop) )= M_z^((plate) )/F_y^((plate) ) and r_z^((cop) )= 〖-M〗_x^((plate) )/F_y^((plate) ), where the y axis is normal to the surface. COP accuracy for feasibility assessments is then determined by whether it falls within the BOS, which is also computed by the plugin. To study the accuracy of COP calculated from motion capture, we first investigated whether COP remained within the BOS, as it must, for exercises performed in the 1g lab environment. Standard exercises such as back squat and deadlift were analyzed, as well as more explosive exercises including hang clean and press. Cases in which the COP exited the BOS indicated that COP accuracy required further investigation. In this study, an exercise device with cables was used, so cable force modeling accuracy should also be considered. In a separate study, we collected motion capture and force plate data for twenty-seven motions not involving an exercise device. About a third were genuine countermeasures exercises (e.g., hang clean and press), some were relevant for lunar tasks (e.g., object pick up), and the rest were of a “unit test” nature (e.g., swaying back and forth or side to side). Motion capture-based COP positions were compared with force plate measured COP. We found that while force plate measured COP remained within the BOS, motion capture-based COP was observed to briefly exit the BOS on occasion. Techniques to mitigate IK artifacts and filtering of calculated data could be used to improve the agreement of calculated and measured results, resolving excursions from the BOS within this dataset. The mean error between calculated and measured COP was found to be less than 6 mm. Additionally, we derived and investigated equations for the COP in terms of the cable force, cable location, as well as the human CM position, acceleration, and angular momentum with respect to the CM, and analyzed them for sensitivity to errors in individual quantities. Several were found, but the most significant one was that when the vertical force on the feet approaches zero, indicating a near-detachment or ‘jump off’ condition, errors are amplified. This is consistent with the observation that in the absence of pressure, the concept of the center of pressure would become meaningless.

C A Bell↗
NASA NTRS2022

Role of RpoS in regulating stationary phase Salmonella Typhimurium pathogenesis-related stress responses under physiological low fluid shear force conditions

The discovery that biomechanical forces regulate microbial virulence was established with the finding that physiological low fluid shear (LFS) forces altered gene expression, stress responses, and virulence of the enteric pathogen Salmonella enterica serovar Typhimurium during log phase. These log phase LFS-induced phenotypes were independent of the master stress response regulator, RpoS (S). Given the central importance of RpoS in regulating stationary phase stress responses of S. Typhimurium cultured under conventional shake flask and static conditions, we examined its role in stationary phase cultures grown under physiological LFS. We constructed an isogenic rpoS mutant derivative of wild type S. Typhimurium and compared the ability of these strains to survive in vitro pathogenesis-related stresses that mimic those encountered in the infected host and environment. We also compared the ability of these strains to colonize (adhere, invade, and survive within) human intestinal epithelial cell cultures. Unexpectedly, LFS-induced resistance of stationary phase S. Typhimurium cultures to acid and bile salts stresses did not rely on RpoS. Likewise, RpoS was dispensable for stationary phase LFS cultures to adhere to and survive within intestinal epithelial cells. In contrast, the resistance of these cultures to challenge with oxidative and thermal stresses, and their invasion into intestinal epithelial cells was influenced by RpoS. These findings expand our mechanistic understanding of how physiological fluid shear forces modulate stationary phase S. Typhimurium physiology in unexpected ways and provide clues into microbial mechanobiology and nuances of Salmonella responses to microenvironmental niches in the infected host.

