Title page for etd-0717108-021155


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URN etd-0717108-021155
Author Hao-chih Chiu
Author's Email Address No Public.
Statistics This thesis had been viewed 5585 times. Download 2191 times.
Department Mechanical and Electro-Mechanical Engineering
Year 2007
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Detecting Slow Wave Sleep by Using a single Channel EEG Signal.
Date of Defense 2008-07-04
Page Count 64
Keyword
  • slow wave sleep
  • EEG
  • Abstract One of the important topics in sleep medicine is sleep structure. Normal sleep consists of rapid eye movement (REM) sleep and nonrapid eye movement (NRME) sleep states. NREM sleep can be further classified into stage 1, 2 and slow wave sleep (SWS) according to the current sleep scoring standard. Among them, SWS has been considered to be very important due to its r restorative value.
    The goal of this research is to detect SWS by using a single channel EEG signal. Its applications can be divided into two phases. In the first phase, a personalized SWS detector is designed for each individuals By combining these personalized SWS detectors, the second phase develops a general SWS detection method that can be applied to general population with any personalized training process.
    By applying the proposed method to 62 persons, the experimental results show that the proposed method, in average, achieves 90.69% classification accuracy 90.09% sensitivity and 93.97% specificity. Our experimental results also demonstrate, when applied to persons with higher AHI (apnoea-hypopnea index) values, the proposed method can still provided satisfactory results.
    Advisory Committee
  • Jiann-Der Lee - chair
  • Liang-Wen HANG - co-chair
  • Chen-Wen Yen - advisor
  • Files
  • etd-0717108-021155.pdf
  • indicate access worldwide
    Date of Submission 2008-07-17

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