Control of Neuralprostheses I: Sensor FusionBy Andrews, Brian J. Williamson, Richard Oulette, Narce Koles, Andrew Department of Biomedical Engineering, University of Alberta, Edmonton, Canada; Proceedings of the RESNA '96 Annual Conference, Vol. 16
(Pages: 282-284) Publication Date: 1996
This article describes a study whose aim is to discover if machine learning technology can be used to map a suite of sensors to a comprehensive set of biomechanical variables required for control of neuralprotheses. Senors currently being evaluated are: micro-machined accelerometers with a DC response; strain gauges; a custom position and angle sensor. Tests were conducted with various combinations of these devices in subject waistbands and ankle foot orthoses. Graphs show typical sensor signals and anatomical positions, velocities and accelerations.
Published by: Rehabilitation Engineering & Assistive Technology Society of North America (RESNA) (Website:http://www.resna.org)
Link to text: http://www.resna.org