Breathing and Snoring Sound Characteristics during Sleep in Adults

Automatically detecting OSAHS patients based on transfer learning and model fusion

Objective. Snoring is the most typical symptom of obstructive sleep apnea hypopnea syndrome (OSAHS) that can be used to develop a non-invasive approach for automatically detecting OSAHS patients.Approach. In this work, a model based on transfer learning and model fusion was applied to classify simple snorers and OSAHS patients. Three kinds of basic models were constructed based on pretrained Visual Geometry Group-16 (VGG16), pretrained audio neural networks (PANN), and Mel-frequency cepstral coefficient (MFCC). The XGBoost was used to select features based on feature importance, the majority voting strategy was applied to fuse these basic models and leave-one-subject-out cross validation was used to evaluate the proposed model.Main results. The results show that the fused model embedded with top-5 VGG16 features, top-5 PANN features, and MFCC feature can correctly identify OSAHS patients (AHI > 5) with 100% accuracy.Significance. The proposed fused model provides a good classification performance with lower computational cost and higher robustness that makes detecting OSAHS patients at home possible.

Chronic intermittent hypoxia-induced hypertension: the impact of sex hormones

Obstructive sleep apnea, a common form of sleep-disordered breathing, is characterized by intermittent cessations of breathing that reduce blood oxygen levels and contribute to the development of hypertension. Hypertension is a major complication of obstructive sleep apnea that elevates the risk of end-organ damage. Premenopausal women have a lower prevalence of obstructive sleep apnea and cardiovascular disease than men and postmenopausal women, suggesting that sex hormones play a role in the pathophysiology of sleep apnea-related hypertension. The lack of protection in men and postmenopausal women implicates estrogen and progesterone as protective agents but testosterone as a permissive agent in sleep apnea-induced hypertension. A better understanding of how sex hormones contribute to the pathophysiology of sleep apnea-induced hypertension is important for future research and possible hormone-based interventions. The effect of sex on the pathophysiology of sleep apnea and associated intermittent hypoxia-induced hypertension is of important consideration in the screening, diagnosis, and treatment of the disease and its cardiovascular complications. This review summarizes our current understanding of the impact of sex hormones on blood pressure regulation in sleep apnea with a focus on sex differences.

Exploring the dynamics of snoring in relation to sleep stages: Implications for gender differences, sleep position, and upper airway collapsibility

OBJECTIVE

The purpose of this study was to determine the sleep stage during which isolated snoring occurs in children and adults, and to analyze changes after treatment of obstructive sleep apnea (OSA).

METHODS

This retrospective study examined duration of snoring time and respiratory events during each sleep stage in adults and children who underwent polysomnography, had an apnea-hypopnea index (AHI) < 15/h and had snoring time ≥ 10% of total sleep time. Changes in duration of snoring time were also examined in adult patients after treatment with an oral appliance (OA).

RESULTS

Snoring time was shown to be predominant during N3 and N2 sleep and less dominant during REM sleep in both children (n = 47) and adults (n = 93). These results were seen even in children with REM dependency. The percentage of snoring time during N3 sleep was more pronounced in women than in men among young adult patients aged < 40 years but was not significantly different between men and women overall. There were no significant differences in the percentage of snoring time in each sleep stage between young women with mild OSA and non-OSA. In children, there were no significant differences between boys and girls in the percentage of snoring time in any sleep stage. The percentage of snoring time during N3 was significantly higher sleep in the non-supine position than in the supine position in children, whereas no significant differences were noted between the supine and non-supine positions in any sleep stage in adults. OA treatment for adult patients (n = 20) significantly increased the percentage of snoring time during N3 sleep, although it significantly decreased AHI, total snoring time, and snoring time during N1 sleep and REM sleep.

CONCLUSIONS

Snoring presented exclusively during the N3 sleep stage, especially in young women with mild OSA, and in children with OSA, especially in the non-supine position. Snoring time during N3 sleep increased during OA treatment for OSA.

