Deep Neural Network Model for Automated Detection of Alzheimer’s Disease using EEG Signals

Authors

  • Atharva Deshmukh Ramaiah Institute of Technology, Bengaluru, India
  • Dr. Maya V. Karki Ramaiah Institute of Technology, Bengaluru, India
  • Bhuvan S R Ramaiah Institute of Technology, Bengaluru, India
  • Gaurav S Ramaiah Institute of Technology, Bengaluru, India
  • Hitesh JP Ramaiah Institute of Technology, Bengaluru, India

DOI:

https://doi.org/10.3991/ijoe.v18i08.29867

Keywords:

EEG, Alzheimer's Disease, Discrete Wavelet Transform, Convolutional Neural Networks, CNN, Support Vector Machine, K-Nearest Neighbours, SVM, KNN, Generative Adversarial Networks, CTGAN, LSTM, Long Short Term Memory, Electroencephalography, Filters, Statistical Features

Abstract


Our brain is our body’s control centre and is essential for proper functioning of the body. Alzheimer’s disease is a chronic neurodegenerative disease that affects the cerebral cortex of the brain and causes memory loss and loss of cognitive thinking. EEG (Electroencephalography) is a method of recording neurological electrical activity with electrodes. It was chosen as it is a simple, painless procedure. This paper suggests an automated and accurate algorithm for the detection of Alzheimer's Disease using EEG signals with a combination of Signal processing and Deep Learning Methods. Concepts like Butterworth filters, DWT, statistical parameters, Data Augmentation and CNN were used in order to achieve a classification algorithm with high accuracy. A total highest  system  accuracy of 97.61% was achieved.

Author Biographies

Atharva Deshmukh, Ramaiah Institute of Technology, Bengaluru, India

Department of Electronics and Communications Engineering, Ramaiah Institute of Technology, Bengaluru, India

Dr. Maya V. Karki, Ramaiah Institute of Technology, Bengaluru, India

Head of Department, Electronics and Communications Engineering, Ramaiah Institute of Technology, Bengaluru, India

Bhuvan S R, Ramaiah Institute of Technology, Bengaluru, India

Department of Electronics and Communications Engineering, Ramaiah Institute of Technology, Bengaluru, India

Gaurav S, Ramaiah Institute of Technology, Bengaluru, India

Department of Electronics and Communications Engineering, Ramaiah Institute of Technology, Bengaluru, India

Hitesh JP, Ramaiah Institute of Technology, Bengaluru, India

Department of Electronics and Communications Engineering, Ramaiah Institute of Technology, Bengaluru, India

Covr iJOE Vol. 18 No. 08 (2022)

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Published

2022-06-28

How to Cite

Deshmukh, A., Karki, M., S R, B., S, G., & JP, H. (2022). Deep Neural Network Model for Automated Detection of Alzheimer’s Disease using EEG Signals. International Journal of Online and Biomedical Engineering (iJOE), 18(08), pp. 115–126. https://doi.org/10.3991/ijoe.v18i08.29867

Issue

Vol. 18 No. 08 (2022)

Section

Papers

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Copyright (c) 2022 Atharva Deshmukh, Dr. Maya V. Karki, Bhuvan S R, Gaurav S, Hitesh JP

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.