The acoustic properties of snores

Abstract

This study was undertaken in an attempt to characterize the acoustic properties of snoring sounds in the time and frequency domains, and to correlate between these properties and the mechanical events underlying their production. Three experimental set-ups were used: 1) Dog model--six mongrel dogs, in which partial upper airway obstruction was created by an implanted supraglottic balloon. Flow, supraglottic pressure, and snoring sounds were recorded during different degrees of obstruction. Fifteen to 20 snores from each dog (total 100 snores) were analysed. 2) Simulated human snores--Six simulated snores from each of four subjects were recorded in two locations (trachea and ambient) with simultaneous airflow, and their correlations examined. 3) Snoring patients--snores were recorded with an ambient microphone from nine subjects with "heavy" snoring and no obstructive sleep apnoea (OSA). Forty to 50 snores from each subject were analysed (total of 400 snores). The snoring sound was analysed in the time (time-expanded waveform) and frequency (power spectrum) domains. After analysing these snores, we were able to identify two dominant patterns which are distinctly different from each other: the "simple-waveform" and the "complex-waveform". The complex-waveform snore is characterized by repetitive, equally-spaced, train of sound structures, starting with a large deflection followed by a decaying amplitude wave. In the frequency domain, it is characterized by multiple, equally-spaced peaks of power (comb-like spectrum). Simple-waveform snores have a quasi-sinusoidal waveform, with a range of variants, and almost no secondary internal oscillations. Their power spectrum contains only 1-3 peaks, of which the first is the most prominent. We developed a mathematical representation of these waveforms, which is presented along with its implications. The complex-waveform snores result from colliding of the airway walls and represent actual brief airway closure. Simple-waveform snores are of higher frequency and probably result from oscillation around a neutral position without actual closure of the lumen.

Acoustic analysis of snoring before and after palatal surgery

“…Vibration of the soft palate is believed to generate a relatively low-frequency sound [19][20][21], and both surgical procedures reduced the energy content of the lowerfrequency sound bands with the most sustained effect being seen in the 0-250-Hz band. The transient change in periodicity observed in this study is also in keeping with a soft palatal effect, as studies in animals and humans [6] have shown that the flapping tremor of the soft palate produces a complex, lowfrequency (64-135 Hz), highly periodic waveform. However, surgery did not significantly reduce the overall loudness of the snores that occurred, with no difference between the pre-and late post-operative data.…”

“…Potential sites of snoring sound include the vibration of upstream structures (e.g. soft palate), oscillations of the airway walls at the point of maximal collapse and the turbulent nature of airflow itself [6,25]. Although the soft palate is assumed to be the primary noise generator, other structures of the supraglottis or oropharynx, as well as tongue base and Data are presented as n (%).…”

“…Although snoring can arise from the vibration of many structures in the upper airway, the soft palate is considered to be the major sound generator [6][7][8]. Based on this assumption, various types of palatal surgical techniques have been developed.…”

“…Acoustic analysis of snoring sound has identified two main types of snoring waveform: 1) a complex waveform of low-frequency sound, generated as a result of collision of opposing airway walls during periods of brief airway closure, typical of palatal flutter; and 2) a simple waveform sound with a quasi-sinusoidal pattern thought to result from oscillations of the airway walls around a neutral position without closure of the airway lumen [6]. To date, there are few rigorous, randomised, controlled clinical trials relating to snoring surgery.…”

Efficient snoring and breathing detection based on sub-band spectral statistics

“…Beck et al [10] previously demonstrated that snoring and breathing usually exhibit a strong energy output in the range from 64 Hz to 800 Hz. Herein, we investigated the spectral signals in that band and found the following additional distinctive characteristics.…”