title: Can we discriminate between apnea and hypopnea using audio signals?
abstract: Obstructive sleep apnea (OSA) affects up to 14% of the population. OSA is characterized by recurrent apneas and hypopneas during sleep. The apnea-hypopnea index (AHI) is frequently used as a measure of OSA severity. In the current study, we explored the acoustic characteristics of hypopnea in order to distinguish it from apnea. We hypothesize that we can find audio-based features that can discriminate between apnea, hypopnea and normal breathing events. Whole night audio recordings were performed using a non-contact microphone on 44 subjects, simultaneously with the polysomnography study (PSG). Recordings were segmented into 2015 apnea, hypopnea, and normal breath events and were divided to design and validation groups. A classification system was built using a 3-class cubic-kernelled support vector machine (SVM) classifier. Its input is a 36-dimensional audio-based feature vector that was extracted from each event. Three-class accuracy rate using the hold-out method was 84.7%. A two-class model to separate apneic events (apneas and hypopneas) from normal breath exhibited accuracy rate of 94.7%. Here we show that it is possible to detect apneas or hypopneas from whole night audio signals. This might provide more insight about a patient's level of upper airway obstruction during sleep. This approach may be used for OSA severity screening and AHI estimation.
authors.forename: M
authors.initials: M
authors.lastname: Halevi
authors.forename: E
authors.initials: E
authors.lastname: Dafna
authors.forename: A
authors.initials: A
authors.lastname: Tarasiuk
authors.forename: Y
authors.initials: Y
authors.lastname: Zigel
mesh_terms: D000162:Acoustics; D000328:Adult; D000465:Algorithms; D019992:Databases as Topic; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017286:Polysomnography; D012815:Signal Processing, Computer-Assisted; D012890:Sleep; D012891:Sleep Apnea Syndromes / Q000175:diagnosis*; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis* / Q000503:physiopathology