Title :
Extricating non invasive fetal ECG by adaptive optimization technique
Author :
Subhashini, S. ; Jagannath, D.J. ; Immanuel Selvakumar, A.
Author_Institution :
Dept. of Electron. & Commun., Karunya Univ., Coimbatore, India
Abstract :
A new methodology to Extricating the Fetal ECG from Abdominal Electrocardiogram signal. Two types of signals are taken from the mother´s skin, one is Thoracic signal which is taken from the mother´s chest and it is known as Maternal signal (MECG). The other type of signal is taken from abdomen of the mother and it is known as Abdominal signal (AECG).The Abdominal ECG includes the Fetal ECG (FECG) and Transformation of Maternal ECG (MECG), that may be a non linear signal with noise. For extricating process of a Fetal ECG, the non linear Maternal ECG is subtracted from the Abdominal ECG by using Adaptive Neuro Fuzzy Inference system (ANFIS). The valid synthetic ECG signal is obtained by using non-invasive method of external monitoring. The Abdominal ECG and Maternal ECG signal are preprocessed and with Adaptive Neural Network to get Fetal ECG and then it is trained with swarm intelligence used to increase the accuracy of fetal signal. By using this method Fetal ECG quality will increase.
Keywords :
bioelectric potentials; electrocardiography; inference mechanisms; medical signal processing; neural nets; noise; optimisation; skin; swarm intelligence; abdominal ECG signal processing; adaptive neural network; adaptive neurofuzzy inference system; adaptive optimization technique; electrocardiography; mother chest; mother skin; noise; noninvasive fetal ECG extricating process; nonlinear maternal ECG signal processing; swarm intelligence; thoracic signal processing; Electrocardiography; Load modeling; MATLAB; Mathematical model; Optimization; Surface treatment; Training; AECG; ANFIS; FECG; MECG;
Conference_Titel :
Electronics and Communication Systems (ICECS), 2014 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-2321-2
DOI :
10.1109/ECS.2014.6892659