Abstract: The goal of this paper is to create a fetal heart rate (FHR) extraction application that can be used to analyse fetus activities in the mother's uterus. FHR can be detected using a variety of ways, including the fetal electrocardiogram (FECG), which is generated by the fetus' heart. While the fetus is inside the mother's uterus, extracting FECG signals is considered a serious issue. The Normalized Least Mean Square (NLMS) method is one of the adaptive filters used to generate FECG. The Pan Tompkins algorithm is used to track R-peaks of FECG signal cardiac pulses. After detecting the RR interval, the bpm (beats per minute) of the FECG is calculated using a formula. Because it provides a reference signal, the abdominal and direct FECG (ADFECG) database will be used to evaluate the implemented approaches. The computed FHR ranged from 125.4 to 130.3 bpm at the conclusion of the study. The inaccuracy of FHR is 0.1 percent when comparing abdominal ECG (AECG) with direct FECG (DFECG). R-peaks extraction is 100 percent accurate, as all R-peaks are detected by the techniques used. For signal simulations, MATLAB is employed. This system will be able to analyse and compute the non-invasive FECG (NIFECG) database's FHR.
Keywords: NLMS Algorithm, Pan Tompkins Algorithm, Fetal Heart rate Extraction
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