eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2026-03-20 19 1 694 718 10.13005/bpj/3386 70310 article Nguetsop Hermann Beaumont 1 Jean Mbihi 2 Gamom Ngounou 3 Moffo Lonla 4 Department of Computer Science Engineering Automation and Bioengeneering of HTTTC, University of Douala, Douala, Cameroon. Department of Health Sciences of HTTTC, University of Ebolowa, South, Cameroon This article describes the design of a device for analyzing and extracting parameters from pregnant women. This is achieved primarily by isolating fetal and maternal cardiac signals. The objective is to contribute to addressing the problem of rising intrauterine fetal mortality in the most isolated regions of developing countries: the case of Cameroon. Our case study focuses on a problem observed in low-income countries: the difficulty of accessing regular medical care for many pregnant women due to the unavailability of doctors and the lack of equipment in health centers. The design and use of less expensive remote fetal monitoring devices is therefore an essential solution. Our technique is based on the preprocessing of signals modulating the maternal ECG (ECG-M) and the fetal ECG (ECG-F), acquired using the DCM (cycle-ratio modulation) method with ultrasound Doppler probes. The composite signal is then separated by a SOBI (second-order blind identification) algorithm. Filtering performed using a filter derived from the Pan-Thomkins structure for detecting ECG R peaks and a heart rate calculation algorithm. The simulation performed using Matlab-Simulink software (2020b). To verify the real-time operation of our cardiac system, we used the FECGSYNDB database (fetal electrocardiogram synthetic database) on an ESP32 board for simulation evaluation of the fetal ECG extraction algorithms, and 30 volunteer patients for practical validation of our device. Finally, the resulting device used for real-time recording in numerous hospitalized patients, and the results were compared to those of existing wearable devices reviewed. Our results demonstrate relatively good performance considering its cost of USD 66. With a separability index of 0.0011 and a 20-hour battery life with a 2500 mAh battery, it detects 97% of the R peaks of physiological cardiac signals. This performance, while satisfactory for us, is superior to that reported by several authors in the literature: accuracy (99.01%), sensitivity (97.45%), specificity (97.09%), precision (98.11%), and F1 score (96.89%). Regarding fetal arrhythmia, our model presents the following results: sensitivity (FECG) = 98.96%; fetal precision (P+FECG) = 99.01%; F1 score (FECG) = 99.51 ± 0.14%. It informs the pregnant woman at any time whether her fetal heart rate is normal, requires monitoring, or is abnormal, facilitating prompt medical intervention. https://biomedpharmajournal.org/vol19no1/design-a-low-cost-device-for-preventing-fetaldistress-by-analysis-of-heart-rate/ Blind source separation Battement per Minutes Cardiac Arrhythmias Duty Cycle Modulation Doppler ultrasonic ESP 32 WROOM FECGSYNDB Fetal ECG Fœtal Heart Rate Internet of Things Maternal ECG Second Oder Blind Identification