TY - JOUR
T1 - Extraction of high-frequency SSVEP for BCI control using iterative filtering based empirical mode decomposition
AU - Hsu, Chuan Chih
AU - Yeh, Chia Lung
AU - Lee, Wai Keung
AU - Hsu, Hao Teng
AU - Shyu, Kuo Kai
AU - Li, Lieber Po Hung
AU - Wu, Tien Yu
AU - Lee, Po Lei
N1 - Funding Information:
This research is supported by the Ministry of Science and Technology under Grant Number: 108-2634-F-008 -003 through Pervasive Artificial Intelligence Research (PAIR) Labs, Taiwan. This study was also funded by the National Central University , Ministry of Science and Technology 106 -2911-I-008-503 , 106-2221-E-075B-001 ), Taipei Medical University Project ( TMU102-AE1-B09 ), NCU-Landseed Hospital project , Taoyuan Hospital Intramural project ( TYGH104048 , TYGH103061 ).
Funding Information:
This research is supported by the Ministry of Science and Technology under Grant Number: 108-2634-F-008 -003 through Pervasive Artificial Intelligence Research (PAIR) Labs, Taiwan. This study was also funded by the National Central University, Ministry of Science and Technology 106 -2911-I-008-503, 106-2221-E-075B-001), Taipei Medical University Project (TMU102-AE1-B09), NCU-Landseed Hospital project, Taoyuan Hospital Intramural project (TYGH104048, TYGH103061).
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/8
Y1 - 2020/8
N2 - Steady-state visual evoked potential (SSVEP) has been regarded as an efficient way to design a brain computer interface (BCI). Most SSVEP-based BCIs utilize visual stimuli with flashing frequencies lower than 30 Hz, owing to their better signal-to-noise ratio (SNR). However, the practical applications of low-frequency SSVEP-based BCI are limited, because low-frequency SSVEP usually incur uncomfortable visual experience and the risk of photosensitive epilepsy. In contrast, SSVEP-based BCIs using higher stimulation frequencies (>40 Hz) can induce flicker fusion effect for better visualization. In this study, we studied the feasibility of using iterative filtering - empirical mode decomposition (IF-EMD) to implement a BCI cursor system. EEG signals were recorded from dry EEG electrodes with impedance matching circuits. Three stimulation frequencies, designed at 47, 50, and 53 Hz, were chosen to induce high-frequency SSVEPs, in order to control the leftward, forward and rightward movements of the BCI cursor. Ten subjects were recruited, and each subject was requested to complete a control experiment and an application experiment. In the control experiment, subjects were requested to gaze at each flickering target for thirty seconds. In the application experiment, subjects were instructed to move a cursor to reach three targets on a PC screen. The mean accuracy (Acc), command transfer interval (CTI), and information transfer rate (ITR) in the control experiment were 90.7 ± 2.9%, 1.14 ± 0.07 s, and 54.94 ± 5.41 bits/min, respectively. In the application experiment, the mean execution time and CTI were 30.0 ± 4.69 s and 1.50 ± 0.31 s, respectively.
AB - Steady-state visual evoked potential (SSVEP) has been regarded as an efficient way to design a brain computer interface (BCI). Most SSVEP-based BCIs utilize visual stimuli with flashing frequencies lower than 30 Hz, owing to their better signal-to-noise ratio (SNR). However, the practical applications of low-frequency SSVEP-based BCI are limited, because low-frequency SSVEP usually incur uncomfortable visual experience and the risk of photosensitive epilepsy. In contrast, SSVEP-based BCIs using higher stimulation frequencies (>40 Hz) can induce flicker fusion effect for better visualization. In this study, we studied the feasibility of using iterative filtering - empirical mode decomposition (IF-EMD) to implement a BCI cursor system. EEG signals were recorded from dry EEG electrodes with impedance matching circuits. Three stimulation frequencies, designed at 47, 50, and 53 Hz, were chosen to induce high-frequency SSVEPs, in order to control the leftward, forward and rightward movements of the BCI cursor. Ten subjects were recruited, and each subject was requested to complete a control experiment and an application experiment. In the control experiment, subjects were requested to gaze at each flickering target for thirty seconds. In the application experiment, subjects were instructed to move a cursor to reach three targets on a PC screen. The mean accuracy (Acc), command transfer interval (CTI), and information transfer rate (ITR) in the control experiment were 90.7 ± 2.9%, 1.14 ± 0.07 s, and 54.94 ± 5.41 bits/min, respectively. In the application experiment, the mean execution time and CTI were 30.0 ± 4.69 s and 1.50 ± 0.31 s, respectively.
KW - Brain computer interface
KW - Empirical mode decomposition
KW - Iterative filtering
KW - Steady-state visual evoked potential
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U2 - 10.1016/j.bspc.2020.102022
DO - 10.1016/j.bspc.2020.102022
M3 - Article
AN - SCOPUS:85087105267
SN - 1746-8094
VL - 61
JO - Biomedical Signal Processing and Control
JF - Biomedical Signal Processing and Control
M1 - 102022
ER -