DocumentCode :
140282
Title :
Hybrid frequency and phase coding for a high-speed SSVEP-based BCI speller
Author :
Xiaogang Chen ; Yijun Wang ; Nakanishi, Masaki ; Tzyy-Ping Jung ; Xiaorong Gao
Author_Institution :
Dept. of Biomed. Eng., Tsinghua Univ., Beijing, China
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
3993
Lastpage :
3996
Abstract :
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of hybrid frequency and phase coding methods in multi-target SSVEP-based BCIs. Specifically, this study compared two hybrid target-coding strategies: (1) mixed frequency and phase coding, and (2) joint frequency and phase coding. In a simulated online BCI experiment using a 40-target BCI speller, BCI performance for both coding approaches were tested with a group of six subjects. At a spelling speed of 40 characters per minute (1.5 seconds per character), both approaches obtained high information transfer rates (ITR) (mixed coding: 172.37±28.67 bits/min, joint coding: 170.94±28.32 bits/min) across subjects. There was no statistically significant difference between the two approaches (p>0.05). These results suggest that the hybrid frequency and phase coding methods are highly efficient for multi-target coding in SSVEP BCIs with a large number of classes, providing a practical solution to implement a high-speed BCI speller.
Keywords :
brain-computer interfaces; phase coding; visual evoked potentials; brain-computer interfaces; frequency coding methods; high-speed BCI speller; high-speed SSVEP-based BCI speller; hybrid target-coding strategy; online BCI experiment; phase coding methods; steady-state visual evoked potential; Accuracy; Brain-computer interfaces; Encoding; Joints; Monitoring; Training; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944499
Filename :
6944499
Link To Document :
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