Karla Franco Meléndez↗
NASA NTRSDate not supplied

TOWARD A METHOD FOR SCALING HUMAN BODY MODELS IN AN IMU-BASED WORKFLOW

BACKGROUND Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, these lengths are determined by motion capture or manual measurement. A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. For example, to measure forearm length, an IMU is placed at the wrist, the point of rotation is at the elbow, and the isolated motion is forearm flexion and extension. These calculated lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. Utilizing IMUs for data collection also provides the synergistic ability to record data without a dedicated space in a room with many cameras, therefore reducing the data collection footprint, or record data where optical motion capture is not possible, such as inside a spacesuit. METHODS AND RESULTS To test this method, upper body data collection was performed with 5 Xsens DOT IMUs on a single subject. IMUs consist of an accelerometer, a gyroscope, and a magnetometer which collect linear acceleration, angular velocity, and magnetic fluctuations, respectively. Before any ground-based laboratory collection, the magnetic fluctuations are used to correct the heading of the IMU in space relative to the Earth’s magnetic field. The direct measurement of angular velocity is integrated to calculate angular acceleration. Then the linear acceleration ( a ) and angular acceleration (α) are solved using r = at/α to calculate the radius, which in this case is the distance between the IMU and the point of rotation (i.e., segment length). The IMU must be placed at the most distal point of the limb being measured (i.e., ankle if measuring lower leg length) and the test plan must consist of an isolated motion about that limb’s proximal joint (i.e., knee flexion and extension if measuring lower leg length). The distances (radii) calculated at every time interval were filtered (bandpass filter keeping 5th-90th percentile data) to eliminate outliers and spurious data that occur when the isolated motion was stopped or nearly stopped. The remaining distances were averaged, resulting in the calculated limb length. Scaling factors were then computed by dividing the calculated limb length by the unscaled model’s length. These scale factors are plugged into the Scale Tool in OpenSim [1,2] to apply the scaling to the OpenSim Full Body Rajagopal Model [3,4]. Manual measurements of limb lengths were taken before data collection started and used for comparing against the calculated lengths. The Anthropometric Survey of US Army Personnel (ANSUR II) [5] was also used as a third source of reference for limb length measurements. The following measurements were retrieved from the subject before data collection: 34.5 cm from L1 to C7 (thorax), 25.7 cm from C7 Joint Center (JC) to head vertex (neck and head), 36.3 cm from shoulder JC to elbow JC (humerus), 29.5 cm from elbow JC to wrist JC (forearm), and 16.2 cm from clavicle to acromion (clavicle). Of those five, forearm and humerus lengths were calculated using this proposed method to obtain preliminary results. The forearm length after filtering and averaging was calculated to be 37.6 cm. This is a 28% overestimation from the measured forearm length (29.5 cm). The humerus length after filtering and averaging was calculated to be 47.8 cm. This is a 31% difference from the measured subject length (36.3 cm). Sources of error include imperfect isolated motion (method currently expects that motion should be perfectly circular in a 2D plane, include no rotation of the IMU, and be relatively smooth; a more secure IMU attachment method will help), unrefined filter techniques (removed highest and lowest values with 20% high and low pass filters and no smoothing filters), arbitrary removal of stopped or near stopped data (kept data for only a short range before and after the angular velocity peaking), and a more representative method for removing gravitational acceleration is needed (current method is to zero all accelerations against a baseline taken just before the isolated motion which does not account for the gravitational acceleration changed due to IMU rotation during movement). Addressing these error sources will improve the accuracy of the limb length calculation. Next steps include creating a method for whole-body scaling estimation using individual limb scale factors. Continued pursuit of these techniques is expected to enable acquiring anthropometric information using only IMUs in real-time.

E. K. Marecki↗
NASA NTRS2023

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗
NASA NTRS2023

Modeling and Simulation for Exercise Vibration Isolation and Stabilization System Design

The microgravity environment that crew members experience on orbit presents a well-known health challenge, particularly when it comes to loss of muscle and bone mass. To counteract these negative effects, exercise countermeasures play a critical role in the daily routine of the crew on the International Space Station (ISS). To help inform requirements for upcoming exploration missions such as the Gateway Program, a new device, called the European Enhanced Exploration Exercise Device (E4D), is being built by the European Space Agency through their contractor, the Danish Aerospace Company. The E4D is being demonstrated on the ISS and is unique from other current exercise devices in that it provides four separate modalities in a single device: resistive, cycle ergometry, seated aerobic rowing, and rope pulling. To support the integration of E4D on ISS, a passive Vibration Isolation and Stabilization (VIS) system was required by NASA, and this responsibility was given to the Johnson Space Center. This paper describes the end-to-end process of modeling, simulation, and analysis used to inform the mechanical design of the VIS system. The process begins with the collection of representative exerciser motion capture (MoCap) through ground-based testing with the developmental E4D in both the Prototype Immersive Technology (PIT) Laboratory and the Active Response Gravity Offload System (ARGOS) facility at the Johnson Space Center. These collected MoCap data are processed through human biomechanics modeling to create forcing functions as input to a multibody dynamics simulation of the combined E4D/VIS system, with numerous resulting outputs. These outputs include microgravity accelerations, overall system displacements, internal and transmitted loads, as well as collisions. Microgravity accelerations are compared for compliance against ISS requirements while displacements are used for sway space determinations on the design and volumetric constraints within the targeted module. Internal loads are supplied to the supporting stress analysis teams and external loads for structural loads and dynamics teams, both at NASA and ESA. Finally, contact and clearance analysis is performed using the simulation to eliminate potential design issues. To ensure that the elements of the multibody simulation were verified and validated, correlation against multiple VIS related ground hardware testbeds was performed and characterized. In addition to the isolation part of the VIS problem, stabilization is also key to the integrated performance and evaluation. Due to the difficulty in defining ISS requirements in this area, the stability of the exerciser was inspected via analysis. Loss of balance was defined analytically as occurring when the resultant force vector acting on the exerciser lies outside the base of support of the feet. Both the VIS and E4D teams have recently gone through their Critical Design Reviews (CDRs) and the iterative model-based approach has been integral to inform mechanical design, particularly in the case of the VIS. This same end-to-end approach is now being applied for the Gateway Program, where an Exploration Exercise Device (EED) derived from the E4D and notional VIS for the device are under concept development.

