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  • 教师姓名: 谢俊
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  • 所在单位: 机械工程学院
  • 学历: 博士研究生毕业
  • 办公地点: 西安交通大学曲江校区西五楼A209室;
    西安交通大学创新港校区2号巨构3175室。
  • 性别: 男
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  • 学位: 博士
  • 职称: 教授
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  • 硕士生导师: 是

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Four Novel Motion Paradigms Based on Steady-State Motion Visual Evoked Potential

发布时间:2025-04-30
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发布时间:
2025-04-30
论文名称:
Four Novel Motion Paradigms Based on Steady-State Motion Visual Evoked Potential
发表刊物:
IEEE Transactions on Biomedical Engineering
摘要:
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.
合写作者:
Wenqiang Yan, Guanghua Xu, Jun Xie, Min Li and Ziyan Dan
是否译文:
发表时间:
2017-10-13