|Title:||Apnea detection based on hidden Markov model kernel||Authors:||Travieso, Carlos M.
Alonso, Jesús B.
Ticay-Rivas, Jaime R.
Del Pozo-Baños, Marcos
|UNESCO Clasification:||3307 Tecnología electrónica||Keywords:||Apnea Detection, Hidden Markov Model, Kernel Building, Pattern Recognition, Non-linear Processing||Issue Date:||2011||Publisher:||0302-9743||Journal:||Lecture Notes in Computer Science||Conference:||5th International Conference on Nonlinear Speech Processing (NOLISP 2011)
5th International Conference on Nonlinear Speech Processing, NOLISP 2011
|Abstract:||This work presents a new system to diagnose the syndrome of obstructive sleep apnea (OSA) that includes a specific block for the removal of Electrocardiogram (ECG) artifacts and the R wave detection. The system is modeled by ECG cepstral coefficients. The final decision is done with two different approaches. The first one is based on Hidden Markov Model (HMM), as classifier. On the other hand, another classification system is based on Support Vector Machines, being the parameterization based on the transformation of HMM by a kernel. Our results reached up to 98.67%.||URI:||http://hdl.handle.net/10553/44041||ISBN:||9783642250194||ISSN:||0302-9743||DOI:||10.1007/978-3-642-25020-0_10||Source:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 7015 LNAI, p. 71-79|
|Appears in Collections:||Actas de congresos|
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