EXTRACTION OF FETAL ECG FROM ABDOMINAL SIGNAL

D. V. Prasad and R. Swarnalatha

Department of Electronics & Instrumentation Engineering, BITS, PILANI, Dubai, U.A.E.

Keywords: fECG, mECG, TECG, Adaptive filtering.

Abstract: Fetal ECG monitoring is essential for identification of fetal distress. The assessment of the QRS waveform

of fetal ECG is good analysis tool. Extraction of fetal ECG from abdominal signals is difficult. This paper

presents a method for extracting fetal ECG (FECG) from composite abdominal signal. This method is

applied to composite abdominal signal containing maternal ECG and fetal ECG. Adaptive filtering

techniques along with denoising techniques were used to extract fECG. This method leads to enhancement

of fetal ECG by cancelling maternal ECG. The results were validated using real signals. The thoracic signal

is purely that of mother (mECG) while the abdominal signal contains both mothers and fetus ECG signals

(mECG + fECG). The results clearly show the effectiveness of the method in extracting fECG.

1 INTRODUCTION

The fetal electrocardiogram (FECG) is the electrical

activity of the fetal heart and first demonstration was

carried out in 1906 by Cremer (Jenkins, 1986). Fetal

electrocardiogram fECG provides clinically

significant information about the physiological state

of a fetus. Anoxia is known to alter the balance

between the electrical polarization and repolarization

of the heart. Similarly arrhythmias show the

maturity of fetal cardiac activity (Symonds EM,

Sahota T, and Chang A, 2001). Many experiments

were performed using invasive techniques to record

fECG. Non invasive techniques appeared in the

seventies. These methods use recorded signals from

maternal abdominal wall. These signals contained

not only maternal electrocardiogram (mECG) but

also fetal ECG (fECG) and other signals. The

maternal signal level is much higher than fetal ECG

and hence has to be suppressed from the composite

signal. With advent of technology and analysis tools

many methods of maternal ECG suppression were

developed.

Adaptive filtering was used with thoracic

signals as the reference inputs, combined to cancel

the maternal ECG in the abdominal signals (Widrow

et al, 1975). A weighted addition of four or more

abdominal signals was calculated to suppress the

maternal ECG (Bergveld P and Meijer JH, 1981).

Singular value decomposition was used successfully

to separate maternal ECG and fetal ECG (Callaerts

D, De Moor B, Vanderwalle J and Sansen W, 1990).

Blind source separation algorithms have also been

applied to extract fECG (Zarcoso and Nandi A K,

2001).

Fetal ECG contains information about the health

status of the fetus. It gives an early diagnosis of any

cardiac defects before delivery (Mazzo J R, 1994).

Non invasive techniques of fetal monitoring are

Doppler ultrasound, fetal electrocardiography and

fetal magneto cardiography. Among these methods

the most commonly used is Doppler ultrasound.

However this method produces an averaged heart

rate and therefore cannot give beat to beat

variability. This method cannot provide

electrophysiological information such as

arrhythmias. Fetal electrocardiogram offers the

advantage of monitoring beat to beat variability.

(Fukushima T, Flores CA, Hon EH, Davidson EC,

1985). There are many technical problems with non

invasive extraction of fECG. The fECG signal is

corrupted by different sources of interferences such

as maternal EMG, 50 Hz power line interference and

base line wander. The low amplitude of the signals,

the different types of noise and overlapping

frequencies of mother and fetal ECG make the

extraction of fECG a difficult task (Godddard B A,

1966). Projective filtering techniques were also used

to extract fetal ECG (Kotas M, 2007)

The fetal heart rate variations during pregnancy

and labour have been used as an indirect indicator of

fetal distress. Observation over longer periods may

245

Prasad D. and Swarnalatha R. (2009).

EXTRACTION OF FETAL ECG FROM ABDOMINAL SIGNAL.

In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, pages 245-248

DOI: 10.5220/0001510502450248

 SciTePress

yield more information about the status of the fetus.

The detection of fetal QRS complex on surface

records is very difficult task which is mainly due to

overlapping of mothers ECG. The mECG and fECG

are partly uncorrelated. Also the mECG signal is

very much stronger than the fECG signal embedded

in it. The noise in which fECG is embedded is also

stronger depending on the gestation age.

In this paper an improved method of extracting

the P QRS T waves of the fetal ECG from composite

abdominal signal is proposed. The proposed method

uses cancellation of mothers ECG and denoising

methods to improve the extracted signal quality.

Real abdominal signals were used to test the

algorithm.

2 METHOD

The block diagram of the proposed algorithm is

shown in Fig 1. The proposed method detects fetal

QRS wave by preprocessing and denoising of

abdominal ECG (AECG) and subsequent

cancellation of maternal ECG in the abdominal

ECG. The thoracic signal (TECG) which is mECG is

used to cancel mECG and the fetal ECG detector

extracts the fECG. This method uses multistage

adaptive filtering.

2.1 Preprocessing

The preprocessing consists of the following steps

(Prasad DV, Swarnalatha R, 2007).

(a) Read the abdominal ECG

(b) Separate the high resolution components

and low resolution components

(d) Derive the noise component

(e) Separate the noise from the original signal

(f) Reconstruct the signal back

(g) Repeat the construction iteratively.

The high resolution components are the components

which are well defined in the abdominal signal.

These are the maternal QRS wave having large

amplitude and the fetal ECG whose amplitudes are

much smaller than maternal ECG. The low

resolution components are the components which do

not directly contribute to the fetal ECG or maternal

ECG.

