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Abstract Details

Activity Number: 405
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #306104
Title: Isotonic Regression for Estimating the Highest Impedance Time Point for Deep Brain Stimulation
Author(s): Yufan Zhao*+ and Lilly Chen and Nitzan Mekel-Bobrov
Companies: Boston Scientific Neuromodulation and Boston Scientific Neuromodulation and Boston Scientific Neuromodulation
Address: 25155 Rye Canyon Loop, Valencia, CA, 91355, United States
Keywords: Deep Brain Stimulation ; Impedance ; Isotonic Regression ; Medical Device ; Neuromodulation
Abstract:

Deep brain stimulation (DBS) is a relatively novel therapy for the treatment of a number of prevalent neurological disorders. One potential obstacle in achieving optimal therapy with delivering DBS is variation over time in the electrical impedance surrounding the implanted electrodes, which may significantly affect the absolute amount of current delivered to the tissue. Consequently, interest has recently emerged in identifying the maximal impedance time-point as optimal timing for device activation. In this talk we demonstrate that the timing which yields highest impedance can be estimated efficiently by using isotonic regression. A two-stage design motivated by Keifer-Wolfowitz procedure was performed to evaluate the relationship between the allocation size of initial stage and the probability of correct timing prediction. Results of simulations are presented.


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