Abstract
Fetal heart sound is an important part of fetal monitoring and has attracted extensive research and attention from scholars at home and abroad in recent years. The fetal heart rate, extracted from the fetal heart sound signal, is one of the important indicators that reflect the health of the fetus in the womb. In this study, a maternal-fetal Holter monitor based on f ECG technology was used to collect maternal heart rate, fetal heart rate, and uterine contractions signals, isolate the fetal heart rate, and design an algorithm to extract the fetal heart rate baseline, acceleration, variation, wake-up cycle, and nonlinear parameters. Using statistical methods to analyze the average value and range of various characteristic parameters of fetal heart rate under continuous long-term monitoring, the results show that the baseline has a downward trend from 10 o'clock in the night to 4 o'clock in the morning and is the lowest around 2 o'clock in the morning. The area and acceleration time were significantly higher than those in the suspicious group. However, there was no significant difference in the number of acceleration values between the two groups; the proportion of small mutations in the normal group was lower than that of the suspicious group and the proportion of medium mutations was higher than that of the suspicious group. There is no statistically significant difference in maternal age, gestational age at childbirth, pregnancy comorbidities, and complication rates in the five-level interpretation system of ACOG (2009), RCOG (2007), SOGC (2007), and the United States (2007). The difference of pregnancy and parity in various images was statistically significant, P < 0.05. The second type of fetal heart rate monitoring images appeared in the highest among the diagnostic standards, and the difference in the second type of fetal heart rate monitoring images between the various diagnostic standards was statistically significant, P ≤ 0.001.
Highlights
In recent years, with the full liberalization of the national second-child policy and the gradual increase of elderly pregnant women, the work pressure of the hospital’s fetal heart rate monitoring department has increased [1]
The workload of the department doctors is overloaded, at the same time, the actual fetal heart rate monitoring needs of pregnant women outside working hours cannot be guaranteed. It is one of the important tasks of our information construction to establish a new model based on the cloud platform, with the “Internet + medical” model and the use of modern information technology for remote fetal heart rate monitoring and diagnosis
In terms of signal acquisition, there are mainly fetal heart sounds, fetal ECG, and ultrasound Doppler, etc., which can be divided into two major categories: active and passive according to the extraction method [12]
Summary
Related Work e methods of obtaining fetal heart rate mainly include the heart sound transducer method, fetal electrocardiogram method, and ultrasound Doppler method [5]. In terms of signal acquisition, there are mainly fetal heart sounds, fetal ECG, and ultrasound Doppler, etc., which can be divided into two major categories: active and passive according to the extraction method [12]. Researchers use smart sensors to obtain fetal heart sounds and build a wireless platform to realize real-time monitoring of fetal heart rate [17]. Ese methods need to be based on the relatively stable period of the fetal heart sound signal and are more sensitive to noise
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