title: Computerized analysis of snoring in sleep apnea syndrome.
abstract: The International Classification of Sleep Disorders lists 90 disorders. Manifestations, such as snoring, are important signs in the diagnosis of the Obstructive Sleep Apnea Syndrome; they are also socially undesirable.
  
  
  OBJECTIVE
  The aim of this paper was to present and evaluate a computerized tool that automatically identifies snoring and highlights the importance of establishing the duration of each snoring event in OSA patients.
  
  
  METHODS
  The low-sampling (200 Hz) electrical signal that indicates snoring was measured during polysomnography. The snoring sound of 31 patients was automatically classified by the software. The Kappa approach was applied to measure agreement between the automatic detection software and a trained observer. Student's T test was applied to evaluate differences in the duration of snoring episodes among simple snorers and OSA snorers.
  
  
  RESULTS
  Of a total 43,976 snoring episodes, the software sensitivity was 99. 26%, the specificity was 97. 35%, and Kappa was 0. 96. We found a statistically significant difference (p <0. 0001) in the duration of snoring episodes (simple snoring x OSA snorers).
  
  
  CONCLUSIONS
  This computer software makes it easier to generate quantitative reports of snoring, thereby reducing manual labor.
authors.affiliation: MSc, professor at the Instituto Federal de Educação Tecnológica de São Paulo (IFSP). Electronic address: fabio.shiomi@cefetsp.br.
authors.forename: Fabio Koiti
authors.initials: FK
authors.lastname: Shiomi
authors.affiliation: Doctoral degree, adjunct professor in the graduate program of the Health Informatics Department, UNIFESP.
authors.forename: Ivan Torres
authors.initials: IT
authors.lastname: Pisa
authors.affiliation: Doctoral degree, tutoring professor in the graduate program of the Health Informatics Department, UNIFESP.
authors.forename: Carlos José Reis
authors.initials: CJR
authors.lastname: de Campos
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012891:Sleep Apnea Syndromes / Q000150:complications / Q000175:diagnosis*; D012913:Snoring / Q000175:diagnosis* / Q000209:etiology; D055815:Young Adult