2014 | OriginalPaper | Buchkapitel
Intraoperative Decision Making with Rough Set Rules for STN DBS in Parkinson Disease
verfasst von : Konrad Ciecierski, Zbigniew W. Raś, Andrzej W. Przybyszewski
Erschienen in: Brain Informatics and Health
Verlag: Springer International Publishing
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In neurosurgical treatment of the Parkinson Disease (
PD
) the target is a small (9 x 7 x 4 mm) deep within brain placed structure called
Subthalamic
Nucleus
(
STN
). The goal of the Deep Brain Stimulation (
DBS
) surgery is the permanent precise placement of the stimulating electrode within target nucleus. As this structure poorly discriminates in CT or MRI it is usually stereotactically located using microelectrode recording. Several microelectrodes are parallelly inserted into the brain and in measured steps they are advanced towards expected location of the nucleus. At each step, from 20 mm above the target, the neuronal activity is recorded. Because
STN
has a distinct physiology, the signals recorded within it also present specific features. By extracting certain features from recordings provided by the microelectrodes, it is possible to construct a classifier that provides useful discrimination. This discrimination divides the recordings into two classes, i.e. those registered within the
STN
and those registered outside of it. Using the decision tree based classifiers, the best results have been obtained using the Random Forest method. In this paper we compared the results obtained from the Random Forest to those provided by the classification based upon rules extracted by the rough set approach.