Wavelet-based Analysis of Nocturnal Snoring in Apneic Patients

Undergoing Polysomnography

Dimitra MatsikiDept. of Electrical & Computer

Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki,

Greece

Source

Proceedings of the 29th Annual International Conference of the IEEE EMBS

Cite International, Lyon, FranceAugust 2-26, 2007.

keywords

Apnea Continuous wavelet transform Nocturnal snoring Total energy distribution Obstructive sleep apnea Polysomnography

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder, characterized by a cessation of respiratory for at least 10 s, corresponding to a complete upper airway (UA) occlusion despite continuous abdominal and chest wall movements.

The gold standard for diagnosing OSA is an overnight multi-channel polysomnography (PSG), which can be time-consuming and labour-intensive in setting up and in the subsequent analysis. Therefore, many researchers have attempted to search for other modalities, such as airflow , nasal pressure , and oxygen saturation , to detect OSA. However, these studies require at least a physical contact sensor, which may cause discomfort to the patients. In addition, specific expertise may be needed at the test site for correct placement of sensors.

Abstract

Article Outline Introduction Methodology

The continuous wavelet transform(CWT) The morlet wavelet Data analysis

Implementation Results And Discussion Concluding remarks

Introduction

Introduction

Methodology

The continuous wavelet transform(CWT) The morlet wavelet Data analysis

Implementation

Results And Discussion

Figure (a) shows a typical example of a snoring sound in the time domain.

Results And Discussion

Figure (b c) illustrate the corresponding frequency content of the snoring signal of figure (a), split in two sections, i.e.,0-0.59s and 0.59-1.46s,respectively.

There is no significant change in the power spectrum between the two time sections.

Results And Discussion

Figure (d) the magnitude of the CWT of the snoring sound of figure (a)

The spectral characteristics of the signal do change over time.

Results And Discussion

Concluding remarks

References

Summarize and my realization According to read this paper, I have mastered many specialized words which I don’t

realized before. Such as Apneic, 从名词 apnoea( 呼吸暂停 ) 演化而来 polysomnography

(PSG), 专有名词

exponential decay( 指数衰减 ) pseudoperiodic( 赝周期的、非周期的 ) I will confirm these words:EEG( 脑电图 ),EMG （肌电图） ,EOG （眼电图）

Quentions Could formant frequencies of snore signals be an

alternative means for the diagnosis of obstructive sleep apnea （ OSA ） ?

Objective: To study the feasibility of using acoustic signatures in snore signals for the

diagnosis of obstructive sleep apnea .

I want to further analyse that acoustic signatures in snore signals carry information for OSA diagnosis, and snore-based analysis might potentially be a non-invasive and inexpensive diagnostic approach for mass screening of OSA.

Thank you

2009-12