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An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker
Objective: Most neurological diseases are usually accompanied by changes in the oculomotor nerve. Analysis of different types of eye movements will help provide important information in ophthalmology, neurology, and psychology. At present, many scholars use optokinetic nystagmus (OKN) to study the p...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320438/ https://www.ncbi.nlm.nih.gov/pubmed/35885808 http://dx.doi.org/10.3390/healthcare10071281 |
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author | Hsu, Wei-Yen Cheng, Ya-Wen Tsai, Chong-Bin |
author_facet | Hsu, Wei-Yen Cheng, Ya-Wen Tsai, Chong-Bin |
author_sort | Hsu, Wei-Yen |
collection | PubMed |
description | Objective: Most neurological diseases are usually accompanied by changes in the oculomotor nerve. Analysis of different types of eye movements will help provide important information in ophthalmology, neurology, and psychology. At present, many scholars use optokinetic nystagmus (OKN) to study the physiological phenomenon of eye movement. OKN is an involuntary eye movement induced by a large moving surrounding visual field. It consists of a slow pursuing eye movement, called “slow phase” (SP), and a fast re-fixating saccade eye movement, called “fast phase” (FP). Non-invasive video-oculography has been used increasingly in eye movement research. However, research-grade eye trackers are often expensive and less accessible to most researchers. Using a low-cost eye tracker to quantitatively measure OKN eye movement will facilitate the general application of eye movement research. Methods & Results: We design an analytical algorithm to quantitatively measure OKN eye movements on a low-cost eye tracker. Using simple conditional filtering, accurate FP positions can be obtained quickly. The high-precision FP recognition rate is of great help for the subsequent calculation of eye movement analysis parameters, such as mean slow phase velocity (MSPV), which is beneficial as a reference index for patients with strabismus and other eye diseases. Conclusions: Experimental results indicate that the proposed method achieves faster and better results than other approaches, and can provide an effective algorithm to calculate and analyze the FP position of OKN waveforms. |
format | Online Article Text |
id | pubmed-9320438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93204382022-07-27 An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker Hsu, Wei-Yen Cheng, Ya-Wen Tsai, Chong-Bin Healthcare (Basel) Article Objective: Most neurological diseases are usually accompanied by changes in the oculomotor nerve. Analysis of different types of eye movements will help provide important information in ophthalmology, neurology, and psychology. At present, many scholars use optokinetic nystagmus (OKN) to study the physiological phenomenon of eye movement. OKN is an involuntary eye movement induced by a large moving surrounding visual field. It consists of a slow pursuing eye movement, called “slow phase” (SP), and a fast re-fixating saccade eye movement, called “fast phase” (FP). Non-invasive video-oculography has been used increasingly in eye movement research. However, research-grade eye trackers are often expensive and less accessible to most researchers. Using a low-cost eye tracker to quantitatively measure OKN eye movement will facilitate the general application of eye movement research. Methods & Results: We design an analytical algorithm to quantitatively measure OKN eye movements on a low-cost eye tracker. Using simple conditional filtering, accurate FP positions can be obtained quickly. The high-precision FP recognition rate is of great help for the subsequent calculation of eye movement analysis parameters, such as mean slow phase velocity (MSPV), which is beneficial as a reference index for patients with strabismus and other eye diseases. Conclusions: Experimental results indicate that the proposed method achieves faster and better results than other approaches, and can provide an effective algorithm to calculate and analyze the FP position of OKN waveforms. MDPI 2022-07-10 /pmc/articles/PMC9320438/ /pubmed/35885808 http://dx.doi.org/10.3390/healthcare10071281 Text en © 2022 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 Hsu, Wei-Yen Cheng, Ya-Wen Tsai, Chong-Bin An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title | An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title_full | An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title_fullStr | An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title_full_unstemmed | An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title_short | An Effective Algorithm to Analyze the Optokinetic Nystagmus Waveforms from a Low-Cost Eye Tracker |
title_sort | effective algorithm to analyze the optokinetic nystagmus waveforms from a low-cost eye tracker |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320438/ https://www.ncbi.nlm.nih.gov/pubmed/35885808 http://dx.doi.org/10.3390/healthcare10071281 |
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