Background/purpose Oral appliances (OAs) have been recommended as alternatives for adult patients with obstructive sleep apnea who are intolerant of continuous positive airway pressure therapy. The aim of this study was to explore the effect on snoring rates among adult patients through use of a novel OA termed the Lin OA (LOA, airflow-interference-type nasal congestion relieving and snore-ceasing oral appliance). Materials and methods The LOA consist of two parts: dental braces and a fixed tongue compressor. The compressor lengths range from 0.5 cm to 3.5 cm across versions. Patients used the LOA during sleep and the SnoreClock smartphone application recorded their snoring rates. Results A total of 4920 recordings (4239 recordings from 34 men, 681 recordings from 8 women) were used for the analysis. The recordings were sorted in accordance with the applied length of the LOA tongue compressor (0.5–3.5 cm, LOA-0.5, LOA-1 and LOA-3.5), and participants not using the LOA were denoted as the LOA-0 group. The women had higher snoring rates in the LOA-0, LOA-0.5 to LOA-2 groups, but lower snoring rates in the LOA-3 group than men by the univariate analysis. The snoring rates were significantly reduced by a mean of 5.04% with every 1 cm increase in tongue compressor length. Continuous LOA use resulted in snoring rate reductions of 0.02% per day by the random intercept model of the linear regression. Conclusion Use of this novel LOA may significantly reduce snoring rates by 5.04% with each 1 cm increase in tongue compressor length.

Background: Snoring constitutes a worldwide public health concern that may be associated with daytime fatigue, endothelial dysfunction, vascular injury, stroke, cardiovascular diseases, and diabetes among female patients. This study explored the effects of the so-called Lin Oral Appliance (LOA) on Taiwanese adults’ snoring rates.Methods: A time series analysis was conducted to examine the associations between LOAs’ tongue compressors of different lengths, and snoring rates were calculated using the SnoreClock app. The LOA comprises 2 components: custom-made dental braces and tongue compressors of adjustable lengths; different versions had different-length compressors.Results: Our multiple linear regression time-series model revealed the effects of the LOA on snoring rates. The results indicated the following: i) LOA tongue compressor lengths of 1 and 2.5 cm (LOA-1 and LOA-2.5, respectively) were associated with reduced snoring rates; ii) sleep durations of 5.5-7.5 h and daytime sleepiness were associated with increased snoring rates; and iii) among participants with snoring rates above 10%, the snoring rates observed 1-7 days before a given day constituted a significant factor influencing snoring rates on the given day.Conclusions: We discovered that the LOA could reduce snoring rates and that the 2.5-cm compressor length in the LOA produced the best results.

Snoring is a nuisance for the bed partners of people who snore and is also associated with chronic diseases. Estimating the snoring duration from a whole-night sleep period is challenging. The authors present a dependable algorithm for visualizing snoring durations through acoustic analysis. Both instruments (Sony digital recorder and smartphone’s SnoreClock app) were placed within 30 cm from the examinee’s head during the sleep period. Subsequently, spectrograms were plotted based on audio files recorded from Sony recorders. The authors thereby developed an algorithm to validate snoring durations through visualization of typical snoring segments. In total, 37 snoring recordings obtained from 6 individuals were analyzed. The mean age of the participants was 44.6 ± 9.9 years. Every recorded file was tailored to a regular 600-second segment and plotted. Visualization revealed that the typical features of the clustered snores in the amplitude domains were near-isometric spikes (most had an ascending–descending trend). The recorded snores exhibited 1 or more visibly fixed frequency bands. Intervals were noted between the snoring clusters and were incorporated into the whole-night snoring calculation. The correlative coefficients of snoring rates from digitally recorded files examined between Examiners A and B were higher (0.865, P < .001) than those with SnoreClock app and Examiners (0.757, P < .001; 0.787, P < .001, respectively). A dependable algorithm with high reproducibility was developed for visualizing snoring durations.

Background: Snoring is a nuisance for the bed partners of people who snore and is also associated with chronic diseases. Estimating the snoring duration from a whole-night-sleep period is challenging. The authors present a dependable algorithm for visualizing snoring durations through acoustic analysis. Method: Both instruments (Sony digital recorder and smartphone’s SnoreClock app) were placed within 30 cm from the examinee’s head during the sleep period. Subsequently, spectrograms were plotted based on audio files recorded from Sony recorders. The authors developed an algorithm to validate snoring durations through visualization of typical snoring segments. Results: In total, 37 snoring recordings obtained from six individuals were analyzed. The mean age of the participants was 44.6 ± 9.9 years. A 3-s segment demonstrated the typical dominant frequency bands and amplitude waves of two snores. Every recorded file was tailored to a regular 600-s segment and plotted. Visualization revealed that the typical features of the clustered snores in the amplitude domains were near-isometric spikes (most had an ascending–descending trend). The recorded snores exhibited one or more visibly fixed frequency bands. Intervals were noted between the snoring clusters and were incorporated into the whole-night snoring calculation. The correlative coefficients of snoring rates of digitally recorded files examined by Examiners A and B were higher (0.865, p < 0.001) than those with SnoreClock app (0.757, p < 0.001; 0.787, p < 0.001, respectively). Conclusion: A dependable algorithm with high reproducibility was developed for visualizing snoring durations.