Comparison of snoring sounds between natural and drug-induced sleep recorded using a smartphone

How to objectively measure snoring: a systematic review

PURPOSE

Snoring is the most common symptom of obstructive sleep apnea. Various objective methods of measuring snoring are available, and even if the measurement is performed the same way, communication is difficult because there are no common reference values between the researcher and clinician with regard to intensity and frequency, among other variables. In other words, no consensus regarding objective measurement has been reached. This study aimed to review the literature related to the objective measurement of snoring, such as measurement devices, definitions, and device locations.

METHODS

A literature search based on the PubMed, Cochrane, and Embase databases was conducted from the date of inception to April 5, 2023. Twenty-nine articles were included in this study. Articles that mentioned only the equipment used for measurement and did not include individual details were excluded from the study.

RESULTS

Three representative methods for measuring snoring emerged. These include (1) a microphone, which measures snoring sound; (2) piezoelectric sensor, which measures snoring vibration; and (3) nasal transducer, which measures airflow. In addition, recent attempts have been made to measure snoring using smartphones and applications.

CONCLUSION

Numerous studies have investigated both obstructive sleep apnea and snoring. However, the objective methods of measuring snoring and snoring-related concepts vary across studies. Consensus in the academic and clinical communities on how to measure and define snoring is required.

Comparison of Drug-Induced Sleep Endoscopy and Natural Sleep Endoscopy in the Assessment of Upper Airway Pathophysiology During Sleep: Protocol and Study Design

Study Objectives: Obstructive sleep apnea (OSA) is increasingly recognized as a complex and heterogenous disorder. As a result, a "one-size-fits-all" management approach should be avoided. Therefore, evaluation of pathophysiological endotyping in OSA patients is emphasized, with upper airway collapse during sleep as one of the main features. To assess the site(s) and pattern(s) of upper airway collapse, natural sleep endoscopy (NSE) is defined as the gold standard. As NSE is labor-intensive and time-consuming, it is not feasible in routine practice. Instead, drug-induced sleep endoscopy (DISE) is the most frequently used technique and can be considered as the clinical standard. Flow shape and snoring analysis are non-invasive measurement techniques, yet are still evolving. Although DISE is used as the clinical alternative to assess upper airway collapse, associations between DISE and NSE observations, and associated flow and snoring signals, have not been quantified satisfactorily. In the current project we aim to compare upper airway collapse identified in patients with OSA using endoscopic techniques as well as flow shape analysis and analysis of tracheal snoring sounds between natural and drug-induced sleep. Methods: This study is a blinded prospective comparative multicenter cohort study. The study population will consist of adult patients with a recent diagnosis of OSA. Eligible patients will undergo a polysomnography (PSG) with NSE overnight and a DISE within 3 months. During DISE the upper airway is assessed under sedation by an experienced ear, nose, throat (ENT) surgeon using a flexible fiberoptic endoscope in the operating theater. In contrast to DISE, NSE is performed during natural sleep using a pediatric bronchoscope. During research DISE and NSE, the standard set-up is expanded with additional PSG measurements, including gold standard flow and analysis of tracheal snoring sounds. Conclusions: This project will be one of the first studies to formally compare collapse patterns during natural and drug-induced sleep. Moreover, this will be, to the authors' best knowledge, the first comparative research in airflow shape and tracheal snoring sounds analysis between DISE and NSE. These novel and non-invasive diagnostic methods studying upper airway mechanics during sleep will be simultaneously validated against DISE and NSE. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT04729478.

Acoustic analyses of snoring sounds using a smartphone in patients undergoing septoplasty and turbinoplasty

PURPOSE

Several studies have been performed using recently developed smartphone-based acoustic analysis techniques. We investigated the effects of septoplasty and turbinoplasty in patients with nasal septal deviation and turbinate hypertrophy accompanied by snoring by recording the sounds of snoring using a smartphone and performing acoustic analysis.

METHODS

A total of 15 male patients who underwent septoplasty with turbinoplasty for snoring and nasal obstruction were included in this prospective study. Preoperatively and 2 months after surgery, their bed partners or caregivers were instructed to record the snoring sounds. The intensity (dB), formant frequencies (F₁, F₂, F₃, and F₄), spectrogram pattern, and visual analog scale (VAS) score were analyzed for each subject.

RESULTS

Overall snoring sounds improved after surgery in 12/15 (80%) patients, and there was significant improvement in the intensity of snoring sounds after surgery (from 64.17 ± 12.18 dB to 55.62 ± 9.11 dB, p = 0.018). There was a significant difference in the F₁ formant frequency before and after surgery (p = 0.031), but there were no significant differences in F₂, F₃, or F₄. The change in F₁ indicated that patients changed from mouth breathing to normal breathing. The degree of subjective snoring sounds improved significantly after surgery (VAS: from 5.40 ± 1.55 to 3.80 ± 1.26, p = 0.003).

CONCLUSION

Our results confirm that snoring is reduced when nasal congestion is improved, and they demonstrate that smartphone-based acoustic analysis of snoring sounds can be useful for diagnosis.

