Key result
The combination of NLMS and Pan Tompkins algorithms extracted fetal heart rate from abdominal ECG signals with 100% R-peak detection accuracy and a 0.1% error rate compared to direct fetal ECG.
Why the study?
Extracting fetal electrocardiogram signals to analyze fetal activity remains a major challenge while the fetus is inside the uterus.
Does the NLMS algorithm combined with Pan Tompkins algorithm accurately extract fetal heart rate from abdominal ECG signals compared to direct fetal ECG?
Does the NLMS algorithm combined with Pan Tompkins algorithm accurately extract fetal heart rate from abdominal ECG signals compared to direct fetal ECG?
The NLMS and Pan Tompkins algorithms can extract fetal heart rate from non-invasive abdominal ECG signals with high accuracy.
Supports non-invasive FHR extraction from abdominal ECG; leaves open prospective clinical validation before adoption.
This project develops a fetal heart rate (FHR) extraction application to analyze the fetus activity in the mother uterus. Several methods are available that can be used to detect FHR such as using the fetal electrocardiogram (FECG) that generated by fetus’ heart. Extracting FECG signals is considered a major challenge while the fetus is inside the mother uterus. Normalized Least Mean Square (NLMS) algorithm is one of adaptive filters that is chosen as adaptive filter to get FECG. Pan Tompkins algorithm is used for tracking R-peaks of heartbeat pulses of FECG signal. After detecting the RR interval a formula is used to calculate the bpm (heartbeat per minute) of FECG. Abdominal and direct FECG (ADFECG) database will be used to evaluate the implemented techniques as it has reference signal. At the end of research, calculated FHR is varied from 125.4 bpm to 130.3 bpm. When comparison is done between abdominal ECG (AECG) and direct FECG (DFECG), the error of FHR is 0.1%. The accuracy of R-peaks extraction is 100% where all R-peaks are detected by implemented techniques. MATLAB is used for signal simulations. This system will have ability to interpret the non-invasive FECG (NIFECG) database and compute its FHR.
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Ricky et al. (2021) studied Fetal heart rate monitoring (n=6). NLMS and Pan Tompkins algorithms vs. Direct Fetal Electrocardiogram (DFECG) was evaluated on R-peak extraction accuracy. The combination of NLMS and Pan Tompkins algorithms extracted fetal heart rate from abdominal ECG signals with 100% R-peak detection accuracy and a 0.1% error rate compared to direct fetal ECG.
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