Millions of books in English, Spanish and other languages. Free UK delivery 

menu

0
  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional
portada Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea: From Feature-Engineering to Deep-Learning Approaches
Type
Physical Book
Publisher
Language
Inglés
Pages
90
Format
Hardcover
Dimensions
23.4 x 15.6 x 0.8 cm
Weight
0.34 kg.
ISBN13
9783031328312

Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea: From Feature-Engineering to Deep-Learning Approaches

Fernando Vaquerizo Villar (Author) · Springer · Hardcover

Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea: From Feature-Engineering to Deep-Learning Approaches - Vaquerizo Villar, Fernando

New Book

£ 186.35

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Wednesday, July 24 and Wednesday, July 31.
You will receive it anywhere in United Kingdom between 1 and 3 business days after shipment.

Synopsis "Automated Analysis of the Oximetry Signal to Simplify the Diagnosis of Pediatric Sleep Apnea: From Feature-Engineering to Deep-Learning Approaches"

This book describes the application of novel signal processing algorithms to improve the diagnostic capability of the blood oxygen saturation signal (SpO2) from nocturnal oximetry in the simplification of pediatric obstructive sleep apnea (OSA) diagnosis. For this purpose, 3196 SpO2 recordings from three different databases were analyzed using feature-engineering and deep-learning methodologies. Particularly, three novel feature extraction algorithms (bispectrum, wavelet, and detrended fluctuation analysis), as well as a novel deep-learning architecture based on convolutional neural networks are proposed. The proposed feature-engineering and deep-learning models outperformed conventional features from the oximetry signal, as well as state-of-the-art approaches. On the one hand, this book shows that bispectrum, wavelet, and detrended fluctuation analysis can be used to characterize changes in the SpO2 signal caused by apneic events in pediatric subjects. On the other hand, it demonstrates that deep-learning algorithms can learn complex features from oximetry dynamics that allow to enhance the diagnostic capability of nocturnal oximetry in the context of childhood OSA. All in all, this book offers a comprehensive and timely guide to the use of signal processing and AI methods in the diagnosis of pediatric OSA, including novel methodological insights concerning the automated analysis of the oximetry signal. It also discusses some open questions for future research.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews