TY - JOUR
T1 - Four novel motion paradigms based on steady-state motion visual evoked potential
AU - Yan, Wenqiang
AU - Xu, Guanghua
AU - Xie, Jun
AU - Li, Min
AU - Dan, Ziyan
N1 - Publisher Copyright:
© 1964-2012 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - Objective: The purpose of this paper was to study the applicability of paradigms with motion forms for use in a brain-computer interface (BCI). We examined the performances of different paradigms and evaluated the stimulus effects. Methods: We designed four novel stimulus paradigms based on basic motion modes: swing, rotation, spiral, and radial contraction-expansion. Canonical correlation analysis (CCA) was used to analyze the accuracy. Additionally, we optimized CCA template signal harmonic combinations for the different motion paradigms. Results: The spiral motion paradigm exhibited the highest average information transfer rate (ITR) and recognition accuracy (41.24 bit/min -1 /95.33%), and the average ITRs and recognition accuracies were lowest for the rotation motion paradigm (31.89 bit/min -1 /80.89%) and the radial contraction-expansion motion paradigm (32.62 bit/min -1 /80.72%) because they include fewer harmonic components. Conclusion: Any stimulus paradigms with periodic motion can induce steady-state motion visual evoked potentials (SSMVEPs), but the SSMVEP harmonic components induced by different motion modes differed significantly. The spiral motion paradigm was more suitable for BCI applications. Significance: This study is an important extension to the existing SSMVEP-based BCI literature, and provides new insight to enable future design of the BCI paradigms.
AB - Objective: The purpose of this paper was to study the applicability of paradigms with motion forms for use in a brain-computer interface (BCI). We examined the performances of different paradigms and evaluated the stimulus effects. Methods: We designed four novel stimulus paradigms based on basic motion modes: swing, rotation, spiral, and radial contraction-expansion. Canonical correlation analysis (CCA) was used to analyze the accuracy. Additionally, we optimized CCA template signal harmonic combinations for the different motion paradigms. Results: The spiral motion paradigm exhibited the highest average information transfer rate (ITR) and recognition accuracy (41.24 bit/min -1 /95.33%), and the average ITRs and recognition accuracies were lowest for the rotation motion paradigm (31.89 bit/min -1 /80.89%) and the radial contraction-expansion motion paradigm (32.62 bit/min -1 /80.72%) because they include fewer harmonic components. Conclusion: Any stimulus paradigms with periodic motion can induce steady-state motion visual evoked potentials (SSMVEPs), but the SSMVEP harmonic components induced by different motion modes differed significantly. The spiral motion paradigm was more suitable for BCI applications. Significance: This study is an important extension to the existing SSMVEP-based BCI literature, and provides new insight to enable future design of the BCI paradigms.
KW - Brain-computer interface
KW - electroencephalogram
KW - harmonic frequency components
KW - motion stimulus paradigm
KW - steady-state motion visual evoked potential
UR - https://www.scopus.com/pages/publications/85050452575
U2 - 10.1109/TBME.2017.2762690
DO - 10.1109/TBME.2017.2762690
M3 - 文章
C2 - 29035204
AN - SCOPUS:85050452575
SN - 0018-9294
VL - 65
SP - 1696
EP - 1704
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 8
ER -