Engineering topics

L J Quiocho

Publications and source records attributed to L J Quiocho.

15 records

NASA NTRS2024

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↗

NASA NTRS2023

Modeling and Simulation of the Angel Upper Limb Offload Device: Branching Into New Methods

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 of the Software, Robotics, and Simulation Division. Previously we have shared preliminary modeling of that device and kinematics based on motion capture data. Here we present an alternative approach to determine device kinematics by calculating ANGEL component angles with an OpenSim plugin. We compare calculated angles to inverse kinematics (IK) derived ones with the goal of validating the model. This new method can be further informative for device design and analytically testing different configurations to achieve desired reduced gravity conditions (e.g., lunar gravity (Lg) or Martian gravity (Mg)). We have compared calculated angles with IK-derived angles in tests with a shirt-sleeve subject positioned in a test stand with a Mark-III Hard Upper Torso (HUT) and Portable Life Support System (PLSS) mockup and arm weights to emulate the weight of the suit sleeve as well as a suited subject in ARGOS with a Mark-III suit. A variety of upper body tasks were completed in the former and full-body tasks in the latter. 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 calculated in the OpenSim plugin by modeling how the components configure themselves under the offloading spring tension given a particular IK-derived arm position. There are four ANGEL components with a total of 5 degrees of freedom (DOFs), each component has a single DOF except for the cuff which is modeled as 2 DOFs. The sickle/yaw bracket and cuff rotation angles are determined statically based on the assumptions that the sickle will track the attachment point of the cuff and that the cuff will rotate such that the attachment point is at its highest point. The cuff tilt, linker and V-bracket angles are then determined by optimizing their positions to approach a mechanical equilibrium. The calculated linker angle is compared to three different methods of determining the linker line-of-force kinematically (from V-bracket to center-cuff, cuff highest point or marker-derived position). Given the joint angles of the device, the spring force and resulting force on the arm is computed by the plugin and applied as an external load in inverse dynamics (ID) 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. The average difference in angles is the smallest for the V-bracket and linker, around 1 to 5 degrees for most trials. The resulting offload and shoulder torque are comparable between calculated and IK-derived angles. In summary, we have developed a method to calculate the joint angles of an exoskeleton-like upper limb offloading device currently in development. We have also developed a custom plugin which will be a valuable tool to optimize device configurations for a desired gravitational environment, probe the offload achieved for motions recorded outside of our test suite, and inform future design improvements.

L B Nilsson↗

NASA NTRS2023

Modeling and Simulation of The Angel Upper Limb Offload Device: Branching into New Methods

L B Nilsson↗

NASA NTRS2022

Human Stability While Exercising on a VIS Device in Zero Gravity

BACKGROUND: A Vibration Isolation and Stabilization (VIS) system is being designed for use with the European Enhanced Exploration Exercise Device (E4D) [1]. The exercise bar is attached to cables that extend and retract through openings in the E4D platform, which the subject stands on while exercising. Since the E4D is mounted on a moving VIS device, the whole system moves under the subject’s feet. While tension in the cables does help stabilize a crew member in 0g by bracing him or her against the moving platform, flexible cables do not offer full support against falling. This raises the question of whether various exercises that are successfully performed in 1g on a stationary device can be performed without losing balance in 0g on a moving device. Quantifying stability conditions and establishing stability requirements for exercise countermeasure systems is a long-standing challenge and this work helped to inform this specific need for integrated E4D/VIS flight project development. METHODS AND RESULTS: A simplified stability analysis can be attempted based on platform accelerations generated by the VIS device simulation. In this type of analysis, the subject is conceived as standing on the platform in 0g while being held down to it by the tension in the cables. If the sideways acceleration of the platform is such that the cables cannot generate a sufficient moment relative to, e.g., the heels or the toes of the subject to overcome the tipping moment from the inertial forces on the accelerated subject’s body, the subject becomes unstable. This approach, which we refer to as the ‘static’ approximation, indicated failure of all the exercises that were considered in the comprehensive VIS analysis of the E4D. It was realized, however, that platform accelerations are not externally imposed but are themselves induced by the motion of the subject’s body during exercise, and a model calculation confirmed that this drastically altered the tipping moment on the subject, with the potential to even switch the direction in which the body would tip over. This made it imperative to consider in a coupled manner both the motion of the exercising subject’s body and the induced VIS platform motion while considering stability. The coupled dynamics requirement was met by the VIS simulation incorporating time-dependent human mass properties atop the platform and driven by the inertial forces from the prescribed subject motion relative to the platform based on motion-capture recorded human trajectories in 1g on a stationary E4D [2]. To analyze simulation results, a stability criterion was also needed. We do not know how to account for the human ‘control system’ that would take visual and vestibular cues as inputs as the platform moves in 0g. We thus chose to follow an approach we had previously used to analyze the dynamic feasibility of performing a task in lunar gravity along the human body trajectory recorded in 1g [3]. In this approach, one analyzes the center of pressure (COP) between the shoes and the ground (or platform) and checks if the COP remains within the convex hull of the footprints on the ground (or platform), commonly referred to as base of support (BOS). Since pressure is vertical and, in the absence of foot restraints, positive, the COP going outside the BOS indicates that the trajectory recorded in 1g is not dynamically feasible in microgravity and/or on the moving platform of the device. The outcome of the COP-based analysis was that some of the key exercises, especially the deadlift and the back squat exercises, were found to be dynamically feasible for at least some number of the exercise cycles, this number increasing with the cable tension. While this type of stability analysis does not account for the likely alteration of the exercise trajectory from its 1g form in space, it does show that there exist at least some realistic trajectories that pass the dynamic feasibility criterion. This adds confidence that, with further adjustment by the subject of the exercise form in 0g on a moving device, a number of exercises can be performed without losing balance.

