A deep learning approach for Parkinson’s disease diagnosis from EEG signals

  • Shu Lih Oh
  • Yuki Hagiwara
  • U. Raghavendra
  • Rajamanickam Yuvaraj
  • N. Arunkumar
  • M. Murugappan
  • U. Rajendra AcharyaEmail author
S.I. : Computer aided Medical Diagnosis


An automated detection system for Parkinson’s disease (PD) employing the convolutional neural network (CNN) is proposed in this study. PD is characterized by the gradual degradation of motor function in the brain. Since it is related to the brain abnormality, electroencephalogram (EEG) signals are usually considered for the early diagnosis. In this work, we have used the EEG signals of twenty PD and twenty normal subjects in this study. A thirteen-layer CNN architecture which can overcome the need for the conventional feature representation stages is implemented. The developed model has achieved a promising performance of 88.25% accuracy, 84.71% sensitivity, and 91.77% specificity. The developed classification model is ready to be used on large population before installation of clinical usage.


Computer-aided detection system Convolutional neural network Deep learning Parkinson’s disease 


Compliance with ethical standards

Conflict of interest

The authors declared no conflict of interest in this work.


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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  • Shu Lih Oh
    • 1
  • Yuki Hagiwara
    • 1
  • U. Raghavendra
    • 2
  • Rajamanickam Yuvaraj
    • 3
  • N. Arunkumar
    • 4
  • M. Murugappan
    • 5
  • U. Rajendra Acharya
    • 1
    • 6
    • 7
    Email author
  1. 1.Department of Electronics and Computer EngineeringNgee Ann PolytechnicSingaporeSingapore
  2. 2.Department of Instrumentation and Control Engineering, Manipal Institute of TechnologyManipal Academy of Higher EducationManipalIndia
  3. 3.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  4. 4.Department of Electronics and InstrumentationSASTRA UniversityThanjavurIndia
  5. 5.Kuwait College of Science and TechnologyDohaKuwait
  6. 6.Department of Biomedical Engineering, School of Science and TechnologySingapore University of Social SciencesSingaporeSingapore
  7. 7.School of Medicine, Faculty of Health and Medical SciencesTaylor’s UniversitySubang JayaMalaysia

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