This study presents a new steady-state visual evoked potential (SSVEP) paradigm for brain computer interface (BCI) systems. The goal of this study is to increase the number of targets using fewer stimulation high frequencies, with diminishing subject’s fatigue and reducing the risk of photosensitive epileptic seizures. The new paradigm is High-Frequency Combination Coding-Based High-Frequency Steady-State Visual Evoked Potential (HFCC-SSVEP).Firstly, we studied SSVEP high frequency(beyond 25 Hz)response of SSVEP, whose paradigm is presented on the LED. The SNR (Signal to Noise Ratio) of high frequency(beyond 40 Hz) response is very low, which is been unable to be distinguished through the traditional analysis method; Secondly we investigated the HFCC-SSVEP response (beyond 25 Hz) for 3 frequencies (25Hz, 33.33Hz, and 40Hz), HFCC-SSVEP produces nn with n high stimulation frequencies through Frequence Combination Code. Further, Animproved Hilbert-huang transform (IHHT)-based variable frequency EEG feature extraction method and a local spectrum extreme target identification algorithmare adopted to extract time-frequency feature of the proposed HFCC-SSVEP response.Linear predictions and fixed sifting (iterating) 10 time is used to overcome the shortage of end effect and stopping criterion,generalized zero-crossing (GZC) is used to compute the instantaneous frequency of the proposed SSVEP respondent signals, the improved HHT-based feature extraction method for the proposed SSVEP paradigm in this study increases recognition efficiency, so as to improve ITR and to increase the stability of the BCI system. what is more, SSVEPs evoked by high-frequency stimuli (beyond 25Hz) minimally diminish subject’s fatigue and prevent safety hazards linked to photo-induced epileptic seizures, So as to ensure the system efficiency and undamaging.This study tests three subjects in order to verify the feasibility of the proposed method.
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10 March 2015
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014)
22–28 September 2014
Rhodes, Greece
Research Article|
March 10 2015
High-frequency combination coding-based steady-state visual evoked potential for brain computer interface
Feng Zhang;
Feng Zhang
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Guang-Hua Xu;
Guang-Hua Xu
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
bState Key Laboratory for Manufacturing Systems Engineering,
Xi’an Jiaotong University
, Xi’an 710054, China
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Xin Zhang;
Xin Zhang
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Jun Xie;
Jun Xie
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Yeping Li;
Yeping Li
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Chengcheng Han;
Chengcheng Han
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Li Lili;
Li Lili
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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Jing Wang
Jing Wang
aSchool of Mechanical Engineering,
Xi’an Jiaotong University
, Xi’an 710049, China
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AIP Conf. Proc. 1648, 850136 (2015)
Citation
Feng Zhang, Guang-Hua Xu, Xin Zhang, Jun Xie, Yeping Li, Chengcheng Han, Li Lili, Jing Wang; High-frequency combination coding-based steady-state visual evoked potential for brain computer interface. AIP Conf. Proc. 10 March 2015; 1648 (1): 850136. https://doi.org/10.1063/1.4913191
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