Machine Learning for Hand Prosthetics (and more)

Supervisor
Claudio Castellini - Università di Genova
Date and time
Tuesday, October 16, 2007 at 5:00 PM
Place
Ca' Vignal - Piramide, Floor 0, Hall Verde
Programme Director
Paolo Fiorini
External reference
Publication date
September 16, 2007
Department
 

Summary

Currently, the dexterity of active hand prosthetics is hindered due to
limitations in interfaces. How is an amputee supposed to command the
prosthesis what to do (i.e., how to grasp an object) and with what force
(i.e., holding a hammer or grasping an egg)? In this talk I address the
issue by applying machine learning to the problem of regression from
surface forearm EMG to the force a subject is applying. A detailed
comparative analysis among three different machine learning approaches
reveals that the apporach, as a whole, is viable.

More applications of machine learning to grasping and reaching will be
shown, among which prediction of grasping postures and of the user's
intention to grasp.






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