Title: EEG control variable algorithm and motion control strategy for toy rail car

Authors: Hongguang Pan; Mei Wang; Xiaokang Wang; Jzau-Sheng Lin

Addresses: School of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China ' School of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China ' School of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China ' Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Abstract: For training the thought concentration ability of hyperactivity sufferers, this paper proposed a kind of electroencephalogram (EEG) control variable extraction method and the motion control strategy. Firstly, the technologies of EEG acquisition from frontal lobe, and the wireless data transmission from the acquisition card to the Pad Phone were realised. Then, through the wavelet Mallat algorithm and FFT to extract the EEG control variable, the accurate controls of start, stop, and running velocity of the toy rail car were implemented. Thirdly, the mathematical model between the velocity and the EEG control variable was established, and then the start threshold, the swerve control and the speed adjust method were accurately designed using this model, so that the delay start and the swerve speed were solved. In addition, the wireless data transmissions among the Pad Phone, the EEG acquisition module and the railelectric potential controller were realised. Finally, it was proved that the proposed EEG control variables and the control strategy effectively fulfil the accurate speed control and the stable motion control.

Keywords: electroencephalogram; EEG; wavelet transform; Mallat algorithm; fast Fourier transform; FFT; motion control.

DOI: 10.1504/IJES.2019.098298

International Journal of Embedded Systems, 2019 Vol.11 No.2, pp.220 - 228

Received: 08 Dec 2016
Accepted: 29 May 2017

Published online: 07 Mar 2019 *

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