A novel software for comprehensive analysis of cardiotocography signals "CTG-OAS"

Küçük Resim Yok

Tarih

2017

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Institute of Electrical and Electronics Engineers Inc.

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

The research interest in fetal heart rate (FHR) monitoring dates back to the 1960s, and the breakthrough on fetal surveillance has been seen during the 1990s with computerized systems. Notwithstanding the general use of cardiotocography (CTG) in fetal monitoring, the assessment of fetal well-being exhibits a significant inter- and even intraobserver variability. Computerized CTG analysis has seen as the most promising way to tackle of the main shortcomings of visual CTG assessment. In this study, a novel software developed for research purposes is introduced. The software named as CTG Open Access Software (CTG-OAS) characterizes FHR signals by using comprehensive features obtained from different fields such as morphological, linear, nonlinear, time-frequency, discrete wavelet transform, and image-based time-frequency domains. The software also covers the main procedures which are necessary for the context of machine learning. More specifically, CTG-OAS presents several tools for performing the preprocessing, feature extraction, feature selection, and classification processes. The proposed software was practiced on CTU-UHB database with 552 raw CTG samples. In addition, a case study with Support Vector Machine classifier was performed in the study via CTG-OAS. According to experimental results, statistical parameters were obtained as accuracy equal to 87.97%, sensitivity equal to 89.04%, specificity equal to 81.36% and, quality index equal to 85.11%. © 2017 IEEE.

Açıklama

2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- 115012

Anahtar Kelimeler

Biomedical signal processing, Cardiotocography, Classification, Fetal heart rate, Machine learning, Software

Kaynak

IDAP 2017 - International Artificial Intelligence and Data Processing Symposium

WoS Q Değeri

Scopus Q Değeri

N/A

Cilt

Sayı

Künye