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Nonlinear Dynamics of the Human Smooth Pursuit System in Health and Disease: Model Structure and Parameter Estimation
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0002-6608-250x
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Oculomotor tests (OMT) are administered to quantify symptoms in neurological and mental diseases. Eye movements in response to displayed visual stimuli are registered by an digital video-based eye tracker and processed. Stimuli of simple signal form, e.g. sine waves, are traditionally used in medical practice to test the performance of the oculomotor system in smooth pursuit (SP). The calculated SP gain and the phase shift at the frequency in question are then presented as the test outcome. This paper revisits the problem of quantifying the SP dynamics from eye-tracking data by means of nonlinear system identification. First, a sparse Volterra-Laguerre (VL) model is estimated from an OMT with sufficiently exciting (in frequency and amplitude) stimuli. Then the structure and initial parameter estimates of a polynomial Wiener model (WM) are obtained from the kernel estimates of the VL model. Finally, the parameter distributions of the WM are inferred by a particle filter (PF). In the proposed approach, the performance of the PF is improved by the individualized sparse model structure. Experimental data show that the latter captures the alternations in the SP dynamics due to aging and in Parkinson’s disease.

Place, publisher, year, edition, pages
2017. 1-6 p.
National Category
Other Medical Engineering Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-334957OAI: oai:DiVA.org:uu-334957DiVA: diva2:1161244
Conference
56th IEEE Conference on Decision and Control, December 12-15, 2017, Melbourne, Australia
Available from: 2017-11-29 Created: 2017-11-29 Last updated: 2017-12-05Bibliographically approved

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Bro, ViktorMedvedev, Alexander

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
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More languages
Output format
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