This abstract describes development work performed on the NASA Digital Astronaut Project Muscle Model. Muscle atrophy is a known physiological response to exposure to a low gravity environment. The DAP muscle model computationally predicts the change in muscle structure and function vs. time in a reduced gravity environment. The spaceflight muscle model can then be used in biomechanical models of exercise countermeasures and spaceflight tasks to: 1) develop site specific bone loading input to the DAP bone adaptation model over the course of a mission; 2) predict astronaut performance of spaceflight tasks; 3) inform effectiveness of new exercise countermeasures concepts

Humphreys, B. T.

Lewandowski, Beth E.

Mulugeta, L.

Pennline, James A.

Ploutz-Snyder, L. L.

Ryder, J. W.

Thompson, W. K.

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DEVELOPMENT OF THE NASA DIGITAL ASTRONAUT PROJECT MUSCLE MODEL
B.E. Lewandowski1, J.A. Pennline1, W.K. Thompson1, B.T. Humphreys2, J.W. Ryder3, L.L. Ploutz-Snyder3, L. Mulugeta3
1NASA Glenn Research Center, 21000 Brookpark Rd., Cleveland, OH 44135 
2ZIN Technologies, 6745 Engle Road, Airport Executive Park, Cleveland, OH 44130
3Universities Space Research Assoc., Div. of Space Life Sciences, 3600 Bay Area Blvd., Houston, TX 77058
ACKNOWLEDGEMENTS REFERENCES
UNCERTAINTY, SENSITIVITY AND VALIDATION ANALYSES
PARTNERS
BACKGROUND
NASA’s Digital Astronaut Project (DAP) Vision
The Digital Astronaut Project implements well-vetted 
computational models to predict and assess spaceflight health 
and performance risks, and enhance countermeasure 
development
HRP Risks/Gaps Addressed by This Effort
Risk of Muscle Atrophy: Impaired performance due to reduced 
muscle mass, strength and endurance
M2 - Characterize in-fight and post-flight muscle performance
M7 - Develop the most efficient exercise program for the 
maintenance of muscle fitness
M24 - Characterize the time course of changes in muscle 
protein turnover, muscle mass and function during long 
duration space flight
National Aeronautics and 
Space Administration
OPERATIONAL CONCEPT
[1]   S. R. Hamner, A. Seth, and S. L. Delp, “Muscle contributions to propulsion and support during running,” J. Biomech., vol. 43, no. 14, pp. 2709–2716, 2010.
[2] D. G. Thelen and F. C. Anderson, “Using computed muscle control to generate forward dynamic simulations of human walking from experimental data.,” J. Biomech., vol. 39, no. 6, pp. 1107–15, Jan. 2006.
[3] D. G. Thelen, F. C. Anderson, and S. L. Delp, “Generating dynamic simulations of movement using computed muscle control,” J. Biomech., vol. 36, no. 3, pp. 321–328, Mar. 2003.
[4] E. M. Arnold, S. R. Ward, R. L. Lieber, and S. L. Delp, “A model of the lower limb for analysis of human movement.,” Ann. Biomed. Eng., vol. 38, no. 2, pp. 269–79, Feb. 2010.
[5] M. Millard, T. Uchida, A. Seth, and S. L. Delp, “Flexing computational muscle: modeling and simulation of musculotendon dynamics.,” J. Biomech. Eng., vol. 135, p. 021005, 2013.
[6] S. Trappe, D. Costill, P. Gallagher, A. Creer, J. R. Peters, H. Evans, D. a Riley, and R. H. Fitts, “Exercise in space: human skeletal muscle after 6 months aboard the International Space Station.,” J. Appl. Physiol., vol. 106, no. 4, pp. 
1159–68, Apr. 2009.
[7] S. W. Trappe, T. A. Trappe, G. A. Lee, and D. L. Costill, “Calf muscle strength in humans,” Int. J. Sports Med., vol. 22, pp. 186–191, 2001.
[8]   M. F. Bobbert and G. J. Van Ingen Schenau, “Isokinetic plantar flexion: Experimental results and model calculations,” J. Biomech., vol. 23, pp. 105–119, 1990.
[9] M. Y. Pang and M. K. Mak, “Influence of contraction type, speed, and joint angle on ankle muscle weakness in Parkinson’s disease: Implications for rehabilitation,” Arch. Phys. Med. Rehabil., vol. 93, pp. 2352–2359, 2012.
[10] R. Gopalakrishnan, K. O. Genc, A. J. Rice, S. M. C. Lee, H. J. Evans, C. C. Maender, H. Ilaslan, and P. R. Cavanagh, “Muscle Volume, Strength, Endurance, and Exercise Loads During 6-Month Missions in Space,” Aviat. Space. 
Environ. Med., vol. 81, no. 2, pp. 91–104, Feb. 2010.
