ALBERT

Description: Historically, spacesuit mobility has been characterized by directly measuring both range of motion and joint torque of individual anatomic joints. The work detailed herein aims to improve on this method, which is often prone to uncertainly, lack of repeatability, and a general lack of applicability to real-world functional tasks. Specifically, the goal of this work is to characterize suited mobility performance by directly measuring the metabolic performance of the occupant. Pilot testing was conducted in 2013, employing three subjects performing a range of functional tasks in two different suits prototypes, the Mark III and Z-1. Cursory analysis of the results shows the approach has merit, with consistent performance trends toward one suit over the other. Forward work includes the need to look at more subjects, a refined task set, and another suit in a different mass/mobility regime to validate the approach.

Description: A challenge in understanding human performance as a function of gravity is determining which tasks to research. Initial studies began with treadmill walking, which was easy to quantify and control. However, with the development of pressurized rovers, it is less important to optimize human performance for ambulation as pressurized rovers will likely perform gross translation for them. Future crews are likely to spend much of their extravehicular activity (EVA) performing geology, construction,a nd maintenance type tasks. With these types of tasks, people have different performance strategies, and it is often difficult to quantify the task and measure steady-state metabolic rates or perform biomechanical analysis. For many of these types of tasks, subjective feedback may be the only data that can be collected. However, subjective data may not fully support a rigorous scientific comparison of human performance across different gravity levels and suit factors. NASA would benefit from having a wide variety of quantifiable tasks that allow human performance comparison across different conditions. In order to determine which tasks will effectively support scientific studies, many different tasks and data analysis techniques will need to be employed. Many of these tasks and techniques will not be effective, but some will produce quantifiable results that are sensitive enough to show performance differences. One of the primary concerns related to EVA performance is metabolic rate. The higher the metabolic rate, the faster the astronaut will exhaust consumables. The focus of this poster will be on how different tasks affect metabolic rate across different gravity levels.

Description: The Risk of Decompression Sickness (DCS) is identified by the NASA Human Research Program (HRP) as a recognized risk to human health and performance in space, as defined in the HRP Program Requirements Document (PRD). This Evidence Report provides a summary of the evidence that has been used to identify and characterize this risk. Given that tissue inert gas partial pressure is often greater than ambient pressure during phases of a mission, primarily during extravehicular activity (EVA), there is a possibility that decompression sickness may occur.

Description: In general metabolic rates tend to be higher in NBL than in flight: a) Restraint method dependant; b) Significant differences between the NBL and flight for BRT and APFR (buoyancy effects). c) No significant difference between NBL and flight for free float and SRMS/SSRMS operations. The total metabolic energy expenditure for a given task and for the EVA as a whole are similar between NBL and flight: a) NBL metabolic rates are higher, but training EVAs are constrained to 5 1/2 hours. b) Flight metabolic rates are lower, but the EVAs are typically an hour or more longer in duration. NBL metabolic rates provide a useful operational tool for flight planning. Quantifying differences and similarities between training and flight improves knowledge for preparation of safe and efficient EVAs.

Description: Injuries to the hands are common among astronauts who train for extravehicular activity (EVA). Many of these injuries refer to the gloves worn during EVA as the root cause. While pressurized, the bladder and outer material of these gloves restrict movement and create pressure points while performing tasks, sometimes resulting in pain, muscle fatigue, abrasions, and occasionally a more severe injury, onycholysis (fingernail delamination). The most common injury causes are glove contact (pressure point/rubbing), ill-fitting gloves, and/or performing EVA tasks in pressurized gloves. A brief review of the Lifetime Surveillance of Astronaut Health's injury database reveals over 57% of the total injuries to the upper extremities during EVA training occurred either to the metacarpophalangeal (MCP) joint, fingernail, or the fingertip. Twenty-five of these injuries resulted in a diagnosis of onycholysis

Description: The Hypobaric Decompression Sickness (DCS) Treatment Model links a decrease in computed bubble volume from increased pressure (DeltaP), increased oxygen (O2) partial pressure, and passage of time during treatment to the probability of symptom resolution [P(symptom resolution)]. The decrease in offending volume is realized in 2 stages: a) during compression via Boyle's Law and b) during subsequent dissolution of the gas phase via the O2 window. We established an empirical model for the P(symptom resolution) while accounting for multiple symptoms within subjects. The data consisted of 154 cases of hypobaric DCS symptoms along with ancillary information from tests on 56 men and 18 women. Our best estimated model is P(symptom resolution) = 1 / (1+exp(-(ln(Delta P) - 1.510 + 0.795AMB - 0.00308Ts) / 0.478)), where (DeltaP) is pressure difference (psid), AMB = 1 if ambulation took place during part of the altitude exposure, otherwise AMB = 0; and where Ts is the elapsed time in mins from start of the altitude exposure to recognition of a DCS symptom. To apply this model in future scenarios, values of DeltaP as inputs to the model would be calculated from the Tissue Bubble Dynamics Model based on the effective treatment pressure: (DeltaP) = P2 - P1 | = P1V1/V2 - P1, where V1 is the computed volume of a spherical bubble in a unit volume of tissue at low pressure P1 and V2 is computed volume after a change to a higher pressure P2. If 100% ground level O2 (GLO) was breathed in place of air, then V2 continues to decrease through time at P2 at a faster rate. This calculated value of (DeltaP then represents the effective treatment pressure at any point in time. Simulation of a "pain-only" symptom at 203 min into an ambulatory extravehicular activity (EVA) at 4.3 psia on Mars resulted in a P(symptom resolution) of 0.49 (0.36 to 0.62 95% confidence intervals) on immediate return to 8.2 psia in the Multi-Mission Space Exploration Vehicle. The P(symptom resolution) increased to near certainty (0.99) after 2 hrs of GLO at 8.2 psia or with less certainty on immediate pressurization to 14.7 psia [0.90 (0.83 - 0.95)]. Given the low probability of DCS during EVA and the prompt treatment of a symptom with guidance from the model, it is likely that the symptom and gas phase will resolve with minimum resources and minimal impact on astronaut health, safety, and productivity.

