Mobile Apnea Screening System for at-home Recording and Analysis of Sleep Apnea Severity

Mathias P. Bonnesen, Helge Bjarup Dissing Sørensen, Poul Jennum

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Obstructive Sleep Apnea (OSA) is a common sleep disorder affecting $>10\%$ of the middle-aged population. The gold standard diagnostic procedure is the Polysomnography (PSG), which is both costly and time consuming. A simple and non-expensive screening therefore would be of great value. This study presents a novel at-home screening method for OSA using a smartphone, a microphone and a modified armband, to measure continuous biological signals during a whole night sleep. A signal-processing algorithm was used to classify the subjects, into classes according to severity of the disorder. The system was validated by conducting a routine sleep study parallel to the data acquisition on a total of 23 subjects. Both binary and 4-class classification problems were tested. The binary classifications showed the best results with sensitiv- ities between 92.3 % and 100 %, and accuracies between 78.3 % and 91.3 %. The 4-class classification was not as successful with a sensitivity of 75 %, and accuracies of 56.5 % and 60 %. We conclude that mobile smartphone technology has a potential for OSA ambulatory screening.
Original languageEnglish
Title of host publicationProceedings of 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2018
Pages457-460
ISBN (Print)9781538636466
DOIs
Publication statusPublished - 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Hawaii Convention Center, Honolulu, United States
Duration: 17 Jul 201821 Jul 2018
https://embc.embs.org/2018/

Conference

Conference40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
LocationHawaii Convention Center
CountryUnited States
CityHonolulu
Period17/07/201821/07/2018
Internet address
Series2017 39th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (embc)
ISSN1558-4615

Keywords

  • Sleep apnea
  • Accelerometers
  • Support vector machines
  • Event detection
  • Correlation
  • Sensitivity

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