Linear predictive coding distinguishes spectral EEG features of Parkinson's disease.

Journal: Parkinsonism & related disorders
Published Date: Aug 23, 2020

Abstract

OBJECTIVE: We have developed and validated a novel EEG-based signal processing approach to distinguish PD and control patients: Linear-predictive-coding EEG Algorithm for PD (LEAPD). This method efficiently encodes EEG time series into features that can detect PD in a computationally fast manner amenable to real time applications.

Authors

  • Md Fahim Anjum
    Department of Electrical and Computer Engineering, The University of Iowa, Iowa, USA. Electronic address: mdfahim-anjum@uiowa.edu.
  • Soura Dasgupta
    Department of Electrical and Computer Engineering, The University of Iowa, Iowa, USA; Shandong Academy of Sciences, Shandong, Jinan, China.
  • Raghuraman Mudumbai
    Department of Electrical and Computer Engineering, The University of Iowa, Iowa, USA.
  • Arun Singh
    Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, South Dakota, USA.
  • James F Cavanagh
    Department of Psychology, University of New Mexico, New Mexico, USA.
  • Nandakumar S Narayanan
    Department of Neurology, The University of Iowa, Iowa, USA.

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