In this work we present a preliminary study on a system able to design automatically sockets for lower-limb prosthesis. The socket is the most important part of the whole prosthesis and requires a custom design specific for the patient’s characteristics and her/his residuum morphology. The system takes in input the weight and the lifestyle of the patient, the tonicity level and the geometry file of the residuum, and creates a new model applying the correct geometric deformations needed to create a functional socket. In fact, in order to provide the right fit and prevent pain, we need to create on the socket load and off-load zones in correspondence of the critical anatomical areas. To identify the position of such critical areas, several neural networks have been trained using a dataset generated from real residuum models.

Automatic below-knee prosthesis socket design: A preliminary approach

COLOMBO, GIORGIO;
2016-01-01

Abstract

In this work we present a preliminary study on a system able to design automatically sockets for lower-limb prosthesis. The socket is the most important part of the whole prosthesis and requires a custom design specific for the patient’s characteristics and her/his residuum morphology. The system takes in input the weight and the lifestyle of the patient, the tonicity level and the geometry file of the residuum, and creates a new model applying the correct geometric deformations needed to create a functional socket. In fact, in order to provide the right fit and prevent pain, we need to create on the socket load and off-load zones in correspondence of the critical anatomical areas. To identify the position of such critical areas, several neural networks have been trained using a dataset generated from real residuum models.
2016
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783319402468
CAD; Lower limb prosthesis; Neural network; Prosthetic socket; Theoretical Computer Science; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1030833
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