Preliminary Comparative Experiments of Support Vector Machine and Neural Network for EEG-based BCI Mobile Robot Control
- Yasushi Bandou, Takuya Hayakawa, Jun Kobayashi*Department of Systems Design and Informatics, Kyushu Institute of Technology, Iizuka 820-8502, Japan*Corresponding author. Email: email@example.com
- Corresponding Author
- Jun Kobayashi
- https://doi.org/10.2991/jrnal.k.190220.014How to use a DOI?
- Brain computer interface, electroencephalography, support vector machine, neural network, mobile robot control
Here we present experimental results of Electroencephalogram (EEG)-based Brain Computer Interface (BCI) for mobile robot control by means of Support Vector Machine (SVM) and Neural Network (NN). The authors had trained NNs using EEGs collected from subjects and verified the performance as BCI; however, the results were unsatisfactory for practical use. In this study, we have used SVM with Radial Basis Function (RBF) kernel function for further improvement and compared the performance with the NNs. Consequently, the SVMs outperformed the NNs in almost all cases.
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Yasushi Bandou AU - Takuya Hayakawa AU - Jun Kobayashi PY - 2019 DA - 2019/03/30 TI - Preliminary Comparative Experiments of Support Vector Machine and Neural Network for EEG-based BCI Mobile Robot Control JO - Journal of Robotics, Networking and Artificial Life SP - 269 EP - 272 VL - 5 IS - 4 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.k.190220.014 DO - https://doi.org/10.2991/jrnal.k.190220.014 ID - Bandou2019 ER -