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Med Biol Eng Comput. 2012 May;50(5):483-91. doi: 10.1007/s11517-012-0890-z. Epub 2012 Mar 8.

Diagnosis of Parkinson's disease using electrovestibulography.

Author information

1
Department of Electrical and Computer Engineering, Room E3-512 Eng. Bldg, 75A Chancellor's Circle, Winnipeg, MB R3T 5V6, Canada. zeinab@ee.umanitoba.ca

Abstract

In this paper, a new method for diagnosis of Parkinson's disease (PD) based on the analysis of electrovestibulography (EVestG) signals is introduced. EVestG signals are in fact the vestibular response modulated by more cortical brain signals; they are recorded from the ear canal. EVestG data of 20 individuals with PD and 28 healthy controls were adopted from a previous study. The field potentials and their firing pattern in response to whole body tilt stimuli from both left and right ears were extracted. We investigated several statistical and fractal features of the field potentials and also their firing interval histograms followed by one-way analysis of variance to select pairs of features showing the most significant differences between individuals with Parkinson disease and the age-matched controls. Linear discriminant analysis classification was applied to every selected feature using a leave-one-out routine. The result of each feature's classifier was used in a heuristic average voting system to diagnose PD patients. The results show more than 95% accuracy for PD diagnosis. Given that the patients were at different stage of disease, the high accuracy of the results is encouraging for continuing exploration of the EVestG application to PD diagnosis as it may provide a quick and non-invasive screening tool.

PMID:
22399163
DOI:
10.1007/s11517-012-0890-z
[Indexed for MEDLINE]

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