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Tremor Signal Analysis for Parkinson’s Disease Detection Using Leap Motion Device

  • Guillermina Vivar-Estudillo
  • Mario-Alberto Ibarra-Manzano
  • Dora-Luz Almanza-Ojeda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11288)

Abstract

Tremor is an involuntary rhythmic movement observed in people with Parkinson’s disease (PD), specifically, hand tremor is a measurement for diagnosing this disease. In this paper, we use hand positions acquired by Leap Motion device for statistical analysis of hand tremor based on the sum and difference of histograms (SDH). Tremor is measured using only one coordinate of the center palm during predefined exercises performed by volunteers at Hospital. In addition, the statistical features obtained with SDH are used to classify tremor signal as with PD or not. Experimental results show that the classification is independent of the hand used during tests, achieving \(98\%\) of accuracy for our proposed approach using different supervised machine learning classifiers. Additionally, we compare our result with others classifiers proposed in the literature.

Keywords

Tremor analysis Parkinson detection SDH method Classification 

Notes

Acknowledgments

Authors gratefully acknowledge all the volunteers at Edmonton Kaye Alberta Clinic, Canada, the Research and Postgraduate studies Support Program (DAIP) by the Universidad de Guanajuato and the Universidad Autónoma “Benito Juárez ”de Oaxaca.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Guillermina Vivar-Estudillo
    • 1
  • Mario-Alberto Ibarra-Manzano
    • 1
  • Dora-Luz Almanza-Ojeda
    • 1
  1. 1.Department of Electronics EngineeringUniversidad de GuanajuatoSalamancaMexico

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