Min Hye Chang1, Jeong Su Lee1, Jeong Heo1, Kwang Suk Park2. 1. Interdisciplinary Program for Bioengineering, Seoul National University, Seoul, Republic of Korea. 2. Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, Republic of Korea. Electronic address: pks@bmsil.snu.ac.kr.
Abstract
BACKGROUND: Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) generate weak SSVEP with a monitor and cannot use harmonic frequencies, whereas P300-based BCIs need multiple stimulation sequences. These issues can decrease the information transfer rate (ITR). NEW METHOD: In this paper, we introduce a novel hybrid SSVEP-P300 speller that generates dual-frequency SSVEP, allowing it to overcome the abovementioned limitations and improve the performance. The hybrid speller consists of nine panels flickering at different frequencies. Each panel contains four different characters that appear in a random sequence. The flickering panel and the periodically updating character evoke the dual-frequency SSVEP, while the oddball stimulus of the target character evokes the P300. A canonical correlation analysis (CCA) and a step-wise linear discriminant analysis (SWLDA) classified SSVEP and P300, respectively. Ten subjects participated in offline and online experiments, in which accuracy and ITR were compared with those of conventional SSVEP and P300 spellers. RESULTS: The offline analysis revealed not only the P300 potential but also SSVEP with peaks at sub-harmonic frequencies, demonstrating that the proposed speller elicited dual-frequency SSVEP. This dual-frequency stimulation improved SSVEP recognition, increased the number of targets by employing harmonic frequencies, reduced the stimulation time for P300, and consequently improved ITR as compared to the conventional spellers. COMPARISON WITH EXISTING METHODS: The new method reduces the stimulation time and allows harmonic frequencies to be employed for different stimuli. CONCLUSIONS: The results indicate that this study provides a promising approach to make the BCI speller more reliable and efficient.
BACKGROUND: Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) generate weak SSVEP with a monitor and cannot use harmonic frequencies, whereas P300-based BCIs need multiple stimulation sequences. These issues can decrease the information transfer rate (ITR). NEW METHOD: In this paper, we introduce a novel hybrid SSVEP-P300 speller that generates dual-frequency SSVEP, allowing it to overcome the abovementioned limitations and improve the performance. The hybrid speller consists of nine panels flickering at different frequencies. Each panel contains four different characters that appear in a random sequence. The flickering panel and the periodically updating character evoke the dual-frequency SSVEP, while the oddball stimulus of the target character evokes the P300. A canonical correlation analysis (CCA) and a step-wise linear discriminant analysis (SWLDA) classified SSVEP and P300, respectively. Ten subjects participated in offline and online experiments, in which accuracy and ITR were compared with those of conventional SSVEP and P300 spellers. RESULTS: The offline analysis revealed not only the P300 potential but also SSVEP with peaks at sub-harmonic frequencies, demonstrating that the proposed speller elicited dual-frequency SSVEP. This dual-frequency stimulation improved SSVEP recognition, increased the number of targets by employing harmonic frequencies, reduced the stimulation time for P300, and consequently improved ITR as compared to the conventional spellers. COMPARISON WITH EXISTING METHODS: The new method reduces the stimulation time and allows harmonic frequencies to be employed for different stimuli. CONCLUSIONS: The results indicate that this study provides a promising approach to make the BCI speller more reliable and efficient.