Toward Filtering of Athetoid Motion with Neural Networks

Juan J. V?quez, Kevin C. Olds, Sara Sibenaller, Dan Ding, and Cameron Riviere
Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August, 2007, pp. 1434-1436.


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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.

Keywords
athetosis, movement disorders, assistive interfaces

Notes
Sponsor: National Institutes of Health
Grant ID: R21HD050717
Associated Center(s) / Consortia: Medical Robotics Technology Center
Associated Lab(s) / Group(s): Surgical Mechatronics Laboratory
Associated Project(s): Joystick Filtering for Movement Disorders
Number of pages: 3

Text Reference
Juan J. V?quez, Kevin C. Olds, Sara Sibenaller, Dan Ding, and Cameron Riviere, "Toward Filtering of Athetoid Motion with Neural Networks," Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August, 2007, pp. 1434-1436.

BibTeX Reference
@inproceedings{Olds_2007_5988,
   author = "Juan J. V?quez 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 the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",
   pages = "1434-1436",
   month = "August",
   year = "2007",
}