Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)

<Previous Article In Volume
Next Article In Volume>

Hand and Foot Movement of Motor Imagery Classification Using Wavelet Packet Decomposition and Multilayer Perceptron Backpropagation

Authors
Prasetyo Cahyo Nugroho, Rahmat Widadi, Dodi Zulherman
Corresponding Author
Dodi Zulherman
Available Online 11 August 2021.
DOI
10.2991/aer.k.210810.042How to use a DOI?
Keywords
EEG, Motor Imagery, Wavelet Packet Decomposition, MLP-BP
Abstract

The development of bionic aids for paralyzed patients leads to the Brain-Computer Interface (BCI) implementation with various obstacles, especially in interpreting brain signals as triggers for the bionic organ. The reading of electrical signal activity in the brain in the BCI system uses electroencephalography (EEG) signal, which comes from many electrodes in the head area and is non-stationary. The measured EEG signal contains much information, including information for the hands and feet motor imagery, so a classification system is needed to separate the information to be processed, such as hand and foot movements. This research aims to develop an imagery motor classification system for the hands and feet so that signals can be classified correctly. The system design is made through several stages of the signal processing process consisting of the pre-processing stage using centering, the feature extraction stage with wavelet packet decomposition (WPD), and multilayer perceptron back-propagation (MLP-BP) as the classifier. Based on the result, this study got the highest accuracy value, about 26.8% at level three, and gain above 0.02. This small accuracy is due to the large error due to under fitting.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)
Series
Advances in Engineering Research
Publication Date
11 August 2021
ISBN
10.2991/aer.k.210810.042
ISSN
2352-5401
DOI
10.2991/aer.k.210810.042How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Prasetyo Cahyo Nugroho
AU  - Rahmat Widadi
AU  - Dodi Zulherman
PY  - 2021
DA  - 2021/08/11
TI  - Hand and Foot Movement of Motor Imagery Classification Using Wavelet Packet Decomposition and Multilayer Perceptron Backpropagation
BT  - Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)
PB  - Atlantis Press
SP  - 248
EP  - 252
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.210810.042
DO  - 10.2991/aer.k.210810.042
ID  - Nugroho2021
ER  -