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Identifying differences in the P600 component of ERP-Signals between OCD patients and controls employing a PNN-based majority vote classification scheme
Όνομα Συνεδρίου:International Conference of the IEEE Engineering in Medicine & Biology Society
In the present study an attempt was made to focus in
the differences between Obsessive-Compulsive Disorder (OCD)
patients and healthy controls, as reflected by the P600 component
of event-related potential (ERP) signals, to locate brain areas
that may be related to Working Memory (WM) deficits.
Neuropsychological research has yielded contradicting results
regarding WM in OCD. Eighteen patients with OCD symptomatology
and 20 normal controls (age and sex matched) were
subjected to a computerized version of the digit span Wechsler
test. EEG activity was recorded from 15 scalp electrodes (leads).
A dedicated computer software was developed to read the
ERP signals and to calculate features related to the ERP
P600 component (500-800 ms). Nineteen features were
generated, from each ERP-signal and each lead, and were
employed in the design of the Probabilistic Neural Network
(PNN) classifier. Highest single-lead precision (86.8%) was
found at the Fp2 and C6 leads. When the output from all singlelead
PNN classifiers fed a Majority Vote Engine (MVE), the system
classified correctly all subjects, providing a powerful classification
scheme. Findings indicated that OCD patients differed
from normal controls at the prefrontal and temporo-central
brain regions.
Θέμα:Medicine, Medical technology, Ιατρική, Ιατρικά όργανα και εξοπλισμός