Sensor-Based Sleep Stage Classification Using Deep Learning

Human Data Understanding - Sensors, Models, Knowledge, Bd. 4

Xinyu Huang

ISBN 978-3-8325-5617-4
167 pages, year of publication: 2023
price: 51.50 €
Sensor-Based Sleep Stage Classification Using Deep Learning
Sleep is a cyclic physiological phenomenon, an important aspect of human life activity, which, like sport and diet, is a nutritional element that ensures the growth and development of the organism. Under the influence of various factors such as work and study stress and metabolic disorders, more and more people suffer from various types of sleep disorders. Sleep has become an important research topic in recent years. Sleep stage analysis plays an important role in the early detection and treatment of sleep disorders. However, different age groups show different symptoms of sleep disorders, and different sleep disorders show variability in their different sleep stages. The prevalence of sleep disorders is much higher in children than in adults. Although the classification of sleep stages in adults has been well studied, children show markedly different characteristics of sleep stages. Therefore, there is an urgent need for sleep stage classification in children. With the rapid development of intelligent computing technology, artificial intelligence has found wide application in medical research and health sciences in recent years.

In the field of sleep medicine, deep learning approaches can efficiently and automatically learn abstracted relevant sleep features from collected sleep data to accurately interpret children's sleep stages accordingly. Compared to traditional sleep data analysis, this saves many manual and time resources for data annotation and helps sleep experts reduce the risk of misdiagnosing sleep disorders based on their prior knowledge. In this context, this book presents several advanced deep learning-based approaches for sleep stage classification in children using time series polysomnography recordings acquired from clinical sensor devices. Significantly improved performance in classifying sleep stages in children suffering from sleep disorders demonstrates the great potential of joint research and development between artificial intelligence and the field of sleep medicine.

cover cover cover cover cover cover cover cover cover
Table of contents (PDF)

Preview (PDF)


  • Artificial intelligence
  • Medical data science
  • Time-series analysis
  • Deep learning
  • Sleep stage classification


51.50 €
in stock

49.50 €
61.50 €
65.50 €

(D) = Within Germany
(W) = Abroad

*You can purchase the eBook (PDF) alone or combined with the printed book (eBundle). In both cases we use the payment service of PayPal for charging you - nevertheless it is not necessary to have a PayPal-account. With purchasing the eBook or eBundle you accept our licence for eBooks.

For multi-user or campus licences (MyLibrary) please fill in the form or write an email to