Distinguishing snoring sounds from breath sounds: a straightforward matter?

Effect of hypoglossal nerve stimulation on snoring: an evaluation using objective acoustic parameters

STUDY OBJECTIVES

Hypoglossal nerve stimulation is an established therapy for sleep apnea syndrome. Whether or not this therapy on snoring and nighttime noise exposure is effective and how strong this effect may be has not been objectively investigated thus far and was the aim of this study.

METHODS

In 15 participants (14 males; age: 30-72 years; mean: 51.7 years), polysomnography and acoustic measurements were performed before and after hypoglossal nerve stimulation.

RESULTS

The therapy led to a significant improvement in sleep apnea (apnea-hypopnea index from 35.8 events/h to 11.2 events/h, P < .001). Acoustic parameters showed a highly significant reduction in the average sound pressure level (42.9 db[A] to 36.4 db[A], P < .001), averaged sound energy, A-weighted (LAeq; 33.1 db[A] to 28.7 db[A], P < .001), snoring index (1,068 to 506, P < .001), percentage snoring time (29.7-14.1%, P < .001), and psychoacoustic snore score, the latter being a measure of annoyance due to snoring (47.9 to 24.5, P < .001).

CONCLUSIONS

This study was able to show for the first time by means of objective acoustic and psychoacoustic parameters that hypoglossal nerve stimulation can not only cause a significant improvement in sleep apnea but also has a positive effect on snoring and thus noise annoyance experienced by the bed partner.

CLINICAL TRIAL REGISTRATION

Registry: German Clinical Trials Register; Name: Effect of Hypoglossal Nerve Stimulation on Snoring: An Evaluation Using Objective Acoustic Parameters; URL: https://drks.de/search/de/trial/DRKS00032354; Identifier: DRKS00032354.

CITATION

Fischer R, Vielsmeier V, Kuehnel TS, et al. Effect of hypoglossal nerve stimulation on snoring: an evaluation using objective acoustic parameters. J Clin Sleep Med. 2024;20(3):363-370.

[Analysis of Snoring in Patients with Obstructive Sleep Apnea (OSA) by Polysomnography and LEOSound]

INTRODUCTION

Snoring was monitored in patients with obstructive sleep apnea (OSA) using the LEOSound-Monitor and simultaneously polysomnographic (PSG) recording. In obstructive apneas snoring is normally apparent after apnea termination and the beginning of ventilation. We wanted to know how often obstructive apneas are terminated by ventilation in combination with snoring.

METHODS AND INTENTION

In 40 patients with OSA (AHI > 15/h) simultaneous polysomnographic recordings were performed amongst long-term respiratory sound monitoring using the LEOSound monitor. Patients' average age was 57±11 years. Average weight was 100±19 kg by a mean body mass index (BMI) of 33±7 kg/m². 12 out of 40 recordings had to be rejected for further analysis because of artifacts. Snoring recorded by polysomnography was compared with snoring monitored by LEOSound.

RESULTS

3778 obstructive apnea episodes were monitored. LEOSound identified snoring in 1921 (51,0%), polysomnography in 2229 (58,8%) obstructive apneas. Only in one patient there was a higher difference in snoring episodes between PSG and LEOSound.

DISCUSSION

In nearly 60% of obstructive apnea events we found snoring during apnea-terminating hyperpnoea. LEOSound is a good diagnostic tool to monitor snoring. It is necessary to clarify why only 60% of all obstructive events/hyperpnoea develop snoring. From a pathophysiological point of view opening of collapsed upper airway should lead in a very high percentage to turbulences in airstream and committed snoring.

Prediction of the obstruction sites in the upper airway in sleep-disordered breathing based on snoring sound parameters: a systematic review

BACKGROUND

Identification of the obstruction site in the upper airway may help in treatment selection for patients with sleep-disordered breathing. Because of limitations of existing techniques, there is a continuous search for more feasible methods. Snoring sound parameters were hypothesized to be potential predictors of the obstruction site. Therefore, this review aims to i) investigate the association between snoring sound parameters and the obstruction sites; and ii) analyze the methodology of reported prediction models of the obstruction sites.

METHODS

The literature search was conducted in PubMed, Embase.com, CENTRAL, Web of Science, and Scopus in collaboration with a medical librarian. Studies were eligible if they investigated the associations between snoring sound parameters and the obstruction sites, and/or reported prediction models of the obstruction sites based on snoring sound.

RESULTS

Of the 1016 retrieved references, 28 eligible studies were included. It was found that the characteristic frequency components generated from lower-level obstructions of the upper airway were higher than those generated from upper-level obstructions. Prediction models were built mainly based on snoring sound parameters in frequency domain. The reported accuracies ranged from 60.4% to 92.2%.

CONCLUSIONS

Available evidence points toward associations between the snoring sound parameters in the frequency domain and the obstruction sites in the upper airway. It is promising to build a prediction model of the obstruction sites based on snoring sound parameters and participant characteristics, but so far snoring sound analysis does not seem to be a viable diagnostic modality for treatment selection.

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.

The anti-snoring bed - a pilot study

Purpose

Avoiding supine position can reduce snoring in most habitual snorers. However, devices that restrict the sleeping position cause discomfort or disrupt sleep resulting in low compliance. Therefore, mechanisms, which lift the trunk of the user without disturbing sleep, have been proposed. We present the first study, which investigates whether individual interventions provided by beds with lifting mechanisms are able to stop snoring (success rate) and whether they reduce the snoring index (number of total snores divided by total time in bed) using a repeated measures design. In addition, we investigated whether the intervention is interfering with the subjective sleep quality.

Methods

Twenty-two subjects were observed for four nights (adaptation, baseline, and two intervention nights). During intervention nights, the bed lifted the trunk of the user in closed-loop manner. Subjects were divided in three groups (non-snorer, snorer one, and snorer two). Non-snorers were lifted by the bed at random time points during the night. In group snorer one, a stepwise increase of the bed inclination was compared with going directly to a randomly selected angle. In group snorer two, the influence of a small inclination angle (10 ∘) and a big inclination angle (20 ∘) was compared.

Results

Snoring was stopped successfully in 22% (small angle) and 67% (big angle) of the interventions. This did not lead to a significant reduction in the snoring index. The subjective sleep quality was not reduced by the intervention.

Conclusion

The anti-snoring bed is able to stop individual episodes of habitual snoring without reducing the subjective sleep quality.

Trial Registration

https://clinicaltrials.gov, no. NCT04053738, registered 12 August 2019 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04053738.

Snoring patterns during home polysomnography. A proposal for a new classification

PURPOSE

Snoring is a very common disorder, but, at present, there is no universally accepted classification for the condition. The main aim of this paper is to introduce a home sleep monitoring-based classification of common snoring patterns in simple snorers and in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS).

MATERIALS AND METHODS

In total, 561 consecutive patients with a history of snoring, either simple or associated with apnea, were enrolled in this home sleep monitoring study. Analysis of the polysomnographic traces and the snoring sensor allowed the main patterns of snoring and their characteristics to be determined.

RESULTS

Four patterns of snoring were identified. In a spectrum of increasing severity (mild, moderate or severe), snoring can be episodic, positional, continuous, or alternating, whereas in obstructive sleep apnea syndrome, the snoring events only occur between successive respiratory obstructive events. In mild snoring, the episodic pattern is the most frequent, whereas in moderate and severe snoring, the continuous snoring pattern occurs in most cases.

CONCLUSIONS

The proposed classification of snoring patterns would be beneficial for providing a realistic disturbance index, for the selection and evaluation of the outcomes of surgical techniques.

[Analysis of Snoring in Patients with Obstructive Sleep Apnea (OSA) by Polysomnography and LEOSound]

INTRODUCTION

 Snoring was monitored in patients with obstructive sleep apnea (OSA) using the LEOSound-Monitor and simultaneously polysomnographic (PSG) recording. In obstructive apneas snoring is normally apparent after apnea termination and the beginning of ventilation. We wanted to know how often obstructive apneas are terminated by ventilation in combination with snoring.

METHODS AND INTENTION

 In 40 patients with OSA (AHI > 15/h) simultaneous polysomnographic recordings were performed amongst long-term respiratory sound monitoring using the LEOSound monitor. Patients' average age was 57 ± 11 years. Average weight was 100 ± 19 kg by a mean body  mass  index (BMI) of 33 ± 7 kg/m². 12 out of 40 recordings had to be rejected for further analysis because of artifacts. Snoring recorded by polysomnography was compared with snoring monitored by LEOSound.

RESULTS

 3778 obstructive apnea episodes were monitored. LEOSound identified snoring in 1921 (51,0 %), polysomnography in 2229 (58,8 %) obstructive apneas. Only in one patient there was a higher difference in snoring episodes between PSG and LEOSound.

DISCUSSION

 In nearly 60 % of obstructive apnea events we found snoring during apnea-terminating hyperpnoea. LEOSound is a good diagnostic tool to monitor snoring. It is necessary to clarify why only 60 % of all obstructive events/hyperpnoea develop snoring. From a pathophysiological point of view opening of collapsed upper airway should lead in a very high percentage to turbulences in airstream and committed snoring.

Are annoyance scores based on sound pressure levels suitable for snoring assessment in the home environment?

Purpose

An objective statement about the annoyance of snoring can be made with the Psychoacoustic Snore Score (PSS). The PSS was developed based on subjective assessments and is strongly influenced by observed sound pressure levels. Robustness against day-to-day interfering noises is a fundamental requirement for use at home. This study investigated whether or not the PSS is suitable for use in the home environment.

Methods

Thirty-six interfering noises, which commonly occur at night, were played in the acoustic laboratory in parallel with 5 snoring sounds. The interfering noises were each presented at sound pressure levels ranging from 25 to 55 dB(A), resulting in 3255 distinct recordings. Annoyance was then assessed using the PSS.

Results

In the case of minimally annoying snoring sounds, interfering noises with a sound pressure level of 25 dB(A) caused significant PSS changes from 40 to 55 dB(A) for annoying snoring sounds. If the interfering noise was another snoring sound, the PSS was more robust depending on the sound pressure level of the interfering noise up to 10 dB(A). Steady (no-peak) interfering noises influenced the PSS more strongly than peak noises.

Conclusions

The PSS is significantly distorted by quiet interfering noises. Its meaningfulness therefore depends strongly on the acoustic environment. It may therefore be assumed that scores dependent on sound pressure level are suitable for measurements when there is minimal ambient noise, as in the sleep laboratory. However, for measurements where noise is incalculable, as in the home environment, interfering noises may distort the results.

Snoring - An Acoustic Definition

Objective- The distinction of snoring and loud breathing is often subjective and lies in the ear of the beholder. The aim of this study is to identify and assess acoustic features with a high suitability to distinguish these two classes of sound, in order to facilitate an objective definition of snoring based on acoustic parameters. Methods- A corpus of snore and breath sounds from 23 subjects has been used that were classified by 25 human raters. Using the openSMILE feature extractor, 6 373 acoustic features have been evaluated for their selectivity comparing SVM classification, logistic regression, and the recall of each single feature. Results- Most selective single features were several statistical functionals of the first and second mel frequency spectrum-generated perceptual linear predictive (PLP) cepstral coefficient with an unweighted average recall (UAR) of up to 93.8%. The best performing feature sets were low level descriptors (LLDs), derivatives and statistical functionals based on fast Fourier transformation (FFT), with a UAR of 93.0%, and on the summed mel frequency spectrum-generated PLP cepstral coefficients, with a UAR of 92.2% using SVM classification. Compared to SVM classification, logistic regression did not show considerable differences in classification performance. Conclusion- It could be shown that snoring and loud breathing can be distinguished by robust acoustic features. The findings might serve as a guidance to find a consensus for an objective definition of snoring compared to loud breathing.

Objective Relationship Between Sleep Apnea and Frequency of Snoring Assessed by Machine Learning

STUDY OBJECTIVES

Snoring is perceived to be directly proportional to sleep apnea severity, especially obstructive sleep apnea (OSA), but this notion has not been thoroughly and objectively evaluated, despite its popularity in clinical practice. This might lead to overdiagnosis or underdiagnosis of OSA. The goal of this study is to examine this notion and objectively quantify the relationship between sleep apnea and snoring detected using advanced signal processing algorithms.

METHODS

We studied adults referred for polysomnography, from which the apnea-hypopnea index (AHI) was derived. Breath sounds were recorded simultaneously, from which snoring was accurately quantified using acoustic analysis of breath sounds and machine-learning computer algorithms. The snore index (SI) was calculated as the number of snores per hour of sleep.

