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An automated segmentation approach to calibrating infantile nystagmus waveforms
Infantile nystagmus (IN) describes a regular, repetitive movement of the eyes. A characteristic feature of each cycle of the IN eye movement waveform is a period in which the eyes are moving at minimal velocity. This so-called “foveation” period has long been considered the basis for the best vision...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797654/ https://www.ncbi.nlm.nih.gov/pubmed/30875024 http://dx.doi.org/10.3758/s13428-018-1178-5 |
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author | Dunn, Matt J. Harris, Christopher M. Ennis, Fergal A. Margrain, Tom H. Woodhouse, J. Margaret McIlreavy, Lee Erichsen, Jonathan T. |
author_facet | Dunn, Matt J. Harris, Christopher M. Ennis, Fergal A. Margrain, Tom H. Woodhouse, J. Margaret McIlreavy, Lee Erichsen, Jonathan T. |
author_sort | Dunn, Matt J. |
collection | PubMed |
description | Infantile nystagmus (IN) describes a regular, repetitive movement of the eyes. A characteristic feature of each cycle of the IN eye movement waveform is a period in which the eyes are moving at minimal velocity. This so-called “foveation” period has long been considered the basis for the best vision in individuals with IN. In recent years, the technology for measuring eye movements has improved considerably, but there remains the challenge of calibrating the direction of gaze in tracking systems when the eyes are continuously moving. Identifying portions of the nystagmus waveform suitable for calibration typically involves time-consuming manual selection of the foveation periods from the eye trace. Without an accurate calibration, the exact parameters of the waveform cannot be determined. In this study, we present an automated method for segmenting IN waveforms with the purpose of determining the foveation positions to be used for calibration of an eye tracker. On average, the “point of regard” was found to be within 0.21° of that determined by hand-marking by an expert observer. This method enables rapid clinical quantification of waveforms and the possibility of gaze-contingent research paradigms being performed with this patient group. |
format | Online Article Text |
id | pubmed-6797654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-67976542019-11-01 An automated segmentation approach to calibrating infantile nystagmus waveforms Dunn, Matt J. Harris, Christopher M. Ennis, Fergal A. Margrain, Tom H. Woodhouse, J. Margaret McIlreavy, Lee Erichsen, Jonathan T. Behav Res Methods Article Infantile nystagmus (IN) describes a regular, repetitive movement of the eyes. A characteristic feature of each cycle of the IN eye movement waveform is a period in which the eyes are moving at minimal velocity. This so-called “foveation” period has long been considered the basis for the best vision in individuals with IN. In recent years, the technology for measuring eye movements has improved considerably, but there remains the challenge of calibrating the direction of gaze in tracking systems when the eyes are continuously moving. Identifying portions of the nystagmus waveform suitable for calibration typically involves time-consuming manual selection of the foveation periods from the eye trace. Without an accurate calibration, the exact parameters of the waveform cannot be determined. In this study, we present an automated method for segmenting IN waveforms with the purpose of determining the foveation positions to be used for calibration of an eye tracker. On average, the “point of regard” was found to be within 0.21° of that determined by hand-marking by an expert observer. This method enables rapid clinical quantification of waveforms and the possibility of gaze-contingent research paradigms being performed with this patient group. Springer US 2019-03-11 2019 /pmc/articles/PMC6797654/ /pubmed/30875024 http://dx.doi.org/10.3758/s13428-018-1178-5 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Dunn, Matt J. Harris, Christopher M. Ennis, Fergal A. Margrain, Tom H. Woodhouse, J. Margaret McIlreavy, Lee Erichsen, Jonathan T. An automated segmentation approach to calibrating infantile nystagmus waveforms |
title | An automated segmentation approach to calibrating infantile nystagmus waveforms |
title_full | An automated segmentation approach to calibrating infantile nystagmus waveforms |
title_fullStr | An automated segmentation approach to calibrating infantile nystagmus waveforms |
title_full_unstemmed | An automated segmentation approach to calibrating infantile nystagmus waveforms |
title_short | An automated segmentation approach to calibrating infantile nystagmus waveforms |
title_sort | automated segmentation approach to calibrating infantile nystagmus waveforms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797654/ https://www.ncbi.nlm.nih.gov/pubmed/30875024 http://dx.doi.org/10.3758/s13428-018-1178-5 |
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