Discriminative methods based on sparse representations of pulse oximetry signals for sleep apnea-hypopnea detection

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• 作者：R.E. Roló ; n^a ; ^{rrolon@sinc.unl.edu.ar} ; L.D. Larrateguy^b ; L.E. Di Persia^a ; R.D. Spies^c ; H.L. Rufiner^a ; ^d
• 关键词：Sleep apnea&ndash ; hypopnea syndrome ; Sparse representations ; Dictionary learning ; Neural networks
• 刊名：Biomedical Signal Processing and Control
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：33
• 期：Complete
• 页码：358-367
• 全文大小：1823 K
• 卷排序：33

文摘

Two novel methods to detect apnea–hypopnea events are presented. Sparse representations of only pulse oximetry signals are used. Discriminative information of sparse coefficients is successfully extracted. A neural network for detecting apnea–hypopnea events is used.