Telephonic Analysis of the Snoring Sound Spectrum

WOS: 000343639200003PubMed: 24913290Objective: Snoring is a sound caused by vibration of collapsed and/or unsteady airway walls of the pharynx and soft palate. We compared stored spectra of snoring sounds recorded via cell phone (CP) and a microphone placed over the head (head phone [HP]). Methods: Thirty-four snoring patients were included in this prospective study. Groups were identified by reference to body mass index (BMI) values: group I, BMI = 30 kg/m(2) (n = 16). Snoring sounds were recorded using CPs and HPs and digitally analyzed. We identified the frequencies with the highest snoring powers (F-max values) and snoring sound intensity levels (SSILs). Results: F-max ranged from 520 to 985 Hz in HP recordings and from 845 to 1645 Hz in CP recordings. Snoring sound intensity level values increased in proportion to BMI and were 6 to 24 dB in HP recordings and 19 to 52 dB in CP recordings. Thus, the CP values of F-max and SSIL were higher than the HP values. In obese patients of group 3, almost all F-max and SSIL values were higher than those of groups 1 and 2. In particular, the CP F-max values were elevated in such patients. The advanced technologies used in modern CPs may allow some snoring sounds in susceptible individuals to be defined as oronasal. Conclusion: Cell phone technology allows snoring to be evaluated in patients located in areas remote from a hospital. To explore the intensity of snoring and to postoperatively monitor the efficacy of surgery used to treat snoring, telephonic sound analysis is both new and effective and reduces the need for patient attendance at a hospital. Those experiencing severe snoring and/or who are obese should be told of what can be done to solve such problems.Continuous Education and Scientific Research AssociationThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Except data collection, preparation of this article including designing and planning was supported by the Continuous Education and Scientific Research Association

An acoustical respiratory phase segmentation algorithm using genetic approach

10.1007/s11517-009-0518-0Medical and Biological Engineering and Computing479941-95