[11] G. Antonutto, C. Capelli, M. Girardis, P. Zamparo, and P. E. di Prampero, “Effects of microgravity on maximal power of lower limbs during very short efforts in humans.,” J. Appl. Physiol., vol. 86, no. 1, pp. 85–92, Jan. 1999.
[12] E. Balsa-Canto and J. Banga, “AMIGO: A model identification toolbox based on global optimization and its applications in biosystems,” Comput. Appl. Biotechnol., vol. 11, no. 1, pp. 132–7, 2010. 
OpenSim plantar flexion model
Musculoskeletal Modeling Objectives
Use an integrated musculoskeletal modeling approach to 
support the bone remodeling model efforts and provide 
muscle performance prediction capabilities:
• Provide bone loading information from biomechanical models of 
exercise that incorporate muscles that reflect spaceflight atrophy
• Develop algorithms which equate mechanical stimulus from in-
flight exercise to muscle maintenance
• Predict the minimal amount of stimulus needed to maintain 
required performance levels
• Predict if the stimulus be achieved by performing in-flight exercise 
on the available exercise devices
• Predict task performance after a specified time in space
• Predict the minimum amount of muscle strength and power to 
perform a task
General information 
about active muscle 
groups
߬ே௘௧ ߬ ൌ ܨ݀
Individual muscle force 
comparison between 
and within exercises
Muscle length and power 
production predictions and 
comparison of muscle 
performance between and 
within exercises
߬ ൌ ܨሺ݈ǡ ݒሻ݀
Mechanical stimulus related to 
muscle function maintenance 
and predict changes in muscle 
performance due to 
spaceflight
߬ ൌ ܨሺ݈ǡ ݒǡ ߤ݃ሻ݀
Inform questions such as:
How does muscle performance differ between different exercise devices, types of exercises and exercise configurations?
Does the limited volume and power requirements affect the muscle forces generated during prescribed exercises?
Does that affect the ability of the countermeasure device to maintain muscle performance?
How does that affect the astronauts ability to perform required tasks?
A full representation of muscle attachment points will likely change the 
stress distribution in the cortical bone
Important for modeling the whole proximal femur rather than only the 
femoral neck and for modeling the periosteal surface as well as cortical 
bone
Incorporate decreases in muscle force due to spaceflight atrophy into 
bone loading predictions
• Use simplified exercise models to gain a sufficient 
understanding of the OpenSim modeling environment 
and to determine how to augment OpenSim in order to 
model spaceflight induced muscle atrophy 
Evaluate OpenSim’s
muscle calculation 
methods
Evaluate the 
mathematical 
structure of 
OpenSim’s
muscle model
Evaluate how the 
model parameters 
map to 
measureable, 
physiological 
quantities
Evaluate the 
sensitivity of the 
muscle model 
parameters
Evaluate 
OpenSim’s
calculation error
Evaluate how 
changes to the 
parameters affect 
muscle force 
calculations
Identify spaceflight data 
which maps to the 
muscle model 
parameters
Determine how to update 
muscle model parameters 
to reflect a certain amount 
of spaceflight time
Determine the source of the 
error and how to reduce it
• OpenSim models of exercises used to assess post-flight strength [1 – 5]
− Isometric and isokinetic plantar flexion exercises [6 – 9]
− Isometric and isokinetic knee flexion and extension exercises [10]
− Leg press exercise to obtain maximum explosive power [11]
• Kinematics input files specify joint angles and kinetics input files specify 
joint torques/ground reaction forces
• Muscle excitations obtained with a Computed Muscle Control analysis
• Muscle forces calculated with a forward dynamics analysis
• Analyses performed:
− Calculated joint torques/ground reaction forces compared to prescribed values to 
find calculation error
− Muscle parameters adjusted systematically to determine sensitivity
− Muscle parameters modified to reflect spaceflight data in order to quantitatively 
compare preflight and post-flight conditions
