IMAGE & SIGNAL PROCESSING Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation Techniques P. Sutha 1 & VE. Jayanthi 2 Received: 6 September 2017 /Accepted: 15 November 2017 /Published online: 8 December 2017 # Springer Science+Business Media, LLC, part of Springer Nature 2017 Abstract Birth defect-related demise is mainly due to congenital heart defects. In the earlier stage of pregnancy, fetus problem can be identified by finding information about the fetus to avoid stillbirths. The gold standard used to monitor the health status of the fetus is by Cardiotachography(CTG), cannot be used for long durations and continuous monitoring. There is a need for contin- uous and long duration monitoring of fetal ECG signals to study the progressive health status of the fetus using portable devices. The non-invasive method of electrocardiogram recording is one of the best method used to diagnose fetal cardiac problem rather than the invasive methods.The monitoring of the fECG requires development of a miniaturized hardware and a efficient signal processing algorithms to extract the fECG embedded in the mother ECG. The paper discusses a prototype hardware developed to monitor and record the raw mother ECG signal containing the fECG and a signal processing algorithm to extract the fetal Electro Cardiogram signal. We have proposed two methods of signal processing, first is based on the Least Mean Square (LMS) Adaptive Noise Cancellation technique and the other method is based on the Wavelet Transformation technique. A prototype hardware was designed and developed to acquire the raw ECG signal containing the mother and fetal ECG and the signal processing techniques were used to eliminate the noises and extract the fetal ECG and the fetal Heart Rate Variability was studied. Both the methods were evaluated with the signal acquired from a fetal ECG simulator, from the Physionet database and that acquired from the subject. Both the methods are evaluated by finding heart rate and its variability, amplitude spectrum and mean value of extracted fetal ECG. Also the accuracy, sensitivity and positive predictive value are also determined for fetal QRS detection technique. In this paper adaptive filtering technique uses Sign-sign LMS algorithm and wavelet techniques with Daubechies wavelet, employed along with de noising techniques for the extraction of fetal Electrocardiogram.Both the methods are having good sensitivity and accuracy. In adaptive method the sensitivity is 96.83, accuracy 89.87, wavelet sensitivity is 95.97 and accuracy is 88.5. Additionally, time domain parameters from the plot of heart rate variability of mother and fetus are analyzed. Keywords Fetal ECG . Cardiotachography . Adaptive Noise Cancellation . Wavelet Transform and Heart Rate Variability Introduction The main cause of fetal mortality during pregnancy is due to cardiovascular disorder. The cardiovascular disorder can be obtained by monitoring the cardiac electric signals.Recording and monitoring of fetal ECG of good diag- nostic quality is required to study the health conditions of the fetus. Fetal still birth reduction is possible by detecting the electrical activity of fetus heart. The fetal demise and perinatal morbidity can be reduced by analyzing fetal cardiac signal recording and [1] heart rate. Magnetic resonance, ultrasounds and digital processing of cardiac signals are the methods used to find complex relationships among different processes. Particularly. Fetal magneto cardiography, fetal electrocardiog- raphy and Doppler ultrasound techniques are non invasive This article is part of the Topical Collection on Image & Signal Processing * P. Sutha sutharvs@gmail.com VE. Jayanthi jayanthi.ramu@gmail.com 1 Department of Biomedical Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India 2 Department of Electronics and Communication, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India Journal of Medical Systems (2018) 42: 21 https://doi.org/10.1007/s10916-017-0868-3