Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1696-1704 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Biomedical Engineering |
| Volume | 65 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2018 |
Keywords
- Brain-computer interface
- electroencephalogram
- harmonic frequency components
- motion stimulus paradigm
- steady-state motion visual evoked potential
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