• Calculation error typically ranged from 1 – 10%, submaximal cases 
tended to be higher
− In some cases, calculation error is larger than the differences due to 
spaceflight and must be reduced for meaningful comparison of 1g to 
spaceflight conditions 
• Tendon slack length and optimal fiber length identified as the most 
sensitive model parameters
− Allows prioritization of parameters when addressing parameters for which 
data is lacking
• Post-flight predictions when changing only the maximum isometric 
force parameter was successful for isometric and low velocity 
isokinetic strength predictions, but not for high velocity isokinetic 
cases
− Spaceflight data suggests that a reduction in force cannot be explained by 
reduction in volume alone
− Neuromotor control, morphology, specific tension, stiffness properties, etc. 
may also be important 
− These preliminary results suggest that they need to be accounted for in the 
model
• Complete leg press analysis, with particular focus on 
error due to unknown kinematics
• Determine and develop strategies to minimize the 
main sources of calculation error in OpenSim
• Take further advantage of the OpenSim optimization 
methodologies and capabilities
• Complete sensitivity analysis with parameters that are 
constant across all muscles
• Develop ranges for muscle model parameters which 
reflect
− Uncertainty due to individuality
− Change due to spaceflight as a function of 
• Time in space
• Level of in-flight exercise performed
• Explore alternative optimization methods for fitting 
parameters to address [12]:
− The interdependency of the parameters
− The lack of quantitative data for all parameters
Support Advanced Exercise Countermeasures Project
Advance from prediction of joint torque to muscle force to muscle force as a function of muscle length and 
velocity to incorporation of muscular changes due to spaceflight
Support Bone Remodeling Modeling Efforts
Increase the fidelity of the input force to the FEM which provides bone strain input to the bone remodeling model
MUSCLE MODEL CONCEPT
DAP Muscle Model Concept
Version 1.0 (Target completion, 9/2016) model input includes time 
spent in space and qualitative level of exercise use (low, average, 
high)
The model uses spaceflight and Earth based analog data to 
perform a parameter fit for the OpenSim muscle model parameters
Model output is an OpenSim muscle model parameter set that 
reflects the state of the muscle after the specified amount of time 
in space and exercise use
Version 2.0 (Target completion, 9/2019) based upon two functions:
1) Muscle degradation vs. time in microgravity
2) Muscle generation/maintenance as a function of muscle 
contraction and stretch during the mission
MUSCLE MODEL COMPONENTS
ܨ் ൌ ܨெ଴ ൌ ሺܽ ௅݂ ௩݂ ൅ ௉݂ாሻ ן
FT = Tendon force vs strain
FM0 = Maximum isometric force
a = Neuromuscular activation
fL = Active force vs length curve
fv = Active force vs velocity curve
fPE = Passive force vs length curve
α = Pennation angle
Tendon Force - Muscle Force Equilibrium Equation
This work is funded by the NASA Human 
Research Program, managed by the NASA 
Johnson Space Center. Specifically, this work is 
part of the Digital Astronaut Project (DAP), which 
directly supports the Human Health and 
Countermeasures (HHC) Element. The DAP 
project is managed at the NASA Glenn 
Research Center (GRC) by DeVon W. Griffin, 
Ph.D., and Lealem Mulugeta of USRA Houston 
serves as the DAP Project Scientist.
Objectives
Methods
OpenSim knee 
flexion/extension model
Results
OpenSim leg press 
model
Future Work
Plantar flexion analysis results
Measured vs simulated comparisons of preflight and 
post-flight strength measurements
Knee flexion/extension analysis results
Measured vs simulated changes in muscle strength from preflight to post-flight
Isometric Isokinetic at 60°/s
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https://ntrs.nasa.gov/search.jsp?R=20150004110 2019-08-31T11:16:54+00:00Z


Development of the NASA Digital Astronaut Project Muscle Model

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