Analysing nystagmus waveforms: a computational framework

Abstract We present a new computational approach to analyse nystagmus waveforms. Our framework is designed to fully characterise the state of the nystagmus, aid clinical diagnosis and to quantify the dynamical changes in the oscillations over time. Both linear and nonlinear analyses of time series w...

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Autores principales:	Richard V. Abadi, Ozgur E. Akman, Gemma E. Arblaster, Richard A. Clement
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7d896e5e15314fb881a384329bc5dedd
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spelling	oai:doaj.org-article:7d896e5e15314fb881a384329bc5dedd2021-12-02T14:29:10ZAnalysing nystagmus waveforms: a computational framework10.1038/s41598-021-89094-72045-2322https://doaj.org/article/7d896e5e15314fb881a384329bc5dedd2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89094-7https://doaj.org/toc/2045-2322Abstract We present a new computational approach to analyse nystagmus waveforms. Our framework is designed to fully characterise the state of the nystagmus, aid clinical diagnosis and to quantify the dynamical changes in the oscillations over time. Both linear and nonlinear analyses of time series were used to determine the regularity and complexity of a specific homogenous phenotype of nystagmus. Two-dimensional binocular eye movement recordings were carried out on 5 adult subjects who exhibited a unilateral, uniplanar, vertical nystagmus secondary to a monocular late-onset severe visual loss in the oscillating eye (the Heimann-Bielschowsky Phenomenon). The non-affected eye held a central gaze in both horizontal and vertical planes (± 10 min. of arc). All affected eyes exhibited vertical oscillations, with mean amplitudes and frequencies ranging from 2.0°–4.0° to 0.25–1.5 Hz, respectively. Unstable periodic orbit analysis revealed only 1 subject exhibited a periodic oscillation. The remaining subjects were found to display quasiperiodic (n = 1) and nonperiodic (n = 3) oscillations. Phase space reconstruction allowed attractor identification and the computation of a time series complexity measure—the permutation entropy. The entropy measure was found to be able to distinguish between a periodic oscillation associated with a limit cycle attractor, a quasiperiodic oscillation associated with a torus attractor and nonperiodic oscillations associated with higher-dimensional attractors. Importantly, the permutation entropy was able to rank the oscillations, thereby providing an objective index of nystagmus complexity (range 0.15–0.21) that could not be obtained via unstable periodic orbit analysis or attractor identification alone. These results suggest that our framework provides a comprehensive methodology for characterising nystagmus, aiding differential diagnosis and also permitting investigation of the waveforms over time, thereby facilitating the quantification of future therapeutic managements. In addition, permutation entropy could provide an additional tool for future oculomotor modelling.Richard V. AbadiOzgur E. AkmanGemma E. ArblasterRichard A. ClementNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Richard V. Abadi Ozgur E. Akman Gemma E. Arblaster Richard A. Clement Analysing nystagmus waveforms: a computational framework
description	Abstract We present a new computational approach to analyse nystagmus waveforms. Our framework is designed to fully characterise the state of the nystagmus, aid clinical diagnosis and to quantify the dynamical changes in the oscillations over time. Both linear and nonlinear analyses of time series were used to determine the regularity and complexity of a specific homogenous phenotype of nystagmus. Two-dimensional binocular eye movement recordings were carried out on 5 adult subjects who exhibited a unilateral, uniplanar, vertical nystagmus secondary to a monocular late-onset severe visual loss in the oscillating eye (the Heimann-Bielschowsky Phenomenon). The non-affected eye held a central gaze in both horizontal and vertical planes (± 10 min. of arc). All affected eyes exhibited vertical oscillations, with mean amplitudes and frequencies ranging from 2.0°–4.0° to 0.25–1.5 Hz, respectively. Unstable periodic orbit analysis revealed only 1 subject exhibited a periodic oscillation. The remaining subjects were found to display quasiperiodic (n = 1) and nonperiodic (n = 3) oscillations. Phase space reconstruction allowed attractor identification and the computation of a time series complexity measure—the permutation entropy. The entropy measure was found to be able to distinguish between a periodic oscillation associated with a limit cycle attractor, a quasiperiodic oscillation associated with a torus attractor and nonperiodic oscillations associated with higher-dimensional attractors. Importantly, the permutation entropy was able to rank the oscillations, thereby providing an objective index of nystagmus complexity (range 0.15–0.21) that could not be obtained via unstable periodic orbit analysis or attractor identification alone. These results suggest that our framework provides a comprehensive methodology for characterising nystagmus, aiding differential diagnosis and also permitting investigation of the waveforms over time, thereby facilitating the quantification of future therapeutic managements. In addition, permutation entropy could provide an additional tool for future oculomotor modelling.
format	article
author	Richard V. Abadi Ozgur E. Akman Gemma E. Arblaster Richard A. Clement
author_facet	Richard V. Abadi Ozgur E. Akman Gemma E. Arblaster Richard A. Clement
author_sort	Richard V. Abadi
title	Analysing nystagmus waveforms: a computational framework
title_short	Analysing nystagmus waveforms: a computational framework
title_full	Analysing nystagmus waveforms: a computational framework
title_fullStr	Analysing nystagmus waveforms: a computational framework
title_full_unstemmed	Analysing nystagmus waveforms: a computational framework
title_sort	analysing nystagmus waveforms: a computational framework
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7d896e5e15314fb881a384329bc5dedd
work_keys_str_mv	AT richardvabadi analysingnystagmuswaveformsacomputationalframework AT ozgureakman analysingnystagmuswaveformsacomputationalframework AT gemmaearblaster analysingnystagmuswaveformsacomputationalframework AT richardaclement analysingnystagmuswaveformsacomputationalframework
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Analysing nystagmus waveforms: a computational framework

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