1. Kamran Shamaei Prof. Gregory S. Sawicki Prof. Aaron M. Dollar
Subject-Specific Predictive Models of Lower-limb Joint Quasi-Stiffness and Applications in Exoskeleton Design
Kamran Shamaei
Prof. Gregory S. Sawicki
Prof. Aaron M. Dollar

2. Scope and Application: Prostheses and Orthoses
C-Leg from Ottobock
Underactuated Exosksleton from MIT (fig. from scientificamerican.com)
HULC from UC Berkeley
Compliant SC Orthosis from Yale
Ankle-Foot Prosthesis
from U. Michigan
(fig. from PLoS One)
Ankle-Foot Prosthesis
from MIT (fig. from MIT news)

3. Challenge: How to size the components of these devices for a specific
user size and gait speed?

4. a randomized sample population
Common Approach: Use average values for joint stiffnesses obtained from gait lab data for
a randomized sample population

5. Drawbacks
Sample population body stature is not necessarily representative of the user’s
Costly and time-consuming
Design centers usually do not have a gait lab

6. Drawbacks
Sample population body stature is not necessarily representative of the user’s
Costly and time-consuming
Design centers usually do not have a gait lab

7. Drawbacks
Sample population body stature is not necessarily representative of the user’s
Costly and time-consuming
Design centers usually do not have a gait lab

8. Alternative Framework

9. Design Example: A Quasi-Passive Knee Exoskeleton
Shamaei K, Napolitano P., and Dollar A. (2013) A Quasi-Passive Compliant Stance Control Knee-Ankle-Foot Orthosis, ICORR, Seattle, Washington, USA.

10. Linear Moment-Angle Behavior of
the Knee in Stance
Design: Compliantly support the knee by an exoskeletal spring
Shamaei et al., PLoS One 2013a
Shamaei et al., ICORR 2011

11. Yale Quasi-Passive Stance Control Orthosis
Shamaei K, Napolitano P., and Dollar A. (2013) A Quasi-Passive Compliant Stance Control Knee-Ankle-Foot Orthosis, ICORR, Seattle, Washington, USA.

12. Challenge: How to size the spring for a specific user and gait speed?
K (Nm/rad)~ [80 , 800]
Shamaei et al. (2013) PLoS One
Challenge: How to size the spring for a specific user and gait speed?

13. Linear Moment-Angle Behavior of the Knee in Stance, a Closer Look
K is:
User-specific
Gait-specific
(Shamaei, ICORR 2011) K
Tune the stiffness of the device according to the body size and gait speed Ke Kf

14. measurable parameters
Framework : Mathematical/Statistical models that estimate knee quasi-stiffnesses using a set of
measurable parameters
Gait Speed
Weight
Height
Joint Excursion Kf Ke K

15. Start with Inverse Dynamics Analysis
MKnee
MAnkle ,FAnkle
GRF, GRM

16. Linking to Gait and Body Parameters
MKnee
MKnee~ f(W,V,H) Ke
MKnee~ Kiθi Kf
Ki ~ f(WVH/θi -WV/θi - WH/θi - W/θi - 1/θi - WVH- WH)

17. Statistical Analysis Regression on Experimental Data
Ki ~ f(WVH/θi, WV/θi, WH/θi,
W/θi, 1/θi, WVH, WH)
Regression on Experimental Data

18. Springy Behavior at the Optimal Gait Speed
Support the knee using a spring

19. Adjust the Stiffness at Higher Gait Speeds
Assist the knee using a combination of
a spring and an active component

20. Comparison with Models that Use Average Values
From: Shamaei K, Sawicki G, and Dollar A. (2013) Estimation of Quasi-Stiffness of the Human Knee in the Stance Phase of Walking, PLOS ONE.

21. Moment-Angle Performance of Hip
From: Shamaei K, Sawicki G, and Dollar A. Estimation of Quasi-Stiffness of the Human Hip in the Stance Phase of Walking, in review.

22. Moment-Angle Performance of Ankle
From: Shamaei K, Sawicki G, and Dollar A. (2013) Estimation of Quasi-Stiffness and Propulsive Work of the Human Ankle in the Stance Phase of Walking, PLOS ONE.

23. Similar Approach for Hip and Ankle
MHip
Quasi-Stiffness
Mknee , FKnee
MAnkle ,FAnkle
Quasi-Stiffness
Work
GRF, GRM

24. Models for Ankle Quasi-Stiffness and Work
From: Shamaei K, Sawicki G, and Dollar A. (2013) Estimation of Quasi-Stiffness and Propulsive Work of the Human Ankle in the Stance Phase of Walking, PLOS ONE.

25. Models for Hip Quasi-Stiffness
From: Shamaei K, Sawicki G, and Dollar A. Estimation of Quasi-Stiffness of the Human Hip in the Stance Phase of Walking, in review.

26. Conclusions
Models accurately predict the stiffnesses compared with average values
Utilize these equations in design of exoskeletons and prostheses
Ideally adjust the stiffness of the device according to the gait speed

27. Conclusions
Models accurately predict the stiffnesses compared with average values
Utilize these equations in design of exoskeletons and prostheses
Ideally adjust the stiffness of the device according to the gait speed

28. Conclusions
Models accurately predict the stiffnesses compared with average values
Utilize these equations in design of exoskeletons and prostheses
Ideally adjust the stiffness of the device according to the gait speed

29. Thanks for Your Attention
Experimental data:
26 subjects
216 gait cycles
Gait speed (m/s): [0.75 , 2.63]
Height (m): [1.45 , 1.86]
Weight (kg): [57.7 , 94.0]
Data granted by: Prof. DeVita, Prof. Sawicki, and Prof. Frigo
Funding: US Defense Medical Research and Development Program, grant #W81XWH