## 3 Results and Discussion
### Signal Characterization
[PERSON], [PERSON], and [PERSON] [53] used the logistic map in the chaotic behavior threshold to obtain the entropic q-index for different values of initial conditions and found that C(N) always presented values around one. Thus, complexity values next to one might indicate that bovine brain signals also have chaotic components. The presented results demonstrate that it is possible to noninvasively acquire brain signals from animals that are free from sedation and have the freedom to move. Future improvements to this method could encompass augmenting the number of animals and enhancing signal acquisition during distinct behaviors (eating, drinking water, chewing, standing, lying down, or walking) to facilitate the association of these behaviors with signal features. Moreover, it holds significance to meticulously characterize the activities undertaken by the animal, particularly during the prolonged process of rumination, during which the animal's extended engagement can potentially impact muscular movements, consequently influencing the recorded signal. The integration of imaging techniques \begin{table}
\begin{tabular}{c c} \hline \hline
**Sequence** & **C(N)** \\ \hline S1 = [0 1 0 1 0 1 0 1 0 \ldots 1 0 1 0 1 0 1 0 1 0 1 ] & 0.0202 \\ \hline S2 = sin(2\(\pi\)30t) & 0.0559 \\ \hline S3 = sin(2\(\pi\)0.5t) + sin(2\(\pi\)10t) + sin(2\(\pi\)18t) + sin(2\(\pi\)30t) + sin(2\(\pi\)30t) & 0.0129 \\ \hline S4 = sin(2\(\pi\)0.5t) + sin(2\(\pi\)10t) + sin(2\(\pi\)18t) + sin(2\(\pi\)30t) + sin(2\(\pi\)30t) & 1.0000 \\ + (array of random numbers) & & \\ \hline S5 = white noise & 0.9957 \\ \hline S6 = array of random numbers & 1.0870 \\ \hline S7 = logistic map in chaos threshold value [53] & 1.0000 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: [PERSON] and [PERSON] normalized complexity C(N) for different time series. \begin{table}
\begin{tabular}{c c} \hline \hline
**Sequence** & **C(N)** \\ \hline Climatic chamber 1 st section (size: 4 s) & 0.9894 \\ \hline Climatic chamber 2 nd section (size: 4 s) & 0.6596 \\ \hline Climatic chamber 3 rd section (size: 4 s) & 0.7483 \\ \hline Climatic chamber 4 th section (size: 4 s) & 0.7475 \\ \hline Climatic chamber 5 th section (size: 9 s) & 0.5857 \\ \hline Pasture 1 st section (size: 240 s) & 0.6078 \\ \hline Pasture 2 nd section (size: 15 s) & 0.6163 \\ \hline Pasture 3 rd section (size: 3 s) & 0.8656 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Normalized complexity C(N) for artifact-free signal sections. to monitor this activity would offer a valuable opportunity for further insight. Another point for the future is to handle artifacts automatically, given that this is a time-consuming stage of signal processing. In terms of equipment and signal acquisition, future enhancements should consider expanding the acquisition range to enable data collection in larger areas and improving the battery autonomy for extended experiment durations. However, the central focus remains on refining the electrode fixation techniques, even accounting for complete hair removal, area cleaning, and the use of EEG conductive paste, as the utilization of surface electrodes in these longer experiments remains a challenge.