Alternatives to Polysomnography for the Diagnosis of Pediatric Obstructive Sleep Apnea

Diagnosis of obstructive sleep apnea (OSA) in children with sleep-disordered breathing (SDB) requires hospital-based, overnight level I polysomnography (PSG). Obtaining a level I PSG can be challenging for children and their caregivers due to the costs, barriers to access, and associated discomfort. Less burdensome methods that approximate pediatric PSG data are needed. The goal of this review is to evaluate and discuss alternatives for evaluating pediatric SDB. To date, wearable devices, single-channel recordings, and home-based PSG have not been validated as suitable replacements for PSG. However, they may play a role in risk stratification or as screening tools for pediatric OSA. Further studies are needed to determine if the combined use of these metrics could predict OSA.

Effects of demographic and sleep-related factors on snoring sound parameters

OBJECTIVE

To investigate the effect of frequently reported between-individual (viz., age, gender, body mass index [BMI], and apnea-hypopnea index [AHI]) and within-individual (viz., sleep stage and sleep position) snoring sound-related factors on snoring sound parameters in temporal, intensity, and frequency domains.

METHODS

This study included 83 adult snorers (mean ± SD age: 42.2 ± 11.3 yrs; male gender: 59%) who underwent an overnight polysomnography (PSG) and simultaneous sound recording, from which a total of 131,745 snoring events were extracted and analyzed. Data on both between-individual and within-individual factors were extracted from the participants' PSG reports.

RESULTS

Gender did not have any significant effect on snoring sound parameters. The fundamental frequency (FF; coefficient = -0.31; P = 0.02) and dominant frequency (DF; coefficient = -12.43; P < 0.01) of snoring sounds decreased with the increase of age, and the second formant increased (coefficient = 22.91; P = 0.02) with the increase of BMI. Severe obstructive sleep apnea (OSA; AHI ≥30 events/hour), non-rapid eye movement sleep stage 3 (N3), and supine position were all associated with more, longer, and louder snoring events (P < 0.05). Supine position was associated with higher FF and DF, and lateral decubitus positions were associated with higher formants.

CONCLUSIONS

Within the limitations of the current patient profile and included factors, AHI was found to have greater effects on snoring sound parameters than the other between-individual factors. The included within-individual factors were found to have greater effects on snoring sound parameters than the between-individual factors under study.

Snoring Index and Neck Circumference as Predictors of Adult Obstructive Sleep Apnea

Background. Snoring is the cardinal symptom of obstructive sleep apnea (OSA). The acoustic features of snoring sounds include intra-snore (including snoring index [SI]) and inter-snore features. However, the correlation between snoring sounds and the severity of OSA according to the apnea−hypopnea index (AHI) is still unclear. We aimed to use the snoring index (SI) and the Epworth Sleepiness Scale (ESS) to predict OSA and its severity according to the AHI among middle-aged participants referred for polysomnography (PSG). Methods. In total, 50 participants (mean age, 47.5 ± 12.6 years; BMI: 29.2 ± 5.6 kg/m2) who reported snoring and were referred for a diagnosis of OSA and who underwent a whole night of PSG were recruited. Results. The mean AHI was 30.2 ± 27.2, and the mean SI was 87.9 ± 56.3 events/hour. Overall, 11 participants had daytime sleepiness (ESS > 10). The correlation between SI and AHI (r = 0.33, p = 0.021) was significant. Univariate linear regression analysis showed that male gender, body mass index, neck circumference, ESS, and SI were associated with AHI. SI (β = 0.18, p = 0.004) and neck circumference (β = 2.40, p < 0.001) remained significantly associated with AHI by the multivariate linear regression model. Conclusion. The total number of snores per hour of sleep and neck circumference were positively associated with OSA among adults referred for PSG.

