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Breathing Characteristics Analysis of Snoring State Using Air Flow in the Nose

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2019, 14(6), pp.585-594
  • DOI : 10.34163/jkits.2019.14.6.001
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Received : September 25, 2019
  • Accepted : December 7, 2019
  • Published : December 31, 2019

Kwangmin Hyun 1 HwanSeog Kim 1 Baek-Ki Kim ORD ID 1

1강릉원주대학교

Accredited

ABSTRACT

In this paper, a method for analyzing breathing characteristics in real time by measuring the change in air pressure intensity flowing through the nasal cavity when snoring occurs, and an algorithm for separating and detecting signal components with converting the measured continuous time signal into discrete time signal were proposed. A commercial digital miniature piezo-resistive sensor was inserted into the nasal cavity to measure changes in air pressure intensity during breathing. The snoring phenomenon was analyzed with snore-breathing vibration within the audible frequency band, using the magnitude of the change in respiratory air pressure and the frequency characteristic causing the auditory effects. Although the digital small piezo-resistive sensor used in this experiment works slowly, we used the undersampled data for the digital signal processing because the purpose of the signal measurement is to obtain slowly varying respiratory air pressure signal and to detect and existence of snoring itself, not to analyze the exact frequency components of a snoring signal. Through this process, the normal respiratory signal component and the abnormal snoring signal component were separated using a real-time digital filter with the characteristic of they have different frequencies each other. And the snoring signal was detected with the envelope detection method to detect the length of time for snoring duration. Further, it is necessary to study the medical meaning analysis of the separated abnormal signal components, and to apply it to various types of snoring phenomena to be applied in real life.

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