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International Journal of Antennas and Propagation
Volume 2013, Article ID 969603, 8 pages
http://dx.doi.org/10.1155/2013/969603
Research Article

A Novel Method for Recognition of Bioradiolocation Signal Breathing Patterns for Noncontact Screening of Sleep Apnea Syndrome

1Remote Sensing Laboratory, Bauman Moscow State Technical University, Moscow 105005, Russia
2Department of Biomedical Engineering, Bauman Moscow State Technical University, Moscow 105005, Russia
3Sleep Laboratory, Almazov Federal Heart, Blood and Endocrinology Centre, Saint Petersburg 197341, Russia
4State Research and Testing Institute of Military Medicine of the Ministry of Defense of Russia, Moscow 127083, Russia

Received 10 March 2013; Accepted 9 June 2013

Academic Editor: Francesco Soldovieri

Copyright © 2013 Maksim Alekhin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A novel method for recognition of breathing patterns of bioradiolocation signals breathing patterns (BSBP) in the task of noncontact screening of sleep apnea syndrome (SAS) is proposed and implemented on the base of wavelet transform (WT) and neural network (NNW) applications. Selection of the optimal parameters of WT includes determination of the proper level of wavelet decomposition and the best basis for feature extraction using modified entropy criterion. Selection of the optimal properties of NNW includes defining the best number of hidden neurons and learning algorithm for the chosen NNW topology. The effectiveness of the proposed approach is tested on clinically verified database of BRL signals corresponding to the three classes of breathing patterns: obstructive sleep apnea (OSA); central sleep apnea (CSA); normal calm sleeping (NCS) without sleep-disordered breathing (SDB) episodes.