Accuracy and modification of the STOP ‐bang questionnaire for screening patients with obstructive sleep apnea in China

Despite the high sensitivity of the STOP-Bang questionnaire [snoring, tiredness, observed apneas, high blood pressure, body mass index, age, neck size, gender] questionnaire (SBQ), which is widely used to screen individuals at high risk of obstructive sleep apnea (OSA), few studies have evaluated the discrimination related to sex in the SBQ. Therefore, our study aimed to assess whether SBQ performance is gender-related and modified by changing body mass index (BMI) and neck circumference (NC) cut-off values. A total of 470 patients attended the sleep centres. They were divided into moderate-to-severe OSA and non-moderate-to-severe OSA groups based on the apnea-hypopnea index (AHI) and the results of the SBQ screening. The predictive performance of the SBQ screening instrument was evaluated by 2 × 2 contingency tables and discriminatory ability, which was estimated from the area under the curve (AUC) obtained from receiver operating characteristic curve. Our results suggest that when screening for moderate-to-severe OSA, the original SBQ has higher sensitivity and lower specificity for men; however, women have higher specificity and lower sensitivity. The SBQ achieved the maximum AUC of 0.783 for men and 0.634 for women when the BMI cut-off value was established at 30 kg/m² and the NC cut-off value was established at 38 cm in men, and the BMI cut-off value was established at 25 kg/m² and the NC cut-off value at 36 cm in women. Balancing the optimal sensitivity and specificity, the cut-off value of the optimal modified SBQ total scores for men was determined to be ≥4 and ≥3 for women.

Correlation between snoring sounds and obstructive sleep apnea in adults: a meta-regression analysis

OBJECTIVE

Snoring is a dominant clinical symptom in patients with obstructive sleep apnea (OSA), and analyzing snoring sounds might be a potential alternative to polysomnography (PSG) for the assessment of OSA. This study aimed to systematically examine the correlation between the snoring sounds and the apnea-hypopnea index (AHI) as the measures of OSA severity.

MATERIAL AND METHODS

A comprehensive literature review using the MEDLINE, Embase, Cochrane Library, Scopus, and PubMed databases identified the published studies reporting the correlations between and severity of snoring and the AHI values by meta-regression analysis.

RESULTS

In total, 13 studies involving 3,153 adult patients were included in this study. The pooled correlation coefficient for snoring sounds and AHI values was 0.71 (95%CI: 0.49, 0.85) from the random-effects meta-analysis with the Knapp and Hartung adjustment. The I 2 and chi-square Q test demonstrated significant heterogeneity (97.6% and p<0.001). After adjusting for the effects of the other covariates, the mean value of the Fisher's r-to-z transformed correlation coefficient would have 0.80 less by the snoring rate (95%CI = -1.02, -0.57), 1.46 less by the snoring index (95%CI = -1.85, -1.07), and 0.21 less in the mean body mass index (95%CI = -0.31, -0.11), but 0.15 more in the mean age (95%CI = 0.10, 0.20). It fitted the data very well (R 2=0.9641).

CONCLUSION

A high correlation between the severity of snoring and the AHI was found in the studies with PSG. As compared to the snoring rate and the snoring index, the snoring intensity, the snoring frequency, and the snoring time interval index were more sensitive measures for the severity of snoring.

Evaluating Prediction Models of Sleep Apnea From Smartphone-Recorded Sleep Breathing Sounds

Importance

Breathing sounds during sleep are an important characteristic feature of obstructive sleep apnea (OSA) and have been regarded as a potential biomarker. Breathing sounds during sleep can be easily recorded using a microphone, which is found in most smartphone devices. Therefore, it may be easy to implement an evaluation tool for prescreening purposes.

Objective

To evaluate OSA prediction models using smartphone-recorded sounds and identify optimal settings with regard to noise processing and sound feature selection.

Design, Setting, and Participants

A cross-sectional study was performed among patients who visited the sleep center of Seoul National University Bundang Hospital for snoring or sleep apnea from August 2015 to August 2019. Audio recordings during sleep were performed using a smartphone during routine, full-night, in-laboratory polysomnography. Using a random forest algorithm, binary classifications were separately conducted for 3 different threshold criteria according to an apnea hypopnea index (AHI) threshold of 5, 15, or 30 events/h. Four regression models were created according to noise reduction and feature selection from the input sound to predict actual AHI: (1) noise reduction without feature selection, (2) noise reduction with feature selection, (3) neither noise reduction nor feature selection, and (4) feature selection without noise reduction. Clinical and polysomnographic parameters that may have been associated with errors were assessed. Data were analyzed from September 2019 to September 2020.

Main Outcomes and Measures

Accuracy of OSA prediction models.

Results

A total of 423 patients (mean [SD] age, 48.1 [12.8] years; 356 [84.1%] male) were analyzed. Data were split into training (n = 256 [60.5%]) and test data sets (n = 167 [39.5%]). Accuracies were 88.2%, 82.3%, and 81.7%, and the areas under curve were 0.90, 0.89, and 0.90 for an AHI threshold of 5, 15, and 30 events/h, respectively. In the regression analysis, using recorded sounds that had not been denoised and had only selected attributes resulted in the highest correlation coefficient (r = 0.78; 95% CI, 0.69-0.88). The AHI (β = 0.33; 95% CI, 0.24-0.42) and sleep efficiency (β = -0.20; 95% CI, -0.35 to -0.05) were found to be associated with estimation error.

Conclusions and Relevance

In this cross-sectional study, recorded sleep breathing sounds using a smartphone were used to create reasonably accurate OSA prediction models. Future research should focus on real-life recordings using various smartphone devices.

Sleep Measurements in Women

Sleep in women and men have been studied in several studies with higher prevalence of sleep complaints in women compared with men. Several factors can affect sleep and could be argued to contribute to sex and gender differences in general sleep. There are no differences in guidelines when measuring sleep in women but several sleep assessment tools have been validated or compared between sexes. Because there is still a lack of knowledge on sleep measurements in women, the present review aimed to produce an overview of the current knowledge of objective and subjective sleep measurements in women.

IoT snoring sound detector prototype as a model of future participatory healthcare

BACKGROUND

Traditional healthcare is centred around providing in-hospital services using hospital owned medical instruments. The COVID-19 pandemic has shown that this approach lacks flexibility to insure follow-up and treatment of common medical problems. In an alternative setting adapted to this problem, participatory healthcare can be considered centred around data provided by patients owning and operating medical data collection equipment in their homes.

OBJECTIVE

In order to trigger such a shift reliable and price attractive devices need to become available. Snoring, as a human sound production during sleep, can reflect sleeping behaviour and indicate sleep problems as an element of the overall health condition of a person.

METHODS

The use of off-the-shelf hardware from Internet of Things platforms and standard audio components allows the development of such devices. A prototype of a snoring sound detector with this purpose is developed.

RESULTS

The device, controlled by the patient and with specific snoring recording and analysing functions is demonstrated as a model for future participatory healthcare.

CONCLUSIONS

Design of monitoring devices following this model could allow market introduction of new equipment for participatory healthcare, bringing a care complementary to traditional healthcare to the reach of patients, and could result in benefits from enhanced patient participation.

Gender Issues in Obstructive Sleep Apnea

Obstructive sleep apnea has historically been considered a male disease. Although most studies have shown male predominance, obstructive sleep apnea is highly prevalent in women, increasing with age and varying with physiologic status among other factors. Obstructive sleep apnea is associated with significant symptoms and health consequences in women yet remains underdiagnosed in women in part due to differences in presenting symptoms, differences in polysomnographic findings, and/or sociocultural factors. This review will discuss the epidemiology, pathophysiology, clinical presentation, diagnostic findings, and treatment of obstructive sleep apnea, focusing on sex and gender differences.

The acoustical and perceptual features of snore-related sounds in patients with obstructive sleep apnea sleeping with the dynamic mandibular advancement system MATRx plus®

PURPOSE

The effect of snoring on the bed partner can be studied through the evaluation of in situ sound records by the bed partner or unspecialized raters as a proxy of real-life snoring perception. The aim was to characterize perceptual snore events through acoustical features in patients with obstructive sleep apnea (OSA) with an advanced mandibular position.

METHODS

Thirty-minute sound samples of 29 patients with OSA were retrieved from overnight, in-home recordings of a study to validate the MATRx plus® dynamic mandibular advancement system. Three unspecialized raters identified sound events and classified them as noise, snore, or breathing. The raters provided ratings for classification certainty and annoyance. Data were analyzed with respect to respiratory phases, and annoyance.

RESULTS

When subdividing perceptual events based on respiratory phase, the logarithm-transformed Mean Power, Spectral Centroid, and Snore Factor differed significantly between event types, although not substantially for the spectral centroid. The variability within event type was high and distributions suggested the presence of subpopulations. The general linear model (GLM) showed a significant patient effect. Inspiration segments occurred in 65% of snore events, expiration segments in 54%. The annoyance correlated with the logarithm of mean power (r = 0.48) and the Snore Factor (0.46).

CONCLUSION

Perceptual sound events identified by non-experts contain a non-negligible mixture of expiration and inspiration phases making the characterization through acoustical features complex. The present study reveals that subpopulations may exist, and patient-specific features need to be introduced.

Perceptual snoring as a basis for a psychoacoustical modeling and clinical patient profiling

PURPOSE

The perceptual burden and social nuisance for mainly the co-sleeper can affect the relationship between snorer and bedpartner. Mandibular advancement devices (MAD) are commonly recommended to treat sleep-related breathing such as snoring or sleep apnea. There is no consensus about the definition of snoring particularly with MAD, which is essential for assessing the effectiveness of treatment. We aimed to stablish a notion of perceptual snoring with MAD in place.

METHODS

Sound samples, each 30 min long, were recorded during in-home, overnight, automatic mandibular repositioning titration studies in a population of 29 patients with obstructive sleep apnea syndrome (OSAS) from a clinical trial carried out to validate the MATRx plus. Three unspecialized and calibrated raters identified sound events and classified them as noise, snore, or breathing as well as providing scores for classification certainty and annoyance. Data were analyzed with respect to expiration-inspiration, duration, annoyance, and classification certainty.

RESULTS

A Fleiss' kappa (>0.80) and correlation duration of events (>0.90) between raters were observed. Prevalence of all breath sounds: snore 55.6% (N = 6398), breathing sounds 31.7% (N = 3652), and noise 9.3% (N = 1072). Inspiration occurs in 88.3% of events, 96.8% contained at least on expiration phase. Snore and breath events had similar duration, respectively 2.58s (sd 1.43) and 2.41s (sd 1.22). Annoyance is lowest for breathing events (8.00 sd 0.98) and highest for snore events (4.90 sd 1.92) on a VAS from zero to ten.

CONCLUSION

Perceptual sound events can be a basis for analysis in a psychosocial context. Perceived snoring occurs during both expiration as well as inspiration. Substantial amount of snoring remains despite repositioning of the mandible aimed at the reduction of AHI-ODI.

Estimation of heart rate from tracheal sounds recorded for the sleep apnea syndrome diagnosis

Obstructive sleep apnea is a common sleep disorder with a high prevalence and often accompanied by significant snoring activity. To diagnose this condition, polysomnography is the standard method, where a neck microphone could be added to record tracheal sounds. These can then be used to study the characteristics of breathing, snoring or apnea. In addition cardiac sounds, also present in the acquired data, could be exploited to extract heart rate. The paper presents new algorithms for estimating heart rate from tracheal sounds, especially in very loud snoring environment. The advantage is that it is possible to reduce the number of diagnostic devices, especially for compact home applications. Three algorithms are proposed, based on optimal filtering and cross-correlation. They are tested firstly on one patient presenting significant pathology of apnea syndrome, with a recording of 509 min. Secondly, an extension to a database of 16 patients is proposed (16 hours of recording). When compared to a reference ECG signal, the final results obtained from tracheal sounds reach an accuracy of 81% to 98% and an RMS error from 1.3 to 4.2 bpm, according to the level of snoring and to the considered algorithm.

