Skip to main content

Part of the book series: IFMBE Proceedings ((IFMBE,volume 43))


Insomnia is a sleep disorder that causes disturbance in a normal sleep pattern resulting from the difficulties to fall asleep or to stay asleep. Biosignals of human body if measured are also affected due to these abnormal conditions. A current practise in diagnosing insomnia is through clinical interview by the physician which is subjective and suffers from human error judgement. Therefore, a more reliable and accurate diagnostic tools are needed to help physician in making decision. The objective of this study is to classify healthy and insomnia by implementing advanced classification technique based on Artificial Neural Network (ANN).

In this study, sleep EEG and ECG signals of 10 insomnia patients and 10 healthy subjects are analysed. Several linear and nonlinear features are extracted from the denoised signals: linear features (power spectral of EEG frequency bands, brain rate, Hjorth parameters, heart rate variability) and nonlinear features (Largest Lyapunov Exponent (LLE), Sample Entropy and Correlation Dimension (CD)).

For classification purpose, a Feedforward Neural Network (FNN) is implemented to classify the two groups. Half of the data is used for training and the other half is used for testing the classifier. The Levenberg Marquardt backpropagation algorithm is used as a training function. Several numbers of hidden layers are tested in order to achieve optimum classification accuracy. A classification accuracy of 81.3 % is obtained for 3 hidden layers This result shows that the combination of features extracted from EEG and ECG signals during sleep and FFN are useful to be adopted as a biomarker and classifier in identifying insomnia.of FNN.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Abdullah, H., Penzel, T., Cvetkovic, D. (2014). Detection of Insomnia from EEG and ECG. In: Goh, J. (eds) The 15th International Conference on Biomedical Engineering. IFMBE Proceedings, vol 43. Springer, Cham.

Download citation

  • DOI:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02912-2

  • Online ISBN: 978-3-319-02913-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics