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Early fault prediction and detection of hydrocephalus shunting system
Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
Mechatronics Engineering Department, Faculty of Engineering and Technology, Al-Balqa’ Applied University, Amman, Jordan
Department of Electrical Engineering, University of Liverpool, Liverpool, UK
Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
Mechatronics Engineering Department, Faculty of Engineering and Technology, Al-Balqa’ Applied University, Amman, Jordan
- 1 Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
- 2 Mechatronics Engineering Department, Faculty of Engineering and Technology, Al-Balqa’ Applied University, Amman, Jordan
- 3 Department of Electrical Engineering, University of Liverpool, Liverpool, UK
- 4 Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
- 5 Faculty of Science and Information Technology, The World Islamic Sciences and Education Technology, Amman, Jordan
- 6 Mechatronics Engineering Department, Faculty of Engineering and Technology, Al-Balqa’ Applied University, Amman, Jordan
Journal of Biomedical Science and Engineering·Volume 06 (2013)·Pages 280–290·Published 12 March 2013·DOI10.4236/jbise.2013.63036
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Abstract
Trends of various intracranial pressure (ICP) parameters for high pressure hydrocephalus patients are utilized to detect various shunt faults in their early stages, as well as, to monitor the effect of such faults on shunt performance. A method was proposed to predict the time required for ICP to be abnormal and for the valve to reach full blockage condition. Furthermore, an auto valve schedule updating method is proposed and used to temporarily deal with detected faults until the patient is checked up by his/her physician. The proposed algorithms were evaluated using numerical simulation.
KeywordsHydrocephalus ShuntsShunt MalfunctionsFaults Detection
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