Literature DB >> 26334355

Application of Vestibular Spontaneous Response as a Diagnostic Aid for Meniere's Disease.

Z A Dastgheib1, B Lithgow2,3,4, B Blakely5, Z Moussavi6,7.   

Abstract

In this paper, we report on a new method for assisting in Meniere's disease diagnosis. An accurate diagnosis of Meniere's is challenging, and requires an expert opinion after observing several clinical assessments and tests over a period of time. Our proposed method is based on the analysis of the spontaneous and driven ear evoked responses recorded using Electrovestibulography (EVestG). We used the EVestG signals of 35 individuals suspected of Meniere's and 26 age-matched healthy controls, out of which data of 14 patients with Meniere's and 16 healthy controls were used for developing the diagnostic algorithm (training set) and the rest for testing. While recording and analyzing the test dataset, the researchers were only aware the patients suffered some dizziness, and were kept blind to the exact diagnoses till the end of study. EVestG field potentials (FPs) and their firing pattern, in response to several whole body tilt stimuli from both left and right ears were extracted. We investigated several features of the extracted FPs in response to each of side, back/forward, rotation, up/down, supine rotation, and supine up/down tilt stimulations, and selected the top five features showing the most significant differences between of the groups of the training set for every tilt. An ad-hoc average voting classifier was designed based on building five single-feature classifiers (using Linear Discriminant analysis) and taking the average of the single-feature classifiers' votes. The results showed the side tilt data were best for the purpose of Meniere's diagnosis; it resulted in 78% and 90% sensitivity and specificity for test dataset, respectively. The second best accuracy was achieved using back/forward tilt. The results and their implications are discussed. Overall, the EVestG side tilt results encourage the use of vestibular response as a non-invasive, robust and quick screening for Meniere's and separating it from other types of dizziness.

Entities:  

Keywords:  Classification; EVestG; Fractal dimension; Meniere’s disease; Vestibular response

Mesh:

Year:  2015        PMID: 26334355     DOI: 10.1007/s10439-015-1441-1

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  5 in total

1.  Physiological separation of Alzheimer's disease and Alzheimer's disease with significant levels of cerebrovascular symptomology and healthy controls.

Authors:  Brian J Lithgow; Zeinab Dastgheib; Neda Anssari; Behzad Mansouri; Brian Blakley; Mehrangiz Ashiri; Zahra Moussavi
Journal:  Med Biol Eng Comput       Date:  2021-07-15       Impact factor: 2.602

2.  An unbiased algorithm for objective separation of Alzheimer's, Alzheimer's mixed with cerebrovascular symptomology, and healthy controls from one another using electrovestibulography (EVestG).

Authors:  Zeinab A Dastgheib; Brian J Lithgow; Zahra K Moussavi
Journal:  Med Biol Eng Comput       Date:  2022-01-31       Impact factor: 2.602

3.  Quantitative measurement of post-concussion syndrome Using Electrovestibulography.

Authors:  Abdelbaset Suleiman; Brian Lithgow; Zeinab Dastgheib; Behzad Mansouri; Zahra Moussavi
Journal:  Sci Rep       Date:  2017-11-27       Impact factor: 4.379

Review 4.  Electrophysiological Measurements of Peripheral Vestibular Function-A Review of Electrovestibulography.

Authors:  Daniel J Brown; Christopher J Pastras; Ian S Curthoys
Journal:  Front Syst Neurosci       Date:  2017-05-31

5.  Verification EVestG recordings are vestibuloacoustic signals.

Authors:  Brian Blakley; Mehrangiz Ashiri; Zahra Moussavi; Brian Lithgow
Journal:  Laryngoscope Investig Otolaryngol       Date:  2022-07-09
  5 in total

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