Description: The Apollo lunar EVA experience revealed challenges with suit stability and control-likely a combination of mass, mobility, and center of gravity (CG) factors. The EVA Physiology, Systems and Performence (EPSP) Project is systematically working with other NASA projects, labs, and facilities to lead a series of studies to understand the role of suit mass, weight, CG, and other parameters on astronaut performance in partial gravity environments.

Description: Introduction: The overarching objective of the Integrated Suit Test (IST) series is to evaluate suited human performance using reduced-gravity analogs and learn what aspects of an EVA suit system affect human performance. For this objective to be successfully achieved, the testing methodology should be valid and reproducible, and the partial-gravity simulations must be as accurate and realistic as possible. Objectives: To highlight some of the key lessons learned about partial-gravity analogs and testing methodology, and to suggest considerations for optimizing the effectiveness and quality of results of future tests. Methods: Performance testing of suited and unsuited subjects was undertaken in different reduced-gravity analogs including the Space Vehicle Mockup Facility s Partial Gravity Simulator (POGO), parabolic flight on the C-9 aircraft, underwater environments including NASA s Extreme Environment Mission Operations (NEEMO) and the Neutral Buoyancy Lab (NBL), and in field analogs including Desert Research and Technology Studies (RATS), the Haughton Mars Project (HMP), and the JSC Rock Pile. Subjects performed level walking, incline/decline walking, running, shoveling, picking up and transferring rocks, kneeling/standing, and task boards. Lessons Learned Analogs: No single analog will properly simulate all aspects of the true partial-gravity environment. The POGO is an ideal environment from the standpoint that there are no time limits or significant volumetric constraints, but it does have several limitations. It allows only 2 translational degrees of freedom (DOF) and applies true partial-gravity offload only through the subject s center of gravity (CG). Also, when a subject is doing non-stationary tasks, significant overhead inertia from the lift column seems to have a negative impact on performance. Parabolic flight allows full translational and rotational DOF and applies offload to all parts of the body, but the simulation lasts less than 30 seconds. When this is coupled with the volumetric constraints of the plane, both task selection and data collection options are significantly limited. The underwater environments also allow all 6 DOF and allow off-loading to be applied throughout the body, but the data collection capabilities are limited to little more than subjective ratings. In addition, water drag negatively affects performance of tasks requiring dynamic motion. Field analogs provide the ability to simulate lunar terrain and more realistic mission-like objectives, but all of them operate at 1-g, so suited human performance testing generally must utilize a reduced-mass or "mockup" suit, depending on study objectives. In general, the ground-based overhead-suspension partial-gravity analogs like POGO allow the most diverse data collection methods possible while still simulating partial gravity. However, as currently designed, the POGO has significant limitations. Design of the Active Response Gravity Offload System (ARGOS) has begun and is focusing on adding full x,y,z translational DOF, improved offload accuracy, increased lift capacity, and active control of the x and y axes to minimize offload system inertia. Additionally, a new gimbal is being designed to reduce mass and inertia and to be able to work with different suits, as the current gimbal only supports suited testing with the Mark III Technology Demonstrator Suit (MKIII).

Description: The presentation slides include: Moving Past Apollo, Testing in Analog Environments, NEEMO/NBL CG (center of gravity) Studies, Center of Gravity Test Design and Methods, CG Suited Locations and Results, CG Individual Considerations, CG Shirt-Sleeve Locations and Results.

Description: The purpose of this report is to document preliminary, predicted, life sciences implications of expected operational concepts for lunar surface extravehicular activity (EVA). Algorithms developed through simulation and testing in lunar analog environments were used to predict crew metabolic rates and ground reaction forces experienced during lunar EVA. Subsequently, the total metabolic energy consumption, the daily bone load stimulus, total oxygen needed, and other variables were calculated and provided to Human Research Program and Exploration Systems Mission Directorate stakeholders. To provide context to the modeling, the report includes an overview of some scenarios that have been considered. Concise descriptions of the analog testing and development of the algorithms are also provided. This document may be updated to remain current with evolving lunar or other planetary surface operations, assumptions and concepts, and to provide additional data and analyses collected during the ongoing analog research program.