RESULTS

In 235 patients, the mean AHI was 20.2 ± 18.8 and mean SI was 320.2 ± 266.7 events/h. On the one hand, the overall correlation between SI and AHI was weak but significant (r = .32, P < .0001). There was a significant stepwise increase in SI with increasing OSA severity, but with a remarkable overlap in SI among OSA severity categories. On the other hand, SI had weak negative correlation with central AHI (r = -.14, P = .035). SI had modest positive and negative predictive values for OSA (0.63 and 0.62 on average, respectively) and good sensitivity but low specificity (0.91 and 0.31 on average, respectively) attributed to the large number of snorers without OSA.

CONCLUSIONS

Snoring on its own is probably of limited usefulness in assessing sleep apnea presence and severity, because of its weak relationship with AHI. Thus, the complaint of snoring should be interpreted with caution to avoid unnecessary referrals for sleep apnea testing. Conversely, clinicians should be aware of the possibility of missing diagnosis of patients with sleep apnea who have minimal snoring.

Breathing and Snoring Sound Characteristics during Sleep in Adults

STUDY OBJECTIVES

Sound level meter is the gold standard approach for snoring evaluation. Using this approach, it was established that snoring intensity (in dB) is higher for men and is associated with increased apnea-hypopnea index (AHI). In this study, we performed a systematic analysis of breathing and snoring sound characteristics using an algorithm designed to detect and analyze breathing and snoring sounds. The effect of sex, sleep stages, and AHI on snoring characteristics was explored.

METHODS

We consecutively recruited 121 subjects referred for diagnosis of obstructive sleep apnea. A whole night audio signal was recorded using noncontact ambient microphone during polysomnography. A large number (> 290,000) of breathing and snoring (> 50 dB) events were analyzed. Breathing sound events were detected using a signal-processing algorithm that discriminates between breathing and nonbreathing (noise events) sounds.

RESULTS

Snoring index (events/h, SI) was 23% higher for men (p = 0.04), and in both sexes SI gradually declined by 50% across sleep time (p < 0.01) independent of AHI. SI was higher in slow wave sleep (p < 0.03) compared to S2 and rapid eye movement sleep; men have higher SI in all sleep stages than women (p < 0.05). Snoring intensity was similar in both genders in all sleep stages and independent of AHI. For both sexes, no correlation was found between AHI and snoring intensity (r = 0.1, p = 0.291).

CONCLUSIONS

This audio analysis approach enables systematic detection and analysis of breathing and snoring sounds from a full night recording. Snoring intensity is similar in both sexes and was not affected by AHI.

Evaluation of acoustic characteristics of snoring sounds obtained during drug-induced sleep endoscopy

INTRODUCTION

Snoring sounds are discussed to contain acoustic information about their geneses. Nocturnal snoring can easily be recorded acoustically but it is difficult to visually verify its genesis. Contrary, snoring patterns induced by drug-induced sleep endoscopy (DISE) can be visually differentiated. The aim of the study was to classify patterns of obstructions and vibration during DISE and to evaluate acoustic characteristics between these different patterns of snoring.

METHODS

DISE was performed in 41 male patients with sleep-disordered breathing. The recorded video sequences (n = 108) were classified visually at a mute mode in different patterns of snoring (velar, velar obstructive, tonsillar, post-apnoeic). The sound tracks of these subgroups were analysed and compared with regard to the parameters sound pressure level, loudness, sharpness, roughness, fluctuations strength and centre frequency.

RESULTS

Obstructive snoring patterns revealed a higher loudness than non-obstructive patterns (>25 sone). Velar snoring showed more roughness (>150 cAsper) than tonsillar and post-apnoeic snoring and revealed the lowest centre frequency (<3000 Hz) of all patterns. Tonsillar snoring presented the highest sharpness (>1.6 acum) whereas post-apnoeic snoring revealed the largest fluctuation strength (>50 cVacil).

CONCLUSION

Different snoring patterns induced by DISE can be classified visually, and an approach to differentiate them acoustically by means of psychoacoustic analyses is demonstrated. On the basis of these results, nocturnal snoring might also be differentiated by psychoacoustic algorithms which could be implemented in acoustic polygraphic screening devices in the future.