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Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching

The detection of nystagmus using video oculography experiences accuracy problems when patients who complain of dizziness have difficulty in fully opening their eyes. Pupil detection and tracking in this condition affect the accuracy of the nystagmus waveform. In this research, we design a pupil dete...

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Autores principales: Syahbana, Yoanda Alim, Yasunari, Yokota, Hiroyuki, Morita, Mitsuhiro, Aoki, Kanade, Suzuki, Yoshitaka, Matsubara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306141/
https://www.ncbi.nlm.nih.gov/pubmed/34356263
http://dx.doi.org/10.3390/healthcare9070885
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author Syahbana, Yoanda Alim
Yasunari, Yokota
Hiroyuki, Morita
Mitsuhiro, Aoki
Kanade, Suzuki
Yoshitaka, Matsubara
author_facet Syahbana, Yoanda Alim
Yasunari, Yokota
Hiroyuki, Morita
Mitsuhiro, Aoki
Kanade, Suzuki
Yoshitaka, Matsubara
author_sort Syahbana, Yoanda Alim
collection PubMed
description The detection of nystagmus using video oculography experiences accuracy problems when patients who complain of dizziness have difficulty in fully opening their eyes. Pupil detection and tracking in this condition affect the accuracy of the nystagmus waveform. In this research, we design a pupil detection method using a pattern matching approach that approximates the pupil using a Mexican hat-type ellipse pattern, in order to deal with the aforementioned problem. We evaluate the performance of the proposed method, in comparison with that of a conventional Hough transform method, for eye movement videos retrieved from Gifu University Hospital. The performance results show that the proposed method can detect and track the pupil position, even when only 20% of the pupil is visible. In comparison, the conventional Hough transform only indicates good performance when 90% of the pupil is visible. We also evaluate the proposed method using the Labelled Pupil in the Wild (LPW) data set. The results show that the proposed method has an accuracy of 1.47, as evaluated using the Mean Square Error (MSE), which is much lower than that of the conventional Hough transform method, with an MSE of 9.53. We conduct expert validation by consulting three medical specialists regarding the nystagmus waveform. The medical specialists agreed that the waveform can be evaluated clinically, without contradicting their diagnoses.
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spelling pubmed-83061412021-07-25 Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching Syahbana, Yoanda Alim Yasunari, Yokota Hiroyuki, Morita Mitsuhiro, Aoki Kanade, Suzuki Yoshitaka, Matsubara Healthcare (Basel) Article The detection of nystagmus using video oculography experiences accuracy problems when patients who complain of dizziness have difficulty in fully opening their eyes. Pupil detection and tracking in this condition affect the accuracy of the nystagmus waveform. In this research, we design a pupil detection method using a pattern matching approach that approximates the pupil using a Mexican hat-type ellipse pattern, in order to deal with the aforementioned problem. We evaluate the performance of the proposed method, in comparison with that of a conventional Hough transform method, for eye movement videos retrieved from Gifu University Hospital. The performance results show that the proposed method can detect and track the pupil position, even when only 20% of the pupil is visible. In comparison, the conventional Hough transform only indicates good performance when 90% of the pupil is visible. We also evaluate the proposed method using the Labelled Pupil in the Wild (LPW) data set. The results show that the proposed method has an accuracy of 1.47, as evaluated using the Mean Square Error (MSE), which is much lower than that of the conventional Hough transform method, with an MSE of 9.53. We conduct expert validation by consulting three medical specialists regarding the nystagmus waveform. The medical specialists agreed that the waveform can be evaluated clinically, without contradicting their diagnoses. MDPI 2021-07-13 /pmc/articles/PMC8306141/ /pubmed/34356263 http://dx.doi.org/10.3390/healthcare9070885 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Syahbana, Yoanda Alim
Yasunari, Yokota
Hiroyuki, Morita
Mitsuhiro, Aoki
Kanade, Suzuki
Yoshitaka, Matsubara
Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title_full Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title_fullStr Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title_full_unstemmed Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title_short Nystagmus Estimation for Dizziness Diagnosis by Pupil Detection and Tracking Using Mexican-Hat-Type Ellipse Pattern Matching
title_sort nystagmus estimation for dizziness diagnosis by pupil detection and tracking using mexican-hat-type ellipse pattern matching
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306141/
https://www.ncbi.nlm.nih.gov/pubmed/34356263
http://dx.doi.org/10.3390/healthcare9070885
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