## 4 Discussion
### Limitations and Future Research  
Several limitations of this study warrant careful consideration. Primarily, an enhancement of the data acquisition apparatus is suggested, as it sporadically introduces substantial noise and extraneous data into the measurements, potentially resulting in inaccurate values. Nevertheless, as a preliminary step towards wireless signal acquisition, the current device's performance is satisfactory. Furthermore, there are ample opportunities to enhance the code's efficiency, speed, and accuracy. The emotion induction protocol could be refined by integrating alternative methods, such as auditory stimulation or personalized replication, and by providing a more immersive experience within the script-driven imagery protocol. The machine learning model utilized in this research could also benefit from an expanded sample size. Augmenting group heterogeneity through various validation and data partitioning techniques, including \(k\)-fold cross-validation, bootstrap, and leave-one-out (LOO), would likely enhance the model's robustness and generalizability. Furthermore,  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Dataset** & **Clinical Metric** & **Stratified \(k\)-Fold** & **Train–Test Split** \\ \hline \multirow{2}{*}{Combined Dataset} & Sensitivity & 0.80 & 0.43 \\  & Specificity & 0.83 & 0.52 \\ \hline \multirow{2}{*}{Emotional Dataset} & Sensitivity & 0.88 & 0.55 \\  & Specificity & 0.95 & 0.73 \\ \hline \multirow{2}{*}{Neutral Dataset} & Sensitivity & 0.87 & 0.81 \\  & Specificity & 0.92 & 0.8 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Sensitivity and specificity (recall metrics) results of the three datasets using stratified five-fold cross-validation).  
the superior performance of the combined database relative to individual datasets remains ambiguous, potentially due to factors such as sample size, false positives in measurements, participants under the influence of medication, or those experiencing specific life conditions or undisclosed medical conditions. Moreover, the content of the script-driven imagery protocol itself might have influenced the measurements, as individual responses to certain scenarios may vary depending on their emotional states. These considerations underscore the need for further research to elucidate these findings and address the identified limitations. However, for the clinical and investigation topic, the real challenge lies in the reach of this kind of research. Sample sizes are often not large enough to conclusively generalize the findings, and the integration of such systems into medical centers presents additional complexities. Although this represents a step forward in generating proposals for clinical practice, further complementary studies are necessary to strengthen its robustness. In addition, widespread dissemination among healthcare professionals is essential for its integration into routine clinical practice. In addition, guidelines established by ethics committees and restrictions on the types of patients that can be included in studies can also influence the quality of the data and delay the integration of such approaches into clinical programs. Consequently, future investigations should focus on refining data acquisition methods, optimizing the code, enhancing emotion induction protocols, and increasing the diversity and size of the sample population, thereby contributing to a more profound understanding of the phenomena under study and enhancing the accuracy and reliability of the results.