Meniere's disease is a common inner ear disorder that affects balance and hearing. Electrovestibulography (EVestG) is a relatively new vestibular driven test that measures spontaneous and driven field potential activity recorded in the external ear canal in response to various vestibular stimuli. The main objectives of this thesis were to record and analyze EVestG signals in order to 1) testify whether the EVestG technology is capable of classifying individuals with Meniere’s from healthy ones, and if it is, then 2) identify the EVestG tilt stimulus providing the most informative response in relation to identifying Meniere’s symptoms; thus, optimizing the EVestG experimental protocol as a Meniere’s disease diagnostic aid.
EVestG signals of two groups of Meniere’s and control individuals during seven different EVestG tilt stimuli were recorded and analyzed by linear and nonlinear signal processing techniques. Data of 14 with Meniere’s disease and 16 healthy individuals were used as the training set, while additional data of 21 individuals with vertiginous disorders (and suspected of Meniere’s disease) and 10 controls were used as the test set. An ad-hoc voting classifier built upon single-feature linear classifiers was designed, and used for classification of the two groups of both training and test datasets.
The results showed an overall accuracy of 87% and 84% for training and test datasets, respectively. Among the seven different tilts that each evokes a specific part of the inner ear organ, the side tilt which stimulates most of the labyrinth and particularly the utricle, was found to generate the best characteristic features for identifying Meniere’s disease from controls. Thus, one may simplify the EVestG protocol to only the side tilt stimulus for a quick screening of Meniere’s disease.
The proposed method encourages the use of EVestG technology as a non-invasive and potentially reliable diagnostic/screening tool to aid clinical diagnosis of Meniere’s diseases. / October 2016
Identifer | oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31654 |
Date | 08 September 2016 |
Creators | Dastgheib, Zeinab |
Contributors | Moussavi, Zahra (Biomedical Engineering) Lithgow, Brian (Biomedical Engineering), Blakley, Brian (Otolaryngology) Kinsner, Witold (Electrical & Computer Engineering) Hadjileontiadis, Leontios (Electrical and Computer Engineering) |
Source Sets | University of Manitoba Canada |
Detected Language | English |
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