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dc.contributor.advisorDing, Yanwu
dc.contributor.authorWang, Zuojun
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science.en_US
dc.description.abstractIn this paper, we introduce a novel cycle identification algorithm using Matlab programming to automatically identify cycles in tidal breathing signals. The algorithm is designed in four steps using filtering, derivation, and other signal processing techniques. To verify the effectiveness of the proposed algorithm, its results are compared with those of cycles identified manually by a human coder. Simulations results show that despite the complexity of the respiratory signals, the proposed algorithm can identify cycles more correctly and more efficiently than cycles identified by hand-coding. This algorithm can serve as an important first step toward timely identification and coding of more complex respiratory signals, such as those underlying speech productions.en_US
dc.format.extentix, 28 leaves, ill.en
dc.publisherWichita State Universityen_US
dc.rightsCopyright Zuojun Wang, 2010. All rights reserveden
dc.subject.lcshElectronic dissertationsen
dc.titleAutomatic cycle identification in tidal breathing signalsen_US

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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science
  • Master's Theses
    This collection includes Master's theses completed at the Wichita State University Graduate School (Fall 2005 --)

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