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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
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Source
Proceedings of the 29th Annual International Conference of the IEEE EMBS
Cite International, Lyon, FranceAugust 2-26, 2007.
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keywords
Apnea Continuous wavelet transform Nocturnal snoring Total energy distribution Obstructive sleep apnea Polysomnography
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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.
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Abstract
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Article Outline Introduction Methodology
The continuous wavelet transform(CWT) The morlet wavelet Data analysis
Implementation Results And Discussion Concluding remarks
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Introduction
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Introduction
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Methodology
The continuous wavelet transform(CWT) The morlet wavelet Data analysis
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Implementation
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Results And Discussion
Figure (a) shows a typical example of a snoring sound in the time domain.
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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.
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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.
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Results And Discussion
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Concluding remarks
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References
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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)
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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.
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Thank you
2009-12