TY - GEN
T1 - Modular Time-Frequency Joint Coding for a Virtual Keyboard Speller Using an SSVEP-Based Brain-Computer Interface
AU - Yang, Hui
AU - Lan, Wenli
AU - He, Jing
AU - Leng, Yue
AU - Wang, Ruimin
AU - Iramina, Keiji
AU - Ge, Sheng
N1 - Funding Information:
ACKNOWLEDGMENT This study was supported by the Fundamental Research Funds for the Central Universities under grants 2242021k30014 and 2242021k30059.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/10/15
Y1 - 2021/10/15
N2 - This paper presents the design of a modular time-frequency joint coding method for steady-state visual evoked potential, in which the stimulus consists of two stages: module flashing and individual flashing. In the first stage, targets are grouped into six-target modules. The modules flash at different frequencies and phases, whereas all targets within the module flash at the same frequency and phase. In the second stage, each target in the module flashes at different frequencies and phases. This coding method is compared with the control method in experiments. The results show that the proposed experimental paradigm performed better; the average accuracy and information transfer rate are higher than those of the control. Specifically, average accuracy is 89.6 ± 8.8%, which is 12.9% higher than that of the control experiment. These results prove the feasibility and superiority of the designed modular time-frequency joint coding method.
AB - This paper presents the design of a modular time-frequency joint coding method for steady-state visual evoked potential, in which the stimulus consists of two stages: module flashing and individual flashing. In the first stage, targets are grouped into six-target modules. The modules flash at different frequencies and phases, whereas all targets within the module flash at the same frequency and phase. In the second stage, each target in the module flashes at different frequencies and phases. This coding method is compared with the control method in experiments. The results show that the proposed experimental paradigm performed better; the average accuracy and information transfer rate are higher than those of the control. Specifically, average accuracy is 89.6 ± 8.8%, which is 12.9% higher than that of the control experiment. These results prove the feasibility and superiority of the designed modular time-frequency joint coding method.
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U2 - 10.1109/ITNEC52019.2021.9587093
DO - 10.1109/ITNEC52019.2021.9587093
M3 - Conference contribution
AN - SCOPUS:85119299780
T3 - IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021
SP - 1300
EP - 1305
BT - IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021
A2 - Xu, Bing
A2 - Mou, Kefen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021
Y2 - 15 October 2021 through 17 October 2021
ER -