University of Cambridge > Talks.cam > Foundation AI > Personalising Crutch Geometries through Bayesian Optimisation

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Personalising Crutch Geometries through Bayesian Optimisation

Download to your calendar using vCal

If you have a question about this talk, please contact Pietro Lio .

Crutches are optimised for stable motion, but this safety comes at the cost of comfort and speed. In this paper, we employ Gaussian Processes (GPs) and Bayesian Optimisation (BO) as hypothesis generators to find better crutch configurations, which we validate on a physical prototype. We do so by defining a novel loss function indicating the quality of a crutch design which combines subjective metrics (joint pain, instability and effort) and the corresponding objective ones. Finally, we (1) use this methodology to build a more stable, less effortful and less painful personalised crutch design and (2) use the knowledge built by the GP through these experiments to enhance our understanding of the physical dynamics of crutching.

This talk is part of the Foundation AI series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Faculty of Law B16 Leslie Stephen Room, Trinity Hall Seminar time is 1pm BST in Room FW 11, Willam Gates Hall. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon

Other talks

The Neurophenomenology of Surrender: Agency, Renewal, and Social Engagement in Speaking in Tongues Machine Learning for Spectral Geometry and Vice Versa Title to be confirmed César Milstein Lecture - Title TBC Royal Papworth Hospital and Acute Medicine From Surrogate Solvers to PINNs and Beyond Classical Methods
 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity