+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Pitch jump probability measures for the analysis of snoring sounds in apnea

Pitch jump probability measures for the analysis of snoring sounds in apnea

Physiological Measurement 26(5): 779-798

Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. Diagnostic systems intent on using snore-related sounds (SRS) face the tough problem of how to define a snore. In this paper, we present a working definition of a snore, and propose algorithms to segment SRS into classes of pure breathing, silence and voiced/unvoiced snores. We propose a novel feature termed the 'intra-snore-pitch-jump' (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivities of 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ have the potential to be good candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment. The segmentation results presented in this paper have been derived using data from eight patients as the training set and another eight patients as the testing set. ISPJ-based OSA detection results have been derived using training data from 16 subjects and testing data from 29 subjects.

Please choose payment method:

(PDF emailed within 0-6 h: $19.90)

Accession: 012420653

Download citation: RISBibTeXText

PMID: 16088068

DOI: 10.1088/0967-3334/26/5/016

Related references

A simple procedure for quantitative and time coded detection of snoring sounds in apnea and snoring patients. Laryngologie, Rhinologie, Otologie 67(9): 449-452, 1988

Spectral analysis of snoring sounds for the diagnosis of sleep apnea syndrome. European Archives of Oto-Rhino-Laryngology 257(2): 97-98, 2000

Frequency analysis of snoring sounds during simulated and nocturnal snoring. European Archives of Oto-Rhino-Laryngology 265(12): 1553-1562, 2008

Snoring sounds variability as a signature of obstructive sleep apnea. Medical Engineering and Physics 35(4): 479-485, 2013

Using psychoacoustics of snoring sounds to screen for obstructive sleep apnea. Conference Proceedings 2008: 1647-1650, 2009

Automatic snoring sounds detection from sleep sounds via multi-features analysis. Australasian Physical and Engineering Sciences in Medicine 40(1): 127-135, 2016

Energy types of snoring sounds in patients with obstructive sleep apnea syndrome: a preliminary observation. Plos One 7(12): E53481, 2013

Snoring analysis for the screening of Sleep Apnea Hypopnea Syndrome with a single-channel device developed using polysomnographic and snoring databases. Conference Proceedings 2011: 8331-8333, 2012

Subgrouping Persons with Snoring and/or Apnea by Using Anthropometric and Cephalometric Measures. Sleep And Breathing 5(2): 079-092, 2001

Subgrouping persons with snoring and/or apnea by using anthropometric and cephalometric measures. Sleep and Breathing 5(2): 79-91, 2002

Snoring frequencies and site of origin of snoring sounds. Practica Otologica Kyoto (SUPPL 39): 1-31, 1990

Detection of post apnea sounds and apnea periods from sleep sounds. Conference Proceedings 2011: 6075-6078, 2012

Digital signal analysis of snoring sounds in children. International Journal of Pediatric Otorhinolaryngology 20(3): 193-202, 1990

Distinguishing snoring sounds from breath sounds: a straightforward matter?. Sleep and Breathing 18(1): 169-176, 2014

The impact of the microphone position on the frequency analysis of snoring sounds. European Archives of Oto-Rhino-Laryngology 266(8): 1315-1322, 2008