An Analysis of FIR Filter Algorithms in Fetal Heart Rate Monitoring

Abstract

Diagnosis of heart rate of both mother and child is very necessary during pregnancy and hence fetal electrocardiogram (FECG) extraction is very crucial to be analyzed. The signal should contain precise information that can help doctors during pregnancy and labor. When trying to record Fetal ECG (FECG) one of the main problems is the interference from the maternal ECG (MECG) and external noises. The major consideration in biomedical data processing is to separate the required signal from noise caused by different reasons. Different filters and algorithms are used to get the desired component from the unwanted signals caused by interferences. Finite Impulse Response (FIR) filtering is one of the widely used operations in DSP. In the existing methodology, FIR filter is designed using array multiplier with higher delay and power dissipation concerns. The proposed methodology enforces a programmable digital finite impulse response (FIR) filter for high performance applications. The filtering process is done with the help of ECG signal information collected from MIT-BIH Arrhythmia Database. This project involves a complete model of the FECG extraction with the implementation of effective algorithms and filters and finally gives the heart rate of the FECG signal.