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

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)

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

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

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

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

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

Alternative Framework

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.

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

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.

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?

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

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

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

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)

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

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

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

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.

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.

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.

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

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.

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.

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

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

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

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-11-2-0054