Title page for etd-0717109-161820


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URN etd-0717109-161820
Author Jen-feng Wang
Author's Email Address No Public.
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Department Mechanical and Electro-Mechanical Engineering
Year 2008
Semester 2
Degree Ph.D.
Type of Document
Language zh-TW.Big5 Chinese
Title AHI prediction improvement by oxyhemoglobin desaturation features with new baseline definition and EEG wake information
Date of Defense 2009-06-25
Page Count 110
Keyword
  • Obstructive sleep apnea syndrome
  • Oxyhemoglobin saturation
  • Abstract The diagnosis of obstructive sleep apnea (OSA) syndrome is overnight PSG (mutli-channel system). But it’s hard to be popularized for the general population (about twenty channel signals). In recent decades, several researches were devoted to a replacement system with only one channel signal (oxyhemoglobin saturation). However, it’s hard to match PSG system’s report without EEG wake information. Consequently, two channels (oxyhemoglobin saturation and EEG) were used of this study to enhance the AHI (estimation index for sleep apnea) prediction performance. After surveying the most recent studies, this work proposes a new basleline removal technique for oxygen saturation signal (SpO2) by using median filter. It was proved this technique improves the diagnostic accuracy for OSA. Furthermore, it is also found that by removing the wake periods, diagnostic accuracy can be improved further.
    By counting the number of times that the desaturation level has dropped more than 2% for at least 3 seconds, the correlation coefficient between AHI and proposed feature is 0.9218. In addition, by removing the wake period, this correlation increases to 0.9425. By using this feature to classify patients with AHI value larger than 5, the proposed approach achieves 93.78% accuracy, 95.94% sensitivity, 78.87% specificity f. Such results demonstrate the feasibility of using single SpO2 channel system for OSA diagnosis.
    Advisory Committee
  • Yaw-Terng Su - chair
  • Jau-Wei Perng - co-chair
  • Wei-Huang Lin - co-chair
  • Pei-Chung Chen - co-chair
  • Chen-Wen Yen - advisor
  • Files
  • etd-0717109-161820.pdf
  • indicate access worldwide
    Date of Submission 2009-07-17

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