Countermeasures↗
NASA NTRSDate not supplied

Recent Improvements and Verification of A Full Body Model in Opensim

BACKGROUND: The dynamic feasibility [1,2] criterion, that the subject’s Center of Pressure (COP) be located within the Base of Support (BOS) which outlines the feet, has aided in assessing the stability of human motion recorded on earth while performing the recorded tasks in lunar gravity or as countermeasures exercises on a vibration isolation and stabilization system in microgravity. The convex hull of the BOS on the platform under the subject’s feet was estimated using virtual markers on the feet of the scaled subject model. The COP was calculated using the ground reaction forces and moments determined from motion capture data with biomechanical modeling tools [3]. Occasionally, large-amplitude oscillatory spikes or “artifacts” were observed in the subject’s linear and angular momentum derivatives, affecting some COP data derived from motion capture. The purpose of this investigation was to assess and improve the accuracy of model scaling and BOS estimation as well as to determine the efficacy of model adjustments in mitigating artifacts influencing motion capture-derived ground reaction force and COP results. METHODS: To aid evaluation of proposed process and model updates, motion capture data were collected for two subjects during unit test and range of motion trials, lunar tasks, and countermeasures exercise motions. Markers were added to the full body Plug-in Gait marker set [4] during data collection. New markers were placed on the front, back, sides, and top of the head to improve scaling using distances between marker pairs. Medial elbow markers were added to stabilize the upper arm during OpenSim Inverse Kinematics (IK) [5]. Finally, markers were added on the outer edge of the heels and on the outside edges of the first and last toes on each foot. These additional foot markers were made available to test new automated foot scaling techniques and to calculate the error between the subject’s estimated and recorded BOS. The modified unscaled OpenSim Full Body Rajagopal Model [6,7] was adjusted using some previously investigated techniques [8] to mitigate rapid shifts in joint angles occurring during IK, as these were found to cause the spike artifacts observed in subsequent stages of analysis. Since OpenSim models use Euler angles and rotation sequences, the arm axes of rotation were adjusted, and the pelvis order of rotation was changed to minimize the likelihood of encountering “gimbal lock” during common human motion. The model clavicle, arm, elbow, wrist, pelvis, and ankle angle limits were adjusted to better accommodate the full human range of motion seen in exercise and lunar data. The shoulder joint center was calculated using a “pivoting” algorithm [9], and both shoulder joint center and upper arm markers were included during IK to provide additional shoulder stability on a case-by-case basis. The quality of IK results was assessed by three criteria: minimizing error between recorded motion capture markers and model markers, checking for reasonable rates of change in joint angles between fames (i.e., no IK artifacts), and ensuring the absence of spikes in the inertial forces and angular momentum derivatives calculated using a custom OpenSim plugin [10]. RESULTS: The additional markers placed on the subject during data collection allowed the head and feet to be scaled more accurately using distances between new marker pairs. Scaling with BOS markers placed on the subject and removing the limit on subtalar angle resulted in more accurate BOS determination. Unrealistically large changes in joint angles between frames could be reduced by including clavicle, sternum, and medial elbow markers during IK. In cases with large arm ranges of motion, results could be further improved by running IK using medial elbow and virtual shoulder joint center markers. Model adjustments significantly improved the IK results affecting COP calculation and increased the accuracy of BOS estimation.

C A Bell↗
NASA NTRSDate not supplied

Toward A Method for Scaling Human Body Models in an IMU-Based Workflow

- Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, limb lengths are determined by motion capture or manual measurement. - A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. - When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. - Calculated limb lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. - This method was investigated as a possible away to obtain scaling information in data collections where IMUs are worn, but optical motion capture may not always be available, such as inside spacesuits or during crew exercise on the International Space Station.

E. K. Marecki↗