Measurement and Extraction of Non-invasive Fetal ECG from Maternal ECG Signal

Project Title

Measurement and Extraction of Non-invasive Fetal ECG from Maternal ECG Signal

Project Area of Specialization Biomedical EngineeringProject Summary

Heart defects are among the most common birth defects and the leading cause of birth defect-related deaths. Every year, about one out of 125 babies are born with some form of congenital heart defects. The defect may be so slight that the baby appears healthy for many years after birth, or so severe that its life is in immediate danger. Congenital heart defects originate in the early stages of pregnancy when the heart is forming and they can affect any of the parts or functions of the heart. Like for adults, it should be possible to visualize the electrical activity of a fetal heart.

The abdominal ECG signal contains fetal ECG signal, the maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary.

Currently, there are two ways to obtain a fetal ECG. One is the invasive scalp electrode method, which can directly measure the pure fetal ECG signal. However, it can only detect fetal ECG signals during birth, and because it is invasive it may cause harm to the mother and the fetus. Another method is the non-invasive abdominal electrode method. Signals from the abdominal body surface are collected by placing an electrode patch in the abdomen of the mother, which allows for long-term monitoring during pregnancy. However, the signals from the maternal abdominal surface are very complex, containing not only maternal ECG and weak fetal ECG signals, but also the mother’s respiratory noise, frequency interference, and other signals. In particular, the magnitude of the maternal ECG detected in the abdomen is about 2–10 times that of the fetal ECG, which makes the extraction of the fetal ECG difficult. Therefore, it is necessary to develop a non-invasive method that can extract the fetal ECG effectively.

For this purpose, we designed an ECG fabricated circuit using all the compliances and standards. Using the circuit we acquired ECG data from patients (mothers) and separated the fetal ECG signal from maternal ECG and noise using different algorithms. 

At present, fetal ECG extraction algorithms mainly include adaptive filtering, wavelet analysis, matched filtering, blind source separation (BSS), independent component analysis (ICA), neural network, and singular value decomposition (SVD).

Challenges of Fetal Signal Extraction

As the above graph depicts, the frequency range of the fetal ECG component covers all the maternal biopotential signals and has a very low amplitude, so it is very critical for us to extract it.

Project Objectives

1. Design and implementation/Fabrication of ECG circuit: ECG circuit designed according to the compliance and standards 
2. Collecting ECG signal from mother: ECG signal collected from mother using three-channel ECG hardware and BIOPAC
3. Ensuring patient safety: Shielding isolators are used so that current from electrodes should be kept at a safe level
4. Acquiring/Acquisition ECG signal in a PC: Data acquisition is done using DAQ card and Labview
5. Pre-processing of ECG Signal: The raw signal is preprocessed and noise is removed using a Bandpass filter
6. Separating FECG from maternal ECG: fetal ECG is separated using different types of algorithms

Project Implementation Method Methodology:

• Collection and study of literature for ECG circuitry and separation methods
• Study the different designs of ECG circuit
• An ECG device will be designed and fabricated according to compliances with standards.
• Signal acquisition from 5 pregnant women of 2nd and 3rd trimesters will be conducted.
• Stratified random sampling will be done to select the subjects.
• Women with multiple pregnancies or with any known diseases (cardiovascular, renal or thyroid) will not be included as a subject of this study.
• The fabricated ECG device and BIOPAC Student Lab device are selected for data collection.

In each hospital or clinic following steps will be executed:

• The Subject will be laid on a bed to avoid undesirable distortion in the signal recording.
• ECG electrodes will be placed on the abdomen.
• Data will be recorded firstly using the designed ECG machine and then the BIOPAC device will be used.
• Preprocessing of the signal acquired
• Fetal ECG separation using the selected algorithm

Benefits of the Project

During pregnancy, monitoring the fetus’ heart condition in order to test their well-being and diagnose possible diseases is of paramount importance. An early diagnosis before delivery using noninvasive techniques increases the effectiveness of the appropriate treatment. Fetal electrocardiogram (FECG) shows the muscular function and electrical activity of the fetal heart. It represents the characteristics such as dynamic behaviors, waveform and heart rate of the fetus. These characteristics help to determine fetal development, the existence of fetal distress, fetal life, intrauterine hypoxia, fetal maturity or congenital heart disease. So these above characteristics can be used for the conduction of appropriate treatment. Currently, fetal electrocardiography (FECG) seems to offer the most promising method to detect fetal hypoxia. Fetal hypoxia is a pathological state that occurs when the fetus is deprived of an adequate supply of oxygen. It can be caused by a number of reasons such as umbilical cord prolapses, cord occlusion or cord thrombosis, placental infarction and others. The non-invasive fetal ECG extraction technique can theoretically be performed at almost any point in the pregnancy. 

Detection of fetal disease in time can allow us to cure the congenital heart disease before further complications. 

Technical Details of Final Deliverable Hardware Design

The product of our project is an ECG hardware that is able to collect ECG data. The ECG signal than obtained will contain maternal ECG. fetal ECG and noise. 

The ECG signal is collected by hardware comprising of:

• Instrumentation Amplifier
• Bandpass Filter
• Analog to Digital Converter (ADC)
• Digital Optocoupler (Isolator)
• Microcontroller to memory card
• LCD Display

For shielding and isolation:

• Metal Sheet (aluminum base)
• Temperature Sensor
• Circuit Breaker

The ECG hardware circuit is encased in an acrylic box.

Software Implementation

• Data Acquisition is done using DAQ Card and analyzed using Labview
• The ECG signal is preprocessed using different filters.
• MATLAB is used to process the raw signal and remove noise.
• Selected Algorithm is used to separate fetal ECG component from signal

Final Deliverable of the Project HW/SW integrated systemCore Industry MedicalOther Industries Health Core Technology OthersOther TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	75000
AD620	Equipment	5	325	1625
Capacitor	Equipment	55	35	1925
resistor pack	Equipment	1	250	250
circuit breaker	Equipment	3	680	2040
fuse	Equipment	5	50	250
battery charger	Equipment	1	3200	3200
rechargeable cells	Equipment	8	700	5600
rechargeable batteries	Equipment	4	590	2360
shipping	Miscellaneous	1	250	250
ECG Socket Adapters	Equipment	3	600	1800
cell holder	Equipment	3	100	300
aux socket	Equipment	6	40	240
aux port	Equipment	6	40	240
breadboard	Equipment	4	180	720
PCB board	Equipment	5	300	1500
LM 35	Equipment	5	150	750
IN5817	Equipment	8	10	80
connecting wires	Equipment	25	20	500
potentiometer	Equipment	5	20	100
LM 358	Equipment	15	20	300
LF33	Equipment	10	50	500
LM741	Equipment	10	30	300
coloured printing	Miscellaneous	40	20	800
photostates	Miscellaneous	40	5	200
stationery	Miscellaneous	1	200	200
seperating sheets	Miscellaneous	13	20	260
travels uber	Miscellaneous	1	5390	5390
travels careem	Miscellaneous	1	2400	2400
electrodes	Equipment	5	1000	5000
leads	Equipment	6	1850	11100
acrylic box	Equipment	1	3000	3000
soldering iron	Equipment	1	950	950
pcb fabrication	Equipment	2	750	1500
cell charger	Equipment	1	2220	2220
electrode gel	Equipment	5	500	2500
glue gun	Equipment	1	1000	1000
glue gun sticks	Miscellaneous	10	50	500
aluminion base	Equipment	1	3000	3000
wire cutter	Equipment	2	1500	3000
Digital multimeter	Equipment	1	850	850
extension wire	Equipment	2	1350	2700
casing cost	Equipment	2	1800	3600