D Frenkel↗

NASA NTRS2022

Accuracy of Center of Pressure Determination Via Motion Capture

This study was conducted to support stability assessment for: (1) Tasks in lunar gravity (2) Exercises on a Vibration Isolation and Stabilization (VIS) system in microgravity. Stability assessment 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.

C A Bell↗

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 NTRSDate not supplied

Adjusting a Full Body Model to Mitigate Inverse Kinematics Artifacts in Opensim

BACKGROUND: In support of Vibration Isolation and Stabilization (VIS) system development for Human Health Countermeasures (HHC) exercise systems in space, such as the European Enhanced Exploration Exercise Device (E4D) [1], dynamic quantities required to model the response of a proposed VIS while considering the effect of VIS motion on the forces between the human and VIS platform were obtained using motion capture data [2]. On occasion, large-amplitude oscillatory spikes were found in the subject’s linear and angular momentum derivatives, affecting analyses that depend on forces and moments derived from motion capture. The purpose of this investigation was to identify causes of these artifacts and techniques for their resolution. METHODS AND RESULTS: To obtain the required human dynamic quantities to drive the VIS simulation, motion capture data was collected containing recorded trajectories of passive retroreflective markers on body landmarks of an exercising subject. Since the full body Rajagopal model [3] was originally used to enhance gait analysis, upper body joints did not require large Ranges of Motion (ROM). We thus modified the Rajagopal model [4, 5] to allow it to be used for upper body intensive exercises like those common to the E4D. OpenSim Inverse Kinematics (IK) [6] was performed using these scaled subject models to generate the joint angles throughout the exercise while minimizing marker error. At times, the arms were observed to ‘snap’ from one configuration to another, causing spike artifacts. Following IK, a custom OpenSim plugin [7] was used to determine the required dynamic quantities including the rates of change of the linear and angular momenta of the human. Since motion capture is recorded at a larger time step than required by the VIS simulation, the human center of mass location was fit with splines and a second derivative taken to obtain the momentum derivative, allowing the VIS simulation to maintain conservation of momentum when appropriate. In a few cases during this stage, artifacts much larger than the expected noise of the second derivatives were introduced. Investigation of cases containing artifacts revealed several modifications that could be made to the OpenSim model to improve IK results. Since OpenSim models use Euler angles and rotation sequences, ‘gimbal lock’ would be encountered in the arms when raised 90 degrees to the side (e.g., T-pose, some hang clean exercise, etc.). This was resolved by reorienting the horizontal axes at the shoulder joint by 45 degrees, placing ‘gimbal lock’ outside common arm ROM, with the arm ROMs adjusted following this change. Elbow and wrist ROMs could also be adjusted to allow realistic motion while at the same time limiting the likelihood of unrealistic orientations. On occasion, the arms flipped backwards when raised above the head. This was prevented by using medial elbow markers in scaling and IK. When medial markers were not available, the acromial joint location in the unscaled model was shifted before model scaling to better align the arm with available markers. Lastly, artifacts which became apparent after taking the second derivatives of spline-fit data were found to occur in cases when the pelvis rotation limit prevented the full range of motion of an exercise. These issues were resolved by unclamping the pelvis rotation limit. Through this investigation, an understanding of conditions leading to IK artifacts was acquired allowing the automation of artifact detection. These artifact detection and mitigation techniques can be applied toward modeling of upper body motions in aerospace and other fields for improved IK results.

