Abstract
Background: Recent EEG-SSVEP signal based BCI studies have used high frequency square pulse visual stimuli to reduce subjective fatigue. However, the effect of total harmonic distortion (THD) has not been considered. Compared to CRT and LCD monitors, LED screen displays high-frequency wave with better refresh rate. In this study, we present high frequency sine wave simple and rhythmic patterns with low THD rate by LED to analyze SSVEP responses and evaluate subjective fatigue in normal subjects.Materials and Methods: We used patterns of 3-sequence high-frequency sine waves (25, 30, and 35 Hz) to design our visual stimuli. Nine stimuli patterns, 3 simple (repetition of each of above 3 frequencies e.g., P25-25-25) and 6 rhythmic (all of the frequencies in 6 different sequences e.g., P25-30-35) were chosen. A hardware setup with low THD rate (<0.1%) was designed to present these patterns on LED. Twenty two normal subjects (aged 23–30 (25 ± 2.1) yrs) were enrolled. Visual analog scale (VAS) was used for subjective fatigue evaluation after presentation of each stimulus pattern. PSD, CCA, and LASSO methods were employed to analyze SSVEP responses. The data including SSVEP features and fatigue rate for different visual stimuli patterns were statistically evaluated.Results: All 9 visual stimuli patterns elicited SSVEP responses. Overall, obtained accuracy rates were 88.35% for PSD and > 90% for CCA and LASSO (for TWs > 1 s). High frequency rhythmic patterns group with low THD rate showed higher accuracy rate (99.24%) than simple patterns group (98.48%). Repeated measure ANOVA showed significant difference between rhythmic pattern features (P < 0.0005). Overall, there was no significant difference between the VAS of rhythmic [3.85 ± 2.13] compared to the simple patterns group [3.96 ± 2.21], (P = 0.63). Rhythmic group had lower within group VAS variation (min = P25-30-35 [2.90 ± 2.45], max = P35-25-30 [4.81 ± 2.65]) as well as least individual pattern VAS (P25-30-35).Discussion and Conclusion: Overall, rhythmic and simple pattern groups had higher and similar accuracy rates. Rhythmic stimuli patterns showed insignificantly lower fatigue rate than simple patterns. We conclude that both rhythmic and simple visual high frequency sine wave stimuli require further research for human subject SSVEP-BCI studies.
Highlights
A brain computer interface (BCI) interprets human brain activities as a control signal to make direct communication between the brain and external devices (Alonso et al, 2012)
We have shown the matrix of mean values of coefficients amplitude (Supplementary Tables S2, S3) that illustrate differences in the ascending, descending and zigzag trends in rhythmic and the simple patterns
At lower frequency ranges (∼8 Hz), the risk of photosensitive epileptic seizures and high fatigue rate have to be considered. These two main challenges encouraged researchers to carry out state visual evoked potential (SSVEP) studies at high frequency range
Summary
A brain computer interface (BCI) interprets human brain activities as a control signal to make direct communication between the brain and external devices (Alonso et al, 2012). Non-invasive modalities such as EEG measurement provide a common solution in BCI studies and applications. P300 (Middendorf et al, 2000; Chang et al, 2016), visual evoked potential (VEP) (Wang et al, 2008; Bin et al, 2009a, 2011; Guger et al, 2012; Nezamfar et al, 2016; Zhao et al, 2017), slow cortical potentials (SCP) (Birbaumer et al, 1999) and sensorimotor rhythms (Pfurtscheller et al, 2000) are the common signals used for EEG-based BCIs. Recent EEG-SSVEP signal based BCI studies have used high frequency square pulse visual stimuli to reduce subjective fatigue. We present high frequency sine wave simple and rhythmic patterns with low THD rate by LED to analyze SSVEP responses and evaluate subjective fatigue in normal subjects
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