科研之友
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摘要
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.
- 出版日期2016-5