C A Bell↗

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 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

Next Generation Exercise Device (NGED): Advancing Exercise Capabilities for Future Space Missions Through Biomechanical Modeling

BACKGROUND As space exploration extends to long-duration missions on the Moon and Mars, maintaining astronaut health and fitness becomes increasingly critical. The Next Generation Exercise Device (NGED), developed and tested by the HumanWorks Lab in NASA Johnson Space Center's (JSC) Software, Robotics, and Simulation Division, aims to address this challenge through innovative approaches. This study presents the development and evaluation of an NGED system, focusing on its adaptability to various mission scenarios, including prospective use in a Lunar Pressurized Rover (LPR). Central to this project is the application of biomechanical modeling to optimize exercise efficacy and safety in microgravity and partial gravity environments. The project is a collaborative effort with the Human Health and Performance group at Johnson Space Center, ensuring a comprehensive approach to astronaut well-being that integrates biomechanical principles with practical exercise solutions. The NGED represents the next generation of exercise capabilities for missions in space, on the Moon and Mars, with a specific focus on applications such as the LPR. METHODS AND RESULTS Data collection for NGED development was conducted with two motor-driven Beyond Power Voltra I [1] systems and a custom test structure to allow placement of the cable-based devices on the ground, at shoulder height, and overhead. The collection was performed in JSC’s Prototype Immersive Technology (PIT) Lab, utilizing an OptiTrack motion capture system and AMTI force platform, to enable detailed biomechanical analysis via OpenSim [2,3]. Motion capture data were collected for three subjects representing different body types and statures. The marker set used was an enhanced version of the full-body Plug-in Gait marker set [4], with additional markers strategically placed for the primary objective of informing exercise volume requirements. Subjects performed a series of 17 exercises, carefully selected to engage various muscle groups, including novel spaceflight exercises such as skiing (ergometer style), lateral pulldowns, wood chops, triceps extensions, and flies, with load variations ranging from 10 to 90 pounds to maintain kinematic form. This comprehensive approach allowed for a thorough evaluation of the NGED's performance across a wide range of motions and loads. The biomechanical modeling and analysis were conducted using a modified OpenSim Full Body Rajagopal Model [4,5] and also scaled to the maximum and minimum anthropometry provided in NASA-STD-3001 [6]. Volumetric convex hulls were generated based on model marker trajectories and aggregated into geometric assemblies. These can be placed in models of vehicle designs to assess fit to protect for exercise as well as to adapt NGED exercise to fit available space. Preliminary findings from the collection indicate that the NGED prototype demonstrates significant adaptability across varying user anthropometrics and exercise types. The device showed consistent performance in load-bearing exercises, with subjects able to perform exercises effectively while maintaining proper biomechanical form. CONCLUSION NGED represents a forward-looking advancement in exercise capabilities for future space missions. In the future, this system can be used to capture valuable metrics (e.g., isometric mid-thigh pull for force output measurements, assessments of postural muscle strength, overall isometric strength). Its versatility in accommodating various exercises and user physiques, coupled with the ability to provide targeted biomechanical loading, makes it a promising approach for maintaining astronaut health during long-duration missions to the Moon and Mars. Future work will focus on refining the NGED based on initial biomechanical findings, leveraging the detailed insights provided by motion capture and analysis techniques. Particular emphasis will be placed on optimizing its use within the confined spaces of a LPR and other space habitats. This work contributes significantly to NASA's goals of supporting human health and performance in deep space exploration, paving the way for sustainable long-term presence beyond Low Earth Orbit through advanced, biomechanically-informed exercise solutions.

C Wang↗

NASA NTRSDate not supplied

Developing Methods for Exercise System Kinematics Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as openCV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: Busy and visually cluttered background Low-textured tracking object with relatively small motions Occlusions and motion by human subject and loose, floating objects Limited number of video cameras with no fixed global references Limited ability to add tags, markers, or visual references to the tracking object Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L B Nilsson↗

NASA NTRSDate not supplied

Next Generation Exercise Device (NGED): Advancing Exercise Capabilities for Future Space Missions Through Biomechanical Modeling

Background: As space exploration extends to long-duration missions on the Moon and Mars, maintaining astronaut health and fitness becomes increasingly critical. The Next Generation Exercise Device (NGED), developed and tested by the HumanWorks Lab at NASA Johnson Space Center (JSC), aims to address this challenge through innovative approaches. Objective: Development and evaluation of a NGED system, focusing on its adaptability to various Moon to Mars mission scenarios, including prospective use in a Lunar Pressurized Rover (LPR). To help inform vehicle and system requirements, an exercise volumetric assessment was performed via data collection and biomechanical modeling.

C Wang↗