William K Thompson | Search NASA

NASA NTRS2020

Cross-Cutting Computational Modeling Project: Exploration Medical Station Analysis

Astronauts will be away from Earth-based medical care for long periods during future exploration missions. Thus, it will be necessary for the astronauts to perform various medical tasks to monitor and maintain their health in the microgravity environment of space. Performance of these tasks will be constrained due to the limited volume available to perform the task, the absence of gravity and the limited resources and capabilities available in the medical work area. It is therefore necessary to evaluate exploration medical workstation designs for how well the designs will support crew performance of medical tasks. This evaluation featured two trained medical caregivers (99th percentile male, 26th percentile female) performing emergent care procedures (alone and in tandem) on a medical manikin. The procedures came from the The procedures came from the International Space Station Medical Checklist, and they are designed for spaceflight. The objectives of the evaluation included determining the operational volume required to perform the tasks, examining the effect of constraining the operational volume with partitions, determining candidate locations for foot restraints and equipment placements and determining the effect of single vs. dual caregiver on the operational volume.A marker-based motion capture system collected the motion data, which enabled computation of operational volumes and foot placement maps using custom Python code. Additional data collected included heart rate, time to perform the procedures, and feedback from the caregivers in the form of the NASA Task Load Index (TLX), the US Government System Usability Survey, and an open-ended questionnaire.

Christopher A Gallo↗

NASA NTRS2018

Estimation of Lower-Body Kinetics from Loading Profile and Kinematics Alone, Without Measured Ground Reaction Forces

Biomechanical models of human motion can estimate kinetic outcomes, such as joint moments, joint forces and muscle forces. Typically, one performs an inverse dynamics (ID) analysis to compute joint moments from joint angles and measured external forces. Sometimes it is impractical to measure ground reaction forces and moments (GRF&M). We devised an empirical method for performing ID analysis of resistance exercises without measured GRF&M. The method solves the multibody dynamics equations of motion with four key assumptions about the GRF&M that reduce the number of unknowns. The assumptions are 1) negligible ground reaction moments, 2) fixed lateral/medial location of the center of pressure (COP), 3) equal fore/aft location of the COP between the feet, and 4) constant angle of the GRF vector relative to the vertical axis in the frontal plane. We used evaluation trials from a spaceflight countermeasure resistance training device to test this approach. Four participants performed squat and deadlift exercises at various loads. We compared results from traditional ID analysis to results without measured GRF&M using our method. We found that joint moment trajectories in the sagittal plane were qualitatively similar in shape between the two methods, and the amount of root mean squared error (RMSE), measured by difference in joint moment impulse, was typically under 10 percent. Non-sagittal joint moment trajectories, which are much lower in overall magnitude, were not qualitatively similar in shape between the two methods. Non-sagittal moments displayed much higher RMSE, with typical values well over 50 percent. These findings were further supported by validation metrics (Sprague and Geers' P and M metrics, Pearson's r correlation coefficient). Based on these findings, we concluded that useful kinetic results are obtained from ID analysis of squat and deadlift exercises, even when GRF&M are not measured, as long as the outcomes of interest lie in the sagittal plane.

computational modeling↗