Guinea Fowl Force Predictions During Perturbated Gaits
-
Upload
christopher-whitney -
Category
Documents
-
view
13 -
download
0
Transcript of Guinea Fowl Force Predictions During Perturbated Gaits
Guinea Fowl Force Predictions During Perturbed Gaits
Early Results
Christopher D. Whitney [email protected] modified: August 14, 2016
Play video
Intro to Data
● Data comes from in vivo measurements conducted by Dr. Daley○ Two individual fowls (blue and yellow)○ Three trials (5cm, 7cm and level)○ Two muscles recorded for each trail (LG, DF)
● Collected using ○ Sonomicrometry for the lengths ○ Tendon buckles for the forces○ Implanted EMG for the activation
Model Description Using the winding filament paradigm of muscle contraction, the following vibrational model was derived by Petak and colleagues [3]. The below schematic is the latest version of the wfm model v9.
Model Description: How it works
● Second-order differential equations are used to describe movement over time ● Displacement vectors (cm) and velocity vectors (cm/s) are found through
double integration of acceleration of the mass of the pulley● Forces are described using the following equations
○ K*delta_x (Springs)○ C*delta_v (Dashpots/Dampers)○ Where K is a spring stiffness constant (N/cm), C is a damping rate constant (Ns/cm) ○ Delta_x is the displacement in position○ Delta_v is the displacement in velocity
Methods
Methods
1. Transform raw EMG percent of activation a. High-pass Butterworth filterb. Rectificatedc. Low-pass Butterworth filterd. Normalized to MVC
2. Activation time delay (23ms) incorporated into the model3. General FL and FV incorporated into the model4. Unknown physiological values estimated (i.e Lo, Po, Vo)5. Force outputs multiplied by cos of the pennation angle6. Hand tuning based on “after-flight” component analysis7. Free-parameters optimized to the measured forces 8. Accuracy measured using R^2
Activation time-delay incorporation
Fce = Po *[Fl(l)*Fv(v)*Act(i-d)] Where i is the current data point, d is the activation delay in time steps, is the peak isometric force, l is muscle fascicle length, v is the velocity of the contractile element, Fl is the force-length relationship which is a function of l, the Fv is the force-velocity relationship which is a function of v, and Act which is percentage of muscle activation between 0-.6.
General FL and FV
Where Lo is optimal length, Vo is optimal velocity, and where a,b,c and Afl are shape-factors.
Note that this force-velocity relationship uses three shape-factor which could be minized by using a different set of equations.
“After-flight” Component AnalysisEach position, velocity, acceleration and force components of the current run is visually examined to make sure it is performing properly.
Figure 1: High-level flowchart of the optimization process where the free parameters are tuned to minimize 1-R Squared. The EMG Normalizer is the transformation function for the raw EMG signal
Optimization Process
Input Parameters
Early Results
Results
The these R^2 results come from tuning the free parameters on the 5 cm obstacle.
(R2 0.26-0.51) Results from a complex two-element Hill model published in 2013 [2].
Complex two-element Hill model
(Lee, S.S 2013)
Discussion
● Is this a science of curve fitting?● And is wfm truly better than a
two-element Hill? ● And does this model truly describe
the winding filament hypothesis?
References
1. Daley, M., Voloshina, A. and Biewener, A. 2009. The role of intrinsic muscle mechanics in the neuromuscular control of stable running in the guinea fowl. The Journal of Physiology. 587, 11 (2009), 2693–2707.
2. Lee, S.S. et al. 2013. Accuracy of gastrocnemius muscles forces in walking and running goats predicted by one-element and two-element Hill-type models. Journal of biomechanics. 46, 13 (Sep. 2013), 2288–95.
3. Petak , J.L. PERFORMANCE TESTING OF A MUSCULOSKELETAL MODEL CONTROLLER FOR A ROBOTIC PROSTHESIS.