Title :
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
fDate :
Aug. 31 2013-Sept. 2 2013
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;
Conference_Titel :
Modelling, Identification & Control (ICMIC), 2013 Proceedings of International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-0-9567157-3-9