Snoring Sound Characteristics are Associated with Common Carotid Artery Profiles in Patients with Obstructive Sleep Apnea

BACKGROUND

Obstructive sleep apnea (OSA) and snoring have been reported to be modifiable risk factors for thick carotid intima-media thickness (CIMT) and carotid atherosclerosis, which are closely linked to cardiovascular disease.

METHODS

This cross-sectional study prospectively recruited 70 participants with OSA and without a history of carotid artery disorder, who primarily sought surgical Intervention. OSA and snoring were assessed with the Epworth Sleepiness Scale, Snore Outcomes Survey, polysomnography, and snoring sound recording. The carotid arteries were evaluated with ultrasonography and divided into three types of carotid artery profiles (normal carotid artery, thick CIMT, or significant carotid atherosclerosis). Multivariate linear/logistic/categorical regressions were performed with the forward selection approaches/logistic least absolute shrinkage and selection operator, as appropriate.

RESULTS

Normalized snoring sound energy (301-850 Hz) was independently associated with the carotid intima-media thickness (regression coefficient [β] = 0.01, standard error [SE] = 0.004, P = 0.03; R ² = 0.067) and type of carotid profile (β = 0.40, SE = 0.09, P < 0.001; R ² = 0.156). Normalized snoring sound energy (4-300 Hz) (β = -0.10, SE = 0.04, P = 0.01) and female sex (β = 1.90, SE = 0.94, P = 0.04) were independently related to the presence of carotid stenosis (R ² = 0.159). The optimal regression model of the type of carotid artery profile included normalized snoring sound energy (301-850 Hz) (β = 0.33, SE = 0.14, P = 0.03), snoring time (β = 0.26, SE = 0.13, P = 0.047), female sex (β = 0.26, SE = 0.13, P = 0.047), and increased age (β = 0.20, SE = 0.10, P = 0.04) under the control of the Snore Outcomes Survey score, 3% oxygen desaturation index, snoring sound energy (4-1500 Hz), normalized snoring sound energy (851-1500 Hz), cigarette smoking, and hyperlipidemia (R ² = 0.427).

CONCLUSION

Our findings suggested that snoring sound characteristics are associated with carotid artery profiles among early OSA patients who cannot be noticed by ultrasound because organic changes of the carotid artery have not yet started. Future studies are warranted to verify the clinical significance of the results.

Analysis of snoring to determine the site of obstruction in obstructive sleep apnea syndrome

BACKGROUND

The aim of this study was to integrate the physical findings of drug-induced sleep endoscopy with snoring sound analysis in patients with obstructive sleep apnea/hypopnea syndrome (OSAS) and to compare the findings with previously published data.

METHODS

This was a prospective, non-randomized study. Participants were all candidates for surgical treatment of OSAS and formed three groups, retropalatal (RP) obstructions, retrolingual (RL) obstructions, and multilevel (ML) obstructions. At the time of DISE, recordings of concurrent snoring sounds were made. Mean pitch frequency, peak sound frequency, and fundamental frequency (Fo) components were determined.

RESULTS

A total of 55 participants had mean age 46.2 ± 7.3 years, mean BMI 30.0 ± 3.7 kg/m², and included 11 women (20%). Differences in mean pitch frequency, Fo, and peak sound frequency were all statistically significant between the RP and RL (p = 0.001), between ML and RL (p = 0.025) but were not significantly different between RP and ML. Mean pitch frequency of RP was lower than RL, and ML frequency was between RL and RP. The sound analysis graphics revealed RP waves with sharp peaks and lower frequencies and RL with smooth curves and higher frequencies. ML showed irregular patterns. Mean pitch frequency of RL was always above 400 Hz, whereas RP was below this value.

CONCLUSIONS

It is feasible to apply sound analysis to determine the site of obstruction during DISE. Combining the data may help surgeons make more accurate assessments of the pattern of the disease.