A Deep Learning Model for Snoring Detection and Vibration Notification Using a Smart Wearable Gadget

Snoring, a form of sleep-disordered breathing, interferes with sleep quality and quantity, both for the person who snores and often for the person who sleeps with the snorer. Poor sleep caused by snoring can create significant physical, mental, and economic problems. A simple and natural solution for snoring is to sleep on the side, instead of sleeping on the back. In this project, a deep learning model for snoring detection is developed and the model is transferred to an embedded system—referred to as the listener module—to automatically detect snoring. A novel wearable gadget is developed to apply a vibration notification on the upper arm until the snorer sleeps on the side. The gadget is rechargeable, and it is wirelessly connected to the listener module using low energy Bluetooth. A smartphone app—connected to the listener module using home Wi-Fi—is developed to log the snoring events with timestamps, and the data can be transferred to a physician for treating and monitoring diseases such as sleep apnea. The snoring detection deep learning model has an accuracy of 96%. A prototype system consisting of the listener module, the wearable gadget, and a smartphone app has been developed and tested successfully.

Obstruction Patterns During Drug-Induced Sleep Endoscopy vs Natural Sleep Endoscopy in Patients With Obstructive Sleep Apnea

Importance

Drug-induced sleep endoscopy (DISE) has been suggested to be a valuable technique for identifying the obstruction site associated with sleep-disordered breathing. However, the reliability of DISE findings is controversial because the procedure uses sedative drugs, which may have implications for the obstruction patterns observed on DISE.

Objective

To compare the obstruction patterns during DISE with the obstruction patterns during natural sleep endoscopy (NSE).

Design, Setting, and Participants

This prospective cohort study was conducted between June 2013 and May 2018 in Kyungpook National University Chilgok Hospital in Daegu, South Korea. All analysis took place from June 1 to July 31, 2018. Participants had an obstructive sleep apnea diagnosis, were older than 18 years, and had an apnea hypopnea index higher than 5 on type I polysomnography. The patients initially enrolled were excluded from the study for not reaching adequate sleep depth and waking up during insertion of the nasopharyngoscope.

Intervention

Patients underwent DISE using midazolam and NSE without sedatives on 2 different days.

Main Outcomes and Measures

Obstruction findings were observed only in the same range (65-75) of the bispectral index on both days. Obstruction findings were classified according to the VOTE (velum, oropharynx lateral wall, tongue base, and epiglottis) classification. The extent of agreement between DISE and NSE findings was evaluated using Cohen weighted κ value.

Results

The study included 26 patients with snoring or obstructive sleep apnea (mean [SD] age, 44.7 [10.3] years; predominantly male [22 (85%)]). The mean (SD) apnea hypopnea index was 41.9 (17.2) and the lowest mean (SD) oxygen saturation was 79.8% (12.2%). The degree of agreement in upper-airway obstruction between DISE and NSE was 76.9% (Cohen weighted κ = 0.42; 95% CI, 0.02-0.83) in the velum, 88.5% (Cohen weighted κ = 0.84; 95% CI, 0.67-1.01) in the oropharynx lateral wall, 69.2% (Cohen weighted κ = 0.66; 95% CI, 0.46-0.86) in the tongue base, and 92.3% (Cohen weighted κ = 0.67; 95% CI, 0.24-1.11) in the epiglottis. Agreement of configuration of the velum was 88.5% (Cohen weighted κ = 0.50; 95% CI, -0.03 to 1.03) and the epiglottis was 92.3% (Cohen weighted κ = 0.67; 95% CI, 0.24-1.11).

Conclusions and Relevance

Obstruction patterns of the upper airway appeared to be in agreement between DISE and NSE, suggesting that DISE may be a reliable test; future studies of multiple positions and sleep stages with larger sample sizes may confirm these results.

Inter-rater reliability between experienced and inexperienced otolaryngologists using Koo's drug-induced sleep endoscopy classification system

PURPOSE

An ideal, drug-induced sleep endoscopy (DISE) classification system should cover all the upper airways, be simple and practical, and quantify the severity of any obstruction. Excellent validity and reliability are essential. We explored the inter-rater reliability of Koo's DISE classification system in the hands of experienced and inexperienced otolaryngologists.

METHODS

We retrospectively analyzed video images of 100 patients who underwent DISE examination in our hospital between 2015 and 2018. Three experienced and three inexperienced otolaryngologists reviewed and scored all images. We calculated the inter-rater reliabilities of the two groups of otolaryngologists.

RESULTS

Independent of the extent of experience with DISE, detection of retropalatal obstructions (overall agreement: 0.87; kappa value: 0.60), and the degree of such obstructions (overall agreement: 0.67; kappa value: 0.52) were more consistent than were the detection of retrolingual obstructions (overall agreement: 0.61, kappa value: 0.37) and the degree of retrolingual obstructions (overall agreement: 0.20, kappa value: 0.35). Inexperienced observers were in good agreement for palatal obstructions and experienced observers were in good agreement for tongue-base obstructions. All of the otolaryngologists found it difficult to detect a lateral pharyngeal wall obstruction at the retrolingual level.

CONCLUSION

Koo's DISE classification system focuses on surgical treatment, especially by otolaryngologists, and the degree of agreement between the experienced and inexperienced observers was relatively high. The participants' level of experience had a strong impact on scoring. The less-experienced otolaryngologists tended to overlook tongue-base obstructions, focusing instead on relatively simple retropalatal obstructions. In the future, development of a DISE classification system that can be accepted globally will be necessary.