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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Печать: 0040-2508
ISSN Онлайн: 1943-6009

Выпуски:
Том 78, 2019 Том 77, 2018 Том 76, 2017 Том 75, 2016 Том 74, 2015 Том 73, 2014 Том 72, 2013 Том 71, 2012 Том 70, 2011 Том 69, 2010 Том 68, 2009 Том 67, 2008 Том 66, 2007 Том 65, 2006 Том 64, 2005 Том 63, 2005 Том 62, 2004 Том 61, 2004 Том 60, 2003 Том 59, 2003 Том 58, 2002 Том 57, 2002 Том 56, 2001 Том 55, 2001 Том 54, 2000 Том 53, 1999 Том 52, 1998 Том 51, 1997

Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v78.i1.70
pages 59-69

RECOGNITION OF PREMATURE BIRTHS BY BISPECTRUM-BASED ABDOMINAL ELECTROMYOGRAPHY SIGNAL PROCESSING

O. Viunytskyi
National Aerospace University (Kharkiv Aviation Institute), 17 Chkalov St., Kharkiv, 61070, Ukraine
V. I. Shulgin
National Aerospace University (Kharkiv Aviation Institute), 17, Chkalov St., Kharkiv, 61070, Ukraine
A. V. Totsky
National Aerospace University (Kharkiv Aviation Institute), 17, Chkalov St., Kharkiv, 61070, Ukraine
Karen O. Egiazarian
Tampere University, Tampere, 33720, Finland
O. A. Polotska
V. Karazin National University of Kharkov, 4, Svoboda Sq., Kharkiv, 61077, Ukraine

Краткое описание

A novel technique for detection and recognition of normal and premature births is proposed and experimentally examined. It is based on the extraction of novel class of informative features contained in higher-order spectrum, namely, bispectrum of the abdominal electromyography signals registered on the abdominal surface of pregnant woman. It is demonstrated that the amplitude bispectrum, phase bispectrum and bicoherence signatures computed for electromyography signals can serve as the perspective facilities for detection and recognition of the normal and premature births. The proposed bispectrum-based information features were studied by real-life experimental data processing. Uterine activity corresponding to two weeks and one week before birth for several patients has been investigated. Experimental results obtained for a number of the patients demonstrate the possibility to extract novel classification features contained in the computed biamplitude, biphase and bicoherence signatures.