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ADAPTIVE LEARNING OF NEURAL ACTIVITY DURING DEEP BRAIN STIMULATION


Abstract Parkinson's disease is a neurodegenerative condition diagnosed on patients with

clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated

number of patients living with Parkinson's disease around the world is seven

to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor

signs of Parkinson's disease patients. It is an advanced surgical technique that is used

when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.

This work proposes a behavior recognition model for patients with Parkinson's

disea... (more)
Created Date 2015
Contributor Dutta, Arindam (Author) / Papandreou-Suppappola, Antonia (Advisor) / Holbert, Keith E. (Committee member) / Bliss, Daniel W. (Committee member) / Arizona State University (Publisher)
Subject Engineering / Electrical engineering / Deep brain stimulation / Dirichlet process Gaussian mixture model / Matching pursuit decomposition / Parkinson's disease
Type Masters Thesis
Extent 55 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Masters Thesis Electrical Engineering 2015
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis