Toward Filtering of Athetoid Motion with Neural Networks
Conference Paper, Proceedings of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '07), pp. 1434 - 1436, August, 2007
Abstract
People with athetoid cerebral palsy (CP) have difficulty using computers due to unintentional involuntary movements in the upper extremities. A neural network-based system has been developed to cancel the undesired motion, and speed up the movements and accuracy in target acquisition and path tracking tasks while using an isometric joystick (IJ). Nonlinear filtering algorithms were created with neural networks using nonlinear models to help people with athetoid CP to access the computer. This paper presents unfiltered test data that have been collected from patients, and describes the planned filtering approach.
BibTeX
@conference{V?quez-2007-9803,author = {Juan J. Vazquez Lopez and Kevin C. Olds and Sara Sibenaller and Dan Ding and Cameron Riviere},
title = {Toward Filtering of Athetoid Motion with Neural Networks},
booktitle = {Proceedings of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '07)},
year = {2007},
month = {August},
pages = {1434 - 1436},
keywords = {athetosis, movement disorders, assistive interfaces},
}
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