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Automatic cycle identification in tidal breathing signals

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dc.contributor.advisor Ding, Yanwu
dc.contributor.author Wang, Zuojun
dc.date.accessioned 2011-09-02T19:59:42Z
dc.date.available 2011-09-02T19:59:42Z
dc.date.copyright 2010 en
dc.date.issued 2010-12
dc.identifier.other t10127
dc.identifier.uri http://hdl.handle.net/10057/3756
dc.description Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science. en_US
dc.description.abstract In 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.extent ix, 28 leaves, ill. en
dc.language.iso en_US en_US
dc.publisher Wichita State University en_US
dc.rights Copyright Zuojun Wang, 2010. All rights reserved en
dc.subject.lcsh Electronic dissertations en
dc.title Automatic cycle identification in tidal breathing signals en_US
dc.type Thesis en_US

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