# Automating Stimulation Frequency Selection for SSVEP-Based Brain-Computer Interfaces
## 6 Discussion  
In this study, to determine individual stimulation frequencies, we used criteria such as the reaction onset speed in response to presented visual stimuli, the capacity to maintain a consistent response at an acceptable level during continuous visual stimuli presentation, and user satisfaction with the presented photostimulus to identify individual stimulation frequencies. For this purpose, we proposed a number of coefficients based on the SNR and theta-to-beta power ratio:  
1. Reaction reaction speed coefficient \(K_{sp}\);
2. Threshold overcoming coefficient \(K_{o}\);
3. Frequency applicability coefficient \(K_{fa}\);
4. Discomfort coefficient \(K_{d}\). Each coefficient serves as a quantitative measure, ranging from 0 to 1, which characterizes the extent to which the stimulation frequency is suitable for the subject in terms of various factors, including the response onset speed to the presented photostimuli, the stability of the response, the overall applicability of the frequency, and the level of induced stress. Notably, our study utilized these coefficients to account for subject responses, not only at the fundamental frequency but also at the second harmonic of the photostimulus frequency. This approach enabled the identification of frequencies that may have elicited weak responses at the fundamental frequency but demonstrated favorable outcomes at the second harmonic. The results of calculating these coefficients in Section 5.2 demonstrate the highly individualized response of each subject to the presented photostimuli. To facilitate working with the obtained coefficients, we developed a special application described in Section 5.3. With the help of this application, the user can adjust the desired threshold values of the calculated coefficients and automatically obtain a set of photostimulus frequencies most appropriate for a particular subject. During the course of this study, notable variations in SSVEP response were observed among subjects. In certain instances, the reaction was indistinguishable, while in others, the reaction was only significant on the fundamental frequency or subharmonic frequency. These findings indicate that an individualized approach may be necessary, as certain frequencies may not be suitable for all patients, but this does not preclude the possibility of other frequencies being effective. Additionally, some subjects exhibited more pronounced responses to subharmonics, suggesting that incorporating subharmonics into SSVEP may enhance the accessibility of SSVEP-BCI. It is crucial to situate the findings of our study within the broader context of previous studies and obtain results. For example, in the study by [PERSON] et al., the researchers aimed to determine the SSVEP response curve, which represented the magnitude of the evoked signal based on frequency. They induced the SSVEP response using a wide range of frequencies (5-30 Hz) and collected data from 10 subjects. The main finding of the study was the identification of the optimal frequency range (12-18 Hz) for detecting SSVEP [31]. The authors of another relevant paper successfully used a filter bank canonical correlation analysis to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs [55]. In line with these findings, the results of our study point to the same range for optimal stimulation frequencies, encompassing high alpha and low beta EEG frequency bands. However, within this optimal range, different subjects have their own most suitable frequencies at which the speed and stability of the evoked SSVEP potential are high enough. Furthermore, we demonstrated that considering not only the fundamental frequency of the photostimulation but also the second harmonic frequency improved the estimation of the reaction onset rate and stability of the SSVEP response. This approach enabled us to account for individual user characteristics and extend the frequency range, particularly in the low-frequency range, where the signal-to-noise ratio may be compromised.