TY - GEN
T1 - Two-step analysis of the fetal heart rate signal as a predictor of distress
AU - Czabanski, Robert
AU - Wrobel, Janusz
AU - Jezewski, Janusz
AU - Jezewski, Michal
PY - 2012
Y1 - 2012
N2 - Cardiotocography is a biophysical method of fetal state assessment based on analysis of fetal heart rate signal (FHR). The computerized fetal monitoring systems provide a quantitative evaluation of FHR signals, however the effective methods for fetal outcome prediction are still needed. The paper proposes a two-step analysis of fetal heart rate recordings that allows for prediction of the fetal distress. The first step consists in classification of FHR signals with Weighted Fuzzy Scoring System. The fuzzy inference that corresponds to the clinical interpretation of signals based on the FIGO guidelines enables to designate recordings indicating the fetal wellbeing. In the second step, the remained recordings are classified using Lagrangian Support Vector Machines (LSVM). The evaluation of the proposed procedure using data collected with computerized fetal surveillance system confirms its efficacy in predicting the fetal distress.
AB - Cardiotocography is a biophysical method of fetal state assessment based on analysis of fetal heart rate signal (FHR). The computerized fetal monitoring systems provide a quantitative evaluation of FHR signals, however the effective methods for fetal outcome prediction are still needed. The paper proposes a two-step analysis of fetal heart rate recordings that allows for prediction of the fetal distress. The first step consists in classification of FHR signals with Weighted Fuzzy Scoring System. The fuzzy inference that corresponds to the clinical interpretation of signals based on the FIGO guidelines enables to designate recordings indicating the fetal wellbeing. In the second step, the remained recordings are classified using Lagrangian Support Vector Machines (LSVM). The evaluation of the proposed procedure using data collected with computerized fetal surveillance system confirms its efficacy in predicting the fetal distress.
KW - Fetal heart rate monitoring
KW - fuzzy systems
KW - signal classification
KW - support vector machines
UR - https://www.scopus.com/pages/publications/84858724651
U2 - 10.1007/978-3-642-28490-8_45
DO - 10.1007/978-3-642-28490-8_45
M3 - Conference contribution
AN - SCOPUS:84858724651
SN - 9783642284892
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 431
EP - 438
BT - Intelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings
T2 - 4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012
Y2 - 19 March 2012 through 21 March 2012
ER -