## 3 Materials and Methods
These recommendations are simple but adapted to variations in the thresholds of a certain group of sensors. Table 3 provides a comprehensive overview of the key methodological considerations for this research on the evaluation of WSNs in monitoring the sleep quality and vital signs of the elderly. It details the research objectives, including the implementation of a WSN to measure various environmental variables, the collection and analysis of real-time data, and the provision of personalized recommendations based on the findings. The hypotheses highlight the expected impacts of temperature, noise, and light intensity on sleep quality. The table also enumerates the specific variables analyzed, data collection methods, and statistical techniques used for data analysis. Ethical considerations, such as informed consent and data protection, are emphasized to ensure the privacy and confidentiality of participants. Overall, the table aims to outline the methodological framework that guided the study, ensuring a systematic approach to improving the healthcare and quality of life of the elderly through innovative non-invasive monitoring technologies. Table 2 provides a detailed overview of the variables analyzed in this research study, focusing on their descriptions and their respective impacts on sleep quality among elderly participants. Breathing frequency, deep sleep, snoring, heart rate, heart rate variability, oxygen saturation, REM sleep, temperature, and total sleep time were the primary variables monitored using wireless sensor networks. The difference between REM sleep and total sleep time is that REM sleep is one specific stage within the overall sleep cycle, whereas total sleep refers to the entire amount of sleep time across all stages. The study found significant positive impacts on sleep quality for variables such as breathing frequency, deep sleep, snoring, heart rate variability, and REM sleep, indicating improvements in participants' sleep patterns. Temperature, on the other hand, negatively affected sleep quality, with higher temperatures correlating with poorer sleep. These findings highlight the importance of continuous and non-invasive monitoring of these variables to enhance the sleep quality and overall well-being of the elderly. \begin{table}
\begin{tabular}{p{142.3 pt} p{284.5 pt}} \hline \hline
**Consideration** & **Description** \\ \hline \multirow{4}{*}{**Research Objectives**} & This study aims to find detrimental patterns affecting sleep in elderly people through constant sleep monitoring with WSNs and remote vital sign measurement. It also aims to present daily recommendations and best practices to address the problem, improving the sleep quality and overall healthcare of the elderly at home. \\ \hline \multirow{4}{*}{**Specific Objectives**} & 1. Implement WSNs to measure various variables (e.g., temperature, pressure, noise, light) in the homes and bedrooms of the elderly. \\  & 2. Collect real-time data from WSNs before and after installation. \\  & 3. Measure the impact of the device post-implementation. \\  & 4. Develop data analysis schemes to assess sensor performance. \\  & 5. Provide personalized measures and recommendations based on analyzed data. \\  & 6. Present monitoring results and potential improvement areas. \\ \hline \multirow{4}{*}{**Hypotheses**} & The non-invasive monitoring of vital signs through a low-cost WSN results in a significant decrease in sleep quality in elderly people when temperatures exceed 23 \({}^{\circ}\)C and noise levels exceed 60 decibels. Additionally, light intensity above 480 nanometers is a significant factor affecting sleep quality. \\ \cline{1-1}  & The implementation of this technology is expected to raise awareness of sleep patterns, enabling early interventions in case of anomalies and improving security by providing discreet yet effective home monitoring. \\ \cline{1-1}  & \multicolumn{1}{p{284.5 pt}}{} \\ \end{tabular}
\end{table} 
Table 3: Important methodological considerations.