Research Interests

I combine experimental and computational biomechanics techniques with machine learning to improve human mobility. I am especially interested in non-surgical interventions for knee osteoarthritis, like gait modifications. I use musculoskeletal simulations to design these interventions, real-time biofeedback to deliver them to individuals with osteoarthritis, and quantitative MRI to evaluate the effects on tissue microstructure. I also develop open-source tools for biomechanical analysis using cell phone video cameras and wearable devices. These tools will allow us to measure and retrain movement at a scale that is orders of magnitude greater than what is currently feasible in a motion capture laboratory.

Degrees

B.S. in Mechanical Engineering, Baylor University, 2014
M.S. in Mechanical Engineering, Stanford University, 2016
Ph.D. in Mechanical Engineering, Stanford University, 2020

Honors and Awards

Clinical Biomechanics Award Finalist (ISB, Stockholm), 2021
3 Minute Thesis Competition Finalist (ASB, Atlanta), 2020
David Winter Young Investigator Award Finalist (ISB, Calgary), 2019
Clinical Biomechanics Award Finalist (ISB, Calgary), 2019
Young Investigator Award (OARSI World Congress, Toronto), 2019
De Luca Student Travel Award (WCB, Dublin), 2018
NSF Graduate Research Fellowship, 2015
Stanford Graduate Fellowship, 2014

Selected Publications

Boswell M.A.*, Uhlrich S.D.*, Kidziński L., Thomas K., Kolesar J.A., Gold G.E., Beaupre G.S., Delp S.L. A neural network to predict the knee adduction moment in patients with osteoarthritis using anatomical landmarks obtainable from 2D video analysis. Osteoarthritis and Cartilage 29(3):346-356. *contributed equally. Download PDF

Uhlrich S.D., Jackson R.W., Seth A., Kolesar J.A., Delp S.L., 2021. Muscle coordination retraining inspired by musculoskeletal simulations: a study on reducing knee loading. bioRxiv. Download PDF

Uhlrich S.D., Kolesar J.A., Kidziński L., Boswell M.A., Silder A., Gold G.E., Delp S.L., Beaupre G.S., 2020. Personalization improves the biomechanical efficacy of foot progression angle modifications in individuals with medial knee osteoarthritis. medRxiv. Download PDF

Simpson C.S., Welker C.G., Uhlrich S.D., Sketch S.M., Jackson R.W., Delp S.L., Collins S.H., Selinger J.C., Hawkes E.W., 2019. Connecting the legs with a spring improves human running economy. Journal of Experimental Biology 222. Download PDF

Haddock B., Fan A.P., Uhlrich S.D., Jorgensen N., Suetta C., Gold G.E., Kogan  F., 2019. Assessment of acute bone loading in humans using [18F]NaF PET/MRI. European Journal of Nuclear Medicine and Molecular Imaging 46(12):2452-2463. Download PDF

Uhlrich S.D., Silder A., Beaupré G.S. Shull, P.B. Delp, S.L., 2018. Subject-specific toe-in or toe-out gait modifications reduce the larger knee adduction moment peak more than a non-personalized approach. Journal of Biomechanics 66:p103-110. Download PDF

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