The Approach to Sensing the True Fetal Heart Rate for CTG Monitoring: An Evaluation of Effectiveness of Deep Learning with Doppler Ultrasound Signals

被引:0
|
作者
Hirono, Yuta [1 ,2 ]
Sato, Ikumi [1 ,3 ]
Kai, Chiharu [1 ,4 ]
Yoshida, Akifumi [4 ]
Kodama, Naoki [4 ]
Uchida, Fumikage [2 ]
Kasai, Satoshi [4 ]
机构
[1] Niigata Univ Hlth & Welf, Grad Sch, Major Hlth & Welf, Niigata 9503198, Japan
[2] TOITU Co Ltd, Tokyo 1500021, Japan
[3] Niigata Univ Hlth & Welf, Fac Nursing, Dept Nursing, Niigata 9503198, Japan
[4] Niigata Univ Hlth & Welf, Fac Med Technol, Dept Radiol Technol, Niigata 9503198, Japan
来源
BIOENGINEERING-BASEL | 2024年 / 11卷 / 07期
关键词
Doppler ultrasound; maternal heart rate; fetal heart rate; AI;
D O I
10.3390/bioengineering11070658
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Cardiotocography (CTG) is widely used to assess fetal well-being. CTG is typically obtained using ultrasound and autocorrelation methods, which extract periodicity from the signal to calculate the heart rate. However, during labor, maternal vessel pulsations can be measured, resulting in the output of the maternal heart rate (MHR). Since the autocorrelation output is displayed as fetal heart rate (FHR), there is a risk that obstetricians may mistakenly evaluate the fetal condition based on MHR, potentially overlooking the necessity for medical intervention. This study proposes a method that utilizes Doppler ultrasound (DUS) signals and artificial intelligence (AI) to determine whether the heart rate obtained by autocorrelation is of fetal origin. We developed a system to simultaneously record DUS signals and CTG and obtained data from 425 cases. The midwife annotated the DUS signals by auditory differentiation, providing data for AI, which included 30,160 data points from the fetal heart and 2160 data points from the maternal vessel. Comparing the classification accuracy of the AI model and a simple mathematical method, the AI model achieved the best performance, with an area under the curve (AUC) of 0.98. Integrating this system into fetal monitoring could provide a new indicator for evaluating CTG quality.
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页数:11
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