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Measurements of Antisaccades Parameters Can Improve the Prediction of Parkinson’s Disease Progression

  • Albert SledzianowskiEmail author
  • Artur Szymanski
  • Aldona Drabik
  • Stanisław Szlufik
  • Dariusz M. Koziorowski
  • Andrzej W. Przybyszewski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11432)

Abstract

In this text we present the results of oculometric experiment consisting the registration of anitsaccades of patients with Parkinson’s Disease (PD) in relation to their neurological data. PD is an important and incurable neurodegenerative disease and we are looking for methods optimizing the treatment. In our previous works we used Reflexive Saccades (RS) and Pursuit Ocular Movements (POM) to check what it can tell us about the disease’s progression expressed in the Unified Parkinson’s Disease Rating Scale (UPDRS). The UPDRS is the most commonly used scale in the clinical studies of Parkinson’s disease. In this experiment we examined antisaccades (AS) of 11 PD patients who performed eye movement tests in controlled conditions. We correlated neurological measurements of patient’s motoric abilities and data describing their treatment with values of AS parameters. We used RSES and for prediction of the UPDRS scoring groups and Weka methods for presentation of the results. We achieved good results with accuracy of 91% and coverage of 100%. The AS test is a relatively easy and non-invasive method that can be used in the telemedicine in the future.

Keywords

Parkinson’s disease Antisaccades Eye tracking Data mining Machine learning 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Albert Sledzianowski
    • 1
    Email author
  • Artur Szymanski
    • 1
  • Aldona Drabik
    • 1
  • Stanisław Szlufik
    • 2
  • Dariusz M. Koziorowski
    • 2
  • Andrzej W. Przybyszewski
    • 1
  1. 1.Polish-Japanese Academy of Information TechnologyWarsawPoland
  2. 2.Neurology, Faculty of Health ScienceMedical University of WarsawWarsawPoland

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