A brain-wave-actuated small robot car using ensemble empirical mode decomposition-based approach

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Title:	A brain-wave-actuated small robot car using ensemble empirical mode decomposition-based approach
Authors:	李柏磊;Lee, Po-Lei;Chang, Hsiang-Chih;Hsieh, Tsung-Yu;Deng, Hua-Ting;Sun, Chia-Wei
Contributors:	資訊電機學院電機工程學系
Keywords:	Brain computer interface (BCI);Brain computer interfaces;Electroencephalography;Empirical mode decomposition;ensemble empirical mode decomposition (EEMD);Matched filters;Robots;Steady-state;steady-state visual evoked potential (SSVEP);Visualization
Date:	2012-03-12
Issue Date:	2026-04-23 13:16:22 (UTC+8)
Publisher:	Institute of Electrical and Electronics Engineers Inc.;IEEE
Abstract:	摘要： An ensemble empirical mode decomposition (EEMD)-based approach was developed to extract steady-state visual evoked potentials (SSVEPs) for wireless handling of a small robot car. Three visual stimuli, flickering at 13, 14, and 15 Hz, were displayed on a liquid crystal display monitor to induce user's SSVEPs. The induced SSVEPs were used to control three movement functions (forward, left, and right) of the small robot car. Users gazed at one chosen visual stimulus at one time, and the induced SSVEP was recognized to activate the desired movement function. In this paper, all subjects were requested to handle the small robot car to complete an S-shaped course four times. The proposed system utilized only one electroencephalography (EEG) channel placed at the Oz position. The acquired EEG signals were first segmented into 1-s epochs, and each epoch was then decomposed by EEMD into a series of oscillation components, denoted as intrinsic oscillatory functions (IOFs), representing multiscale features of the recorded signal. The SSVEP-related IOFs were then recognized using a matched filter detector (MFD), including a matched filter demodulator and an amplitude detector. The visual stimulus, which contributed maximum power to the MFD, was recognized as the gazed target. In this paper, all subjects could actuate the small robot car using the proposed EEMD-based brain computer interface system to complete an S-shaped course four times; the mean execution time, number of valid detections, and command transfer interval over the 11 subjects were 84.5 s, 51.13 commands, and 1.65 s/command, respectively. 其他題名： TSMCA 出版者： IEEE 出版日期： 2012-09-01 出處： IEEE transactions on systems, man and cybernetics. Part A, Systems and humans, 2012-09, Vol.42 (5), p.1053-1064 資源來源： IEEE Electronic Library (IEL) 識別號： ISSN: 1083-4427 識別號： EISSN: 1558-2426 識別號： DOI: 10.1109/TSMCA.2012.2187184 識別號： CODEN: ITSHFX
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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