2.2 Material

The testing of the algorithm was done by using data

from SISTA/DAISY and Physionet. The data from

SISTA/DAISY has abdominal data of 5 channels

and thoracic data of 3 channels. Physionet has 2

channels of thoracic signals and 4 channels of

abdominal signals. However for verification of the

algorithm only one channel of abdominal signals

was used. The gestation period varies from 22 to 40

weeks. DAISY data and Physionet data have

different sampling frequencies. The algorithm has

been tested with both the data.

2.3 Fetal QRS Detection

The aim of the algorithm is to enhance the fetal ECG

by suppressing the other components of the signal.

The enhanced signal contains mostly fetal ECG and

EMG noise. The proposed method detects fetal QRS

waves by canceling the maternal ECG.

Fetal ECG

detection was done by improving signal to noise

ratio (SNR) of fetal QRS complex to the other

components of the signal using a nonlinear operator

defined by equation 1. This reduces the maternal P

and T waves. The operator is defined as follows.

Ψ = DS (DS-1) (1)

where DS is the preprocessed and denoised signal

obtained from the original abdominal ECG. Fig 2 (a)

shows the abdominal signal to be analyzed and the

maternal ECG recorded from thoracic region is

shown in Fig 3(a). Fetal ECG can be extracted by

direct application of blind source separation (BSS)

(De Lathauwer L, De Moor B, and Vanderwalle J,

2000). However such methods fail to give precise

extraction. In order to reduce the mothers ECG

effects on extraction, mECG was eliminated by

using two stage adaptive filtering. The reference

signal taken is shown in Fig 3(b) which is the

squared signal of the thoracic signal corresponding

to mECG Fig 3(a).The advantage of this method is

that the reference signal need not closely mimic the

signal to be cancelled. If such a reference signal

could be generated, than this method can be applied

where only the mothers ECG is available. The

adaptive filter used behaves as an exponential

averager (Laguna P, Jane R, Meste et al, 1992).

The output of the adaptive filter 1 is again adaptive

filtered with (TECG)

to obtain the signal shown in

Fig 3(d).To obtain better results the adaptive filter

design plays an important role. The selection of the

step size of the adaptive filter is very important as

the signal to be extracted is highly sensitive to the

BIOSIGNALS 2009 - International Conference on Bio-inspired Systems and Signal Processing

246

step size. The resultant signal depends on the value

for the constant of adaptation. The output 3(d) is

applied to fECG detector and extracted fECG and

mECG are shown in Fig 4(b) and 4(c). The signal

quality is high enough to recognize fetal QRS

complexes.

Figure 1: Block Diagram of the proposed algorithm.

Figure 2: (a)Original abdominal ECG (b) Preprocessed

signal (c) Square of preprocessed signal (d) signal

obtained after adding b and c.

3 RESULTS

The proposed algorithm was assessed by using real

composite signal comprising of mECG and fECG.

The noise is to due to mother’s electromyogram

activity. The performance of the method is seen

from the extracted waveforms centering on R wave

peak. The P and T waves can also be seen. Fig 4

gives the extracted fECG and mECG. Fig 6 shows

the power spectrum of the original signal and the

extracted fECG and mECG. The results show that

the P, R and T waves are clearly visible in the

extracted signals. Two cases have been studied. Case

1 has a sampling rate of 250 samples/sec and case 2

has a sampling rate of 1000 samples/sec. Fig 4a

shows the results for case 1 and Fig 5b shows the

results for case 2.

Figure 3: (a) Thoracic ECG (b) square of Thoracic ECG

filter 2.

Figure 4: (a) Original abdominal ECG of patient 1 (b)

Extracted fECG (c) Extracted mECG.

Figure 5: (a) Original abdominal ECG of patient 2 (b)

Extracted fECG.

AECG

(TECG)

TECG

Adaptive

Filter 1

Adaptive

Filter 2

Cancelling

mECG

fECG

detecto

Adaptive

Filter 1

Adaptive

Filter 2

mECG

Preprocessin

g &

Denoising

FECG

Ψ=DS (DS-1)

Denoised

signal (DS)

EXTRACTION OF FETAL ECG FROM ABDOMINAL SIGNAL

247

Figure 6: Power spectrum of (a) Original Abdominal ECG

(b) Extracted fECG (c) Extracted mECG.

4 CONCLUSIONS

Fetal ECG extraction with out disturbing the

morphology is a difficult task. The limitations of

conventional methods led to the design of this

extraction system which improves the estimate the

fetal ECG and maternal ECG. A two stage adaptive

filter system is shown to retrieve fetal ECG from

actual patients maternal ECG. It is not easy to see

how well the fECG extraction is

achieved by

looking at a large number of samples. Thus a frame

of 400 samples is taken for patient 1 and 2000

samples for patient 2, to illustrate the effectiveness

of the algorithm. In this frame there are both

overlapping and non overlapping between maternal

and the fetal components in the abdominal signal.

This is a significant challenge to the extraction

algorithm. The results show that the algorithm was

able to successfully extract the fECG signal. It can

be noted the visual quality of the extracted fECG is

much better. The advantage of this method is that

the reference signal need not closely mimic the

signal to be cancelled. The algorithm was able to

reveal complete fetal ECG such QRS complex, its

shape and duration. This also allows for beat to beat

detection of the fetal R waves. This feature allows us

to investigate fetal heart rate fluctuations. This

feature of the algorithm can be used in early stages

of pregnancy. Consequently, it is possible to

understand the fetal heart rate fluctuations as a

function of gestational time. The algorithm was able

to overcome noise due to sources such as maternal

muscle activity, uterine contractions and external

electrical interference.

ACKNOWLEDGEMENTS

The authors would like to thank Prof. M.

Ramachandran, Director, BITS, Pilani-Dubai for his

constant encouragement and support. We would also

like to thank Physionet.org and SISTA/DAISY for

the fetal ECG data.

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