# Eye State Identification Based on Discrete Wavelet Transforms
## 4 Materials and Methods  
To evaluate the suitability of the proposed system, we have carried out a series of experiments with a participant group who agreed to participate in the research. This participant group included a total of 7 volunteers with an average age of 29.67 (range 24-56). The participants indicated that they do not have hearing or visual impairments. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Levels** & **Frequency Band (Hz)** & **EEG Rhyth** & **Decomposition Level** \\ \hline D1 & 50–100 & Noise & 1 \\ D2 & 25–50 & Beta-Gamma & 2 \\ D3 & 12.50–25 & Beta & 3 \\ D4 & 6.25–12.50 & Theta-Alpha & 4 \\ A4 & 0–6.25 & Delta-Theta & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Wavelet coefficients and EEG rhythm equivalence. Participation was voluntary and informed consent was obtained for each participant in order to employ their EEG data in our study. Our EEG prototype was used to capture the brain activity of the subjects. Gold cup electrodes were placed in accordance with the 10-20 international system for electrode placement [54] and attached to the subjects scalp using a conductive paste. Electrode-skin impedances were below 15 k\(\Omega\) at all electrodes. Several studies have proved that the alpha rhythm predominates in the occipital area of the brain when subjects remain with their eyes closed and it is reduced when visual stimulation takes place [55; 56; 57]. In accordance with these works, the input channels of the EEG devices were located in the O1 and O2 positions. Moreover, to optimize the setup time and EEG signal quality, the reference and ground electrodes were placed in the FP2 and A1 positions, respectively, where the absence of hair facilitates its placement [58] (see Figure 4). All the experiments were conducted in a sound-attenuated and controlled environment. Participants were seated in a comfortable chair, and asked to be relaxed and focused on the task, trying to avoid any distraction or external stimulus. Experiments were composed of 2 tasks: the first one, 60 s of OE and the second, 60 s of CE. In order to simulate a real-life situation, the subject could freely move his gaze during the eye-open tasks, without the need to keep it at a fixed point. The procedure was conveniently explained in advance allowing the participants to feel comfortable and familiar with the test environment. Moreover, possible artifacts were minimized by asking them not to speak, move or blink (or at least as little as possible) throughout the OE task. Electrode-skin impedance was below 15 k\(\Omega\) at all the electrodes. A total of 10 tasks (i.e., 10 min) were continuously recorded for each participant, which corresponds to 5 tasks of OE and 5 tasks of CE. Each task was separated by a sound alert, which indicated the user to change the state. All the experiments started with OE as the initial state (see Figure 5). The captured signals were filtered between 4 and 40 Hz and the mean of the signal was subtracted. Since an essential feature of our study is to provide a reliable system with high accuracy rates, several types of wavelets, already used in previous works for EEG analysis, were evaluated and compared for extracting the features. In particular, nine types of wavelets were tested: db2, db4, db8, coif1, coif4, haar, sym2, sym4, and sym10. Moreover, overlapped windows have been used for extracting the features. We have considered time windows of \(D\) seconds and an overlapped time slot of \(d\) seconds. It is important to note that, using this technique, the response time of the system is directly related to \(D\) and \(d\), i.e., the decision delay, which is the wait time for a new classifier decision, is given by \(D-d\) s. Hence, in order to find the shortest response time with a reliable accuracy rate, we have evaluated our system using several window sizes, ranging  
Figure 4: Anatomical electrode distribution in accordance with the standard 10–20 placement system used during the electroencephalography measurements.