WP11: Modelling and
simulation for NND
Thomas Geijtenbeek, Frans van der Helm
Delft University of Technology
Amsterdam – 23-24 February 2015
Status of the WP
• T11.1 Construction of a scalable mass
distribution model
– Literature study on sensitivity of scaling methods
– Process results from joint center calibration
Amsterdam – 23-24 February 2015
Status of the WP
• T11.2 Development of a personalized disease
specific skeletal model
– Functional calibration
• Find joint rotation centers and axes
• Scale segment lengths
• Scale segment weights
– MRI recordings
• Muscle volume – Physiological Cross-Sectional Area
– Muscle optimum length from cadaver studies & scaled
• Via points – muscle attachments
– Finally through Statistical State Model
Amsterdam – 23-24 February 2015
Constructing a scaled model
Functional joint center calibration
Scaled musculoskeletal models
Brussels – 6-7 May 2014
Status of the WP
• T11.3 Construction of a disease specific
muscle model
– Plan to include spasticity model from VUMC (Van
der Krogt et al.)
– Muscle constraints:
» Contractures: Passive constraints
» Aberrant reflexes: low threshold on muscle contraction
velocity reflex
Amsterdam – 23-24 February 2015
METHODS
Spastic controller: increased stretch
reflex (vdKrogt et al., 2015)
If:
Stretch velocity of muscle fibers > Threshold
Then: Spastic excitation ( t + Delay ) = Gain * stretch velocity
Afferent impulses
from spinal cord…
… lead to efferent impulses
causing contraction
Threshold: extracted from data
Delay: fixed to 30 ms
Gain: individually tuned (0-4)
Cerebral Palsy (CP) vs Typically Developing (TD)
vdKrogt et al. (2015)
1.5
Relative fiber force
RESULTS
Force-length curves - with optimal stiffness parameters
1
Active
Default passive
TD hamstrings
CP hamstrings
TD vasti
CP vasti
0.5
0
0.5
1
Relative fiber length
1.5
Status of the WP
• T11.4 Design of models driven by the dynamics of gait perturbations
– OpenSim model (available)
• Gait2392 model
– 23 DOF
– 92 musculotendon actuators representing 76 muscles
• To be adapted by available gait and morphological data
– Optimization toolbox (connected)
• Covariance matrix adaptation (CMA)
– Neural control signal, feedback parameters
– Unknown model parameters
– Predictive simulations (in progress)
• Optimization
– Simulate optimal neural control model in pathological state
» Mimick pathological gait
– Predict optimal neural control after therapeutic intervention
» Prediction of outcome after intervention and rehabilitation practice
– Use gait data + EMG for validation
Amsterdam – 23-24 February 2015
Predictive Simulations
• Find optimal gait pattern for any given
musculoskeletal model
• Use high-level optimization criteria
– Target speed
– Metabolic energy expenditure
• Method does not require motion capture data
– Can be used for validation
• Can incorporate neuromuscular deficiencies
Amsterdam – 23-24 February 2015
Adapt to Model Scaling
Amsterdam – 23-24 February 2015
The Optimization Process
Amsterdam – 23-24 February 2015
Adapt to Target Speed
Amsterdam – 23-24 February 2015
Find Optimized Muscle Attachments
Amsterdam – 23-24 February 2015