PSORR - An unsupervised feature selection technique for fetal heart rate

Author

Azar, Ahmad Taher ; Banu, P. K. Nizar ; Inbarani, H.H.

Author_Institution

Fac. of Comput. & Inf., Benha Univ., Benha, Egypt

fYear

2013

fDate

Aug. 31 2013-Sept. 2 2013

Firstpage

60

Lastpage

65

Abstract

Fetal heart activity is generally monitored using a CardioTocoGraph (CTG) which estimates the fetal tachogram based on the evaluation of ultrasound pulses reflected from the fetal heart. It consists in a simultaneous recording and analysis of Fetal Heart Rate (FHR) signal, uterine contraction activity and fetal movements. Generally cardiotocograph comprises more number of features. This paper aims to identify the important features, consequently reducing the number of features to assess the fetal heart rate. The features are selected by using Unsupervised Particle Swarm Optimization (PSO) based Relative Reduct and are tested by using various measures of diagnostic accuracy.

Keywords

biomedical ultrasonics; medical signal processing; particle swarm optimisation; unsupervised learning; CTG; CardioTocoGraph; PSORR; fetal heart activity; fetal heart rate; fetal heart rate signal; fetal movements; fetal tachogram; ultrasound pulses; unsupervised feature selection technique; unsupervised particle swarm optimization based relative reduct; uterine contraction activity; Accuracy; Sensitivity; Stress; Stress measurement; Cardiotocogram; Feature selection; Fetal Heart Rate; PSO; Relative Reduct; Unsupervised;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling, Identification & Control (ICMIC), 2013 Proceedings of International Conference on

Conference_Location

Cairo

Print_ISBN

978-0-9567157-3-9

Type

conf

Filename

6642175