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The Mobilize Center and Restore Center at Stanford University invite you to join our next webinar, featuring Keenon Werling from Stanford University.
DETAILS
Title: AddBiomechanics – Lowering the Barriers to Musculoskeletal Modeling and Large-Scale Discoveries in Biomechanics
Speaker: Keenon Werling, Stanford University
Time: Wednesday, September 20, 2023 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Generating large-scale public datasets could unlock insights into human movement, neuromuscular diseases, and new treatments and interventions. However, processing movement data with detailed musculoskeletal models requires a substantial amount of time and expertise.To address this problem, Keenon Werling and colleagues at Stanford University developed AddBiomechanics, a free online tool with the mission of enhancing the impact of biomechanical motion capture efforts by helping labs process and share their data, unlocking powerful machine learning tools and improving replicability of results. AddBiomechanics automatically generates scaled models, joint angles, and torque trajectories that best fit your optical marker trajectories and force plate measurements with similar or better accuracy compared to expert-processed results. The uploaded data and processed results are automatically shared with the community, under a license that requires users of the data to cite your work.
In the first part of this webinar, Mr. Werling will present the AddBiomechanics web platform and show how it can fit into your lab’s workflow. He will outline the data sharing vision of the platform, describe how the tool works, discuss its evaluation of performance against human experts, and introduce the inverse dynamics features that have been recently added.
In the second half of the webinar, Mr. Werling will walk participants through a hands-on tutorial of uploading and processing motion capture data, provide best practices and troubleshooting tips when using AddBiomechanics, and provide an easy “getting started” kit for data sharing compliance.
Keenon Werling, Nicholas A. Bianco, Michael Raitor, Jon Stingel, Jennifer L. Hicks, Steven H. Collins, Scott L. Delp, C. Karen Liu. (2023) AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization. bioRxiv
DETAILS
Title: AddBiomechanics – Lowering the Barriers to Musculoskeletal Modeling and Large-Scale Discoveries in Biomechanics
Speaker: Keenon Werling, Stanford University
Time: Wednesday, September 20, 2023 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Generating large-scale public datasets could unlock insights into human movement, neuromuscular diseases, and new treatments and interventions. However, processing movement data with detailed musculoskeletal models requires a substantial amount of time and expertise.To address this problem, Keenon Werling and colleagues at Stanford University developed AddBiomechanics, a free online tool with the mission of enhancing the impact of biomechanical motion capture efforts by helping labs process and share their data, unlocking powerful machine learning tools and improving replicability of results. AddBiomechanics automatically generates scaled models, joint angles, and torque trajectories that best fit your optical marker trajectories and force plate measurements with similar or better accuracy compared to expert-processed results. The uploaded data and processed results are automatically shared with the community, under a license that requires users of the data to cite your work.
In the first part of this webinar, Mr. Werling will present the AddBiomechanics web platform and show how it can fit into your lab’s workflow. He will outline the data sharing vision of the platform, describe how the tool works, discuss its evaluation of performance against human experts, and introduce the inverse dynamics features that have been recently added.
In the second half of the webinar, Mr. Werling will walk participants through a hands-on tutorial of uploading and processing motion capture data, provide best practices and troubleshooting tips when using AddBiomechanics, and provide an easy “getting started” kit for data sharing compliance.
Keenon Werling, Nicholas A. Bianco, Michael Raitor, Jon Stingel, Jennifer L. Hicks, Steven H. Collins, Scott L. Delp, C. Karen Liu. (2023) AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization. bioRxiv