## 5 Discussion and Conclusions  
This research proposed a multisensor embedded sleep quality health monitoring intraoral appliance device with innovative design and development features. Sleep quality could be improved by preventing bruxism and OSA via real-time monitoring and biofeedback. s-Guard is fundamentally a wearable sensor. Therefore, assessing sensor stability in terms of wireless communication and seamless monitoring is most important. Necessarily, this can be assessed mainly by two categories: communication speed and communication errors. The results revealed a wireless data transmission monitoring speed of 91,870.19 bytes per second, a connection success rate of 100%, and a minimum transmission error rate of 0.1%. Considering that previous research mentioned the problems regarding limited bandwidth in wireless health monitoring situations [30,31], this performance can be considered highly suitable. Actual monitoring results showed successful sleep posture monitoring data calculated by the s-Guard algorithm based on sensed six-axis data. s-Guard was capable of monitoring a total of five sleep statuses: unidentified posture (null), prone position, supine position, leftward position, and rightward position. In addition, bruxism anomaly was also successfully detected by s-Guard, specifically monitored according to severity. The solution proposed herein could contribute significantly to enhancing the sleep quality of modern lives, in which many people suffer from early age OSA and bruxism. OSA patients who have to use CPAP for intensive care may now use a much more compact and convenient method for treatment and management. In addition, this research opened the possibility of embedding sensors other than temperature, six-axis, and SpO\({}_{2}\). This is envisioned to be applied in various other fields of information communication technology (ICT) and IoT. In addition, s-Guard can be used in both medicine and everyday healthcare management. A limitation of this research was that this solution was not suitable for short-term monitoring situations due to the high error rate in short-term sensing. Future research should investigate the reason for this and solve the issue of error rate so that this solution can also be used in short-term diagnosis situations. Conceptualization, S-J.L. and I-D.J. ; methodology, E.-B.K. ; software, I-H.J. ; validation, J.-Y.P. and J.-H.H. ; formal analysis, S-J.L. ; investigation, E.-B.K. and J.-Y.P. ; resources, J.-H.H., and T.-Y.J. ; data curation, T.-Y.J. ; writing--original draft preparation, S.-J.L., [PERSON]-H.H., and T.-Y.J. ; writing--review and editing, I-D.J. and T.-Y.J. ; visualization, J.-Y.P. ; supervision, T.-Y.J. ; project administration, [PERSON]-[PERSON] and [PERSON]; funding acquisition, [PERSON]-J.L., [PERSON], and [PERSON]-[PERSON]. All authors have read and agreed to the published version of the manuscript. This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded the Ministry of Health & Welfare, Republic of Korea (grant number: H19C1243), and the National Research Foundation of Korea (grant number: NRF-2020R11A1A01053726). \begin{table}
\begin{tabular}{c} **Error Rate (\%)** \\ \end{tabular} \\ \hline
10 s & 2500 & 2044 & 456 & 18.24 \\
100 s & 25,000 & 24,284 & 716 & 2.86 \\
10 min & 150,000 & 149,178 & 822 & 0.55 \\
1 h & 900,000 & 898,510 & 1490 & 0.17 \\
4 h & 3,600,000 & 3,595,042 & 4958 & 0.14 \\
8 h & 7,200,000 & 7,192,854 & 7146 & 0.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Wireless data stream error ratio evaluation results. **Institutional Review Board Statement:** The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Yonsei Severance Hospital (IRB approval number 2-2019-0060). **Informed Consent Statement:** Patient consent was waived due to nonidentifiable personal information included in this study.