Influence of age and gender on sleep bruxism and snoring in non-apneic snoring patients: A polysomnographic study

The present study aimed to assess the influence of gender and age on snoring and sleep bruxism in non-apneic snoring patients. Adult participants with clinical suspicion of snoring and with no other significant medical history were recruited. Single-night video polysomnography was performed to detect snoring and sleep bruxism. Finally, 137 snoring non-apneic participants were included. Statistical analysis of gender groups showed that the total snore index and snore train were significantly higher in men than in women. Men also presented severe bruxism, with significantly more frequent episodes and higher bruxism episodes index scores. The correlation analysis showed the presence of significant linear relationships in the supine sleep position between age and snore index, snore index in non-rapid eye movement 2 (N2) sleep stage, and snore train. The analysis of groups separated according to the criterion of third age quartile showed that the average, maximum and minimum audio volume in the non-supine sleep position was significantly higher in the older group. The analysis of groups separated according to the criterion of median age showed that the bruxism episode index and bruxism phasic episodes were significantly higher in the younger group. Thus, it can be concluded that both age and gender influence snoring and sleep bruxism. Snoring and sleep bruxism seem to be more intensive in men. Older patients seem to snore more in N2 sleep and the supine sleep position and present lower bruxism episodes, especially the phasic type. The results of the present study indicate the need for further research on this topic to establish the possible relationship between snoring and sleep bruxism.

SnoreNet: Detecting Snore Events from Raw Sound Recordings

Snoring is one of the earliest symptoms of Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS). Snore detection is the first step in developing non-invasive, low-cost, and totally sound-based OSAHS analysis approaches. In this work, we propose a simple yet effective deep neural network, named SnoreNet, for detecting snores from a continuous sound recording. Without manually crafted features, SnoreNet can capture the characteristics of snores. Since snore varies in temporal length, SnoreNet combines output from multiple feature maps to detect snore. In each feature map, SnoreNet uses a set of default bounding box generated by a base length and different scales to match snores. SnoreNet adjusts the box to better locate snores and predicts a score for the presence of snore in each default bounding box. The performance of SnoreNet was evaluated on a newly collected snore pattern classes dataset, which achieves 81.82% average precision (AP).

The Associations of Gender, Menopause, Age, and Asthma with REM-Predominant Obstructive Sleep Apnea: A Prospective Observational Study

PURPOSE

The study sought to assess demographics, clinical features, comorbidities, and polysomnographic features of a large cohort of clinic-based patients with rapid eye movement-predominant obstructive sleep apnea (REM-predominant-OSA) in both genders, while assessing the relationship between REM-predominant OSA in one hand and menopausal status and age on the other.

METHODS

This prospective observational study was conducted between January 2003 and December 2017. REM-predominant OSA diagnostic criteria included an AHI of ≥5/h, with REM-AHI/non-REM-AHI of >2, a non-REM-AHI of <15/h, and a minimum of 15 min of REM sleep. Patients who had an AHI>5 events/h and did not meet the criteria for REM-predominant OSA were included in the non-stage-specific OSA group (NSS).

RESULTS

The study consisted of 1346 men and 823 women (total=2169). REM-predominant OSA was diagnosed in 17% (n=369). The prevalence of REM-predominant OSA in women was 25% compared with 12% in men. Several independent associations of REM-predominant OSA were identified in the whole group, including age (OR: 0.97 [0.95-0.98], p<0.01), female sex (OR: 6.95 [4.86-9.93], p>0.01), REM sleep duration (min) (OR: 1.02 [1.02-1.03], < 0.01), and time with SpO2 <90% (mins) (OR: 0.97 [0.95-0.99], < 0.01), hypertension (OR:0.67 [0.45-0.99], 0.04) and asthma (OR: 2.19 [1.56-3.07], < 0.01). The prevalence of REM-predominant OSA in premenopausal and postmenopausal women was 35% and 18.6% (p< 0.01), respectively. Among women, age was an independent correlate (OR: 0.97 [0.94-0.99], p=0.03; however, menopausal status was not.

