
A. (Ajay) Seth
A. (Ajay) Seth
Profile
Biography
I lead the
Computational Biomechanics Lab in the department of Biomechanical Engineering here at TU Delft. The lab's mission is to develop computational models and algorithms that enable the acquisition, analysis and study of human and animal movement. We are interested in methods that quantify and explain the biological basis of movement from the pathological to the exceptional.
Before joining TU Delft, I was the architect of the
OpenSim modeling and simulation libraries at Stanford University for nearly a decade after completing a Simbios distinguished postdoctoral fellowship in Bioengineering. I received my PhD at the University of Texas at Austin in Biomedical engineering and my predoctoral degrees in Systems Design Engineering from the University of Waterloo.
Expertise
I build neuromuscular and musculoskeletal models and develop simulation tools to obtain deeper insights into human and animal movement. I combine expertise in multibody dynamics, muscle-tendon mechanics, neuromotor control and anatomy to create insightful and reproducible models. I leverage decades of software engineering experience to implement algorithms and simulators that enable new lines of research in movement science, assistive robotics and wearable sensing.
Expertise
Publications
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2022
Conclusion or Illusion
Quantifying Uncertainty in Inverse Analyses From Marker-Based Motion Capture due to Errors in Marker Registration and Model Scaling
Thomas K. Uchida / Ajay Seth -
2022
Enabling Patient- and Teleoperator-led Robotic Physiotherapy via Strain Map Segmentation and Shared-authority
S. Balvert / J.M. Prendergast / I. Belli / A. Seth / L. Peternel
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2022
From Human Walking to Bipedal Robot Locomotion
Reflex Inspired Compensation on Planned and Unplanned Downsteps
J. Verhagen / Xiaobin Xiong / A. D. Ames / A. Seth -
2022
Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force
Scott D. Uhlrich / Rachel W. Jackson / Ajay Seth / Julie A. Kolesar / Scott L. Delp
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2022
OpenSense
An open-source toolbox for inertial-measurement-unit-based measurement of lower extremity kinematics over long durations
Mazen Al Borno / Johanna O’Day / Vanessa Ibarra / James Dunne / Ajay Seth / Ayman Habib / Carmichael Ong / Jennifer Hicks / Scott Uhlrich / Scott Delp -
Media
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2018-07-26
Software recreates complex movements for medical, rehabilitation, and basic research
Appeared in: Phys.org
Ancillary activities
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2022-11-18 - 2024-11-18