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논문 기본 정보

자료유형
학술저널
저자정보
Seungyoon Nam (University of Science and Technology) John Lorenzo Bautista (University of Science and Technology) Chanyoung Hahm (Electronics and Telecommunications Research Institute) Hyunsoon Shin (University of Science and Technology)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.11 No.2
발행연도
2022.4
수록면
97 - 104 (8page)

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초록· 키워드

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The photoplethysmography signal is composed of a cardiac-synchronous pulsatile waveform and different parts, which is modulated in amplitude by respiration. This paper presents a new indexing method similar to the apnea-hypopnea index and respiratory disturbance index for the self-diagnosis of sleep apnea symptoms (central and obstructed apnea) by using only a photoplethysmogram (PPG) signal. Sleep apnea is a sleeping disorder from several chronic conditions in which partial or complete cessation of breathing occurs many times throughout sleep at night. A respiratory rate signal (respiration-induced intensity variation) is modulated by synchronizing with the breathing rhythm extracted from PPG using a reflected light on the top of the wrist. This paper presents a new automated recognition and estimation method for daytime apnea and sleep-induced apnea using a wristwatch-type wearable device that can recognize irregular breathing using respiratory rate frequency-based features. The new respiratory effort strength index is proposed to quantify sleep apnea by determining how much a patient is suffering.

목차

Abstract
1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
References

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