CONCLUSION

REM-predominant OSA is prevalent among clinic-based patients with OSA. A younger age and female sex were independent correlates of REM-predominant OSA. Among women, a younger age but not menopausal status was a correlate of REM-predominant OSA. Asthma was independently associated with REM-predominant OSA.

Fluoride exposure and sleep patterns among older adolescents in the United States: a cross-sectional study of NHANES 2015-2016

BACKGROUND

Fluoride from environmental sources accumulates preferentially in the pineal gland which produces melatonin, the hormone that regulates the sleep-wake cycle. However, the effects of fluoride on sleep regulation remain unknown. This population-based study examined whether chronic low-level fluoride exposure is associated with sleep patterns and daytime sleepiness among older adolescents in the United States (US).

METHOD

This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (2015-2016). We analyzed data from adolescents who had plasma fluoride (n = 473) and water fluoride (n = 419) measures and were not prescribed medication for sleep disorders. Relationships between fluoride exposure and self-reported sleep patterns or daytime sleepiness were examined using survey-weighted linear, binomial logistic or multinomial logistic regression after covariate adjustment. A Holm-Bonferroni correction accounted for multiple comparisons.

RESULTS

The average age of adolescents was 17 years (range = 16-19). Median (IQR) water and plasma fluoride concentrations were 0.27 (0.52) mg/L and 0.29 (0.19) μmol/L respectively. An IQR increase in water fluoride was associated with 1.97 times higher odds of reporting symptoms suggestive of sleep apnea (95% CI: 1.27, 3.05; p = 0.02), a 24 min later bedtime (B = 0.40, 95% CI: 0.10, 0.70; p = 0.05), a 26 min later morning wake time (B = 0.43, 95% CI: 0.13, 0.73; p = 0.04), and among males, a 38% reduction in the odds of reporting snoring (95% CI: 0.45, 0.87, p = 0.03).

CONCLUSIONS

Fluoride exposure may contribute to changes in sleep cycle regulation and sleep behaviors among older adolescents in the US. Additional prospective studies are warranted to examine the effects of fluoride on sleep patterns and determine critical windows of vulnerability for potential effects.

Sleep staging using nocturnal sound analysis

Sleep staging is essential for evaluating sleep and its disorders. Most sleep studies today incorporate contact sensors that may interfere with natural sleep and may bias results. Moreover, the availability of sleep studies is limited, and many people with sleep disorders remain undiagnosed. Here, we present a pioneering approach for rapid eye movement (REM), non-REM, and wake staging (macro-sleep stages, MSS) estimation based on sleep sounds analysis. Our working hypothesis is that the properties of sleep sounds, such as breathing and movement, within each MSS are different. We recorded audio signals, using non-contact microphones, of 250 patients referred to a polysomnography (PSG) study in a sleep laboratory. We trained an ensemble of one-layer, feedforward neural network classifiers fed by time-series of sleep sounds to produce real-time and offline analyses. The audio-based system was validated and produced an epoch-by-epoch (standard 30-sec segments) agreement with PSG of 87% with Cohen's kappa of 0.7. This study shows the potential of audio signal analysis as a simple, convenient, and reliable MSS estimation without contact sensors.

Spatial acoustic radiation of respiratory sounds for sleep evaluation

Body posture has an effect on sleeping quality and breathing disorders and therefore it is important to be recognized for the completion of the sleep evaluation process. Since humans have a directional acoustic radiation pattern, it is hypothesized that microphone arrays can be used to recognize different body postures, which is highly practical for sleep evaluation applications that already measure respiratory sounds using distant microphones. Furthermore, body posture may have an effect on distant microphone measurement; hence, the measurement can be compensated if the body posture is correctly recognized. A spherical harmonics decomposition approach to the spatial acoustic radiation is presented, assuming an array of eight microphones in a medium-sized audiology booth. The spatial sampling and reconstruction of the radiation pattern is discussed, and a final setup for the microphone array is recommended. A case study is shown using recorded segments of snoring and breathing sounds of three human subjects in three body postures in a silent but not anechoic audiology booth.