A Wireless High-Sensitivity Fetal Heart Sound Monitoring System
In certain cases, the condition of the fetus can be revealed by the fetal heart sound. However, when the sound is detected, it is mixed with noise from the external environment as well as internal disturbances. Our exclusive sensor, which was constructed of copper with an enclosed cavity, was design...
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Online Access: | https://www.mdpi.com/1424-8220/21/1/193 |
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doaj-89f1421b6a5e4646ba6e79a80a7adfe62020-12-31T00:02:20ZengMDPI AGSensors1424-82202021-12-012119319310.3390/s21010193A Wireless High-Sensitivity Fetal Heart Sound Monitoring SystemJianjun Wei0Zhenyuan Wang1Xinpeng Xing2School of Telecommunications Engineering, Xidian University, Xi’an 710072, ChinaSchool of Telecommunications Engineering, Xidian University, Xi’an 710072, ChinaShenzhen International Graduate School, Tsinghua University, Shenzhen 518055, ChinaIn certain cases, the condition of the fetus can be revealed by the fetal heart sound. However, when the sound is detected, it is mixed with noise from the external environment as well as internal disturbances. Our exclusive sensor, which was constructed of copper with an enclosed cavity, was designed to prevent external noise. In the sensor, a polyvinylidene fluoride (PVDF) piezoelectric film, with a frequency range covering that of the fetal heart sound, was adopted to convert the sound into an electrical signal. The adaptive support vector regression (SVR) algorithm was proposed to reduce internal disturbance. The weighted-index average algorithm with deviation correction was proposed to calculate the fetal heart rate. The fetal heart sound data were weighted automatically in the window and the weight was modified with an exponent between windows. The experiments show that the adaptive SVR algorithm was superior to empirical mode decomposition (EMD), the self-adaptive least square method (LSM), and wavelet transform. The weighted-index average algorithm weakens fetal heart rate jumps and the results are consistent with reality.https://www.mdpi.com/1424-8220/21/1/193fetal heart soundfetal heart ratePVDF piezoelectric filmautomatic weightweighted-index average |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jianjun Wei Zhenyuan Wang Xinpeng Xing |
spellingShingle |
Jianjun Wei Zhenyuan Wang Xinpeng Xing A Wireless High-Sensitivity Fetal Heart Sound Monitoring System Sensors fetal heart sound fetal heart rate PVDF piezoelectric film automatic weight weighted-index average |
author_facet |
Jianjun Wei Zhenyuan Wang Xinpeng Xing |
author_sort |
Jianjun Wei |
title |
A Wireless High-Sensitivity Fetal Heart Sound Monitoring System |
title_short |
A Wireless High-Sensitivity Fetal Heart Sound Monitoring System |
title_full |
A Wireless High-Sensitivity Fetal Heart Sound Monitoring System |
title_fullStr |
A Wireless High-Sensitivity Fetal Heart Sound Monitoring System |
title_full_unstemmed |
A Wireless High-Sensitivity Fetal Heart Sound Monitoring System |
title_sort |
wireless high-sensitivity fetal heart sound monitoring system |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-12-01 |
description |
In certain cases, the condition of the fetus can be revealed by the fetal heart sound. However, when the sound is detected, it is mixed with noise from the external environment as well as internal disturbances. Our exclusive sensor, which was constructed of copper with an enclosed cavity, was designed to prevent external noise. In the sensor, a polyvinylidene fluoride (PVDF) piezoelectric film, with a frequency range covering that of the fetal heart sound, was adopted to convert the sound into an electrical signal. The adaptive support vector regression (SVR) algorithm was proposed to reduce internal disturbance. The weighted-index average algorithm with deviation correction was proposed to calculate the fetal heart rate. The fetal heart sound data were weighted automatically in the window and the weight was modified with an exponent between windows. The experiments show that the adaptive SVR algorithm was superior to empirical mode decomposition (EMD), the self-adaptive least square method (LSM), and wavelet transform. The weighted-index average algorithm weakens fetal heart rate jumps and the results are consistent with reality. |
topic |
fetal heart sound fetal heart rate PVDF piezoelectric film automatic weight weighted-index average |
url |
https://www.mdpi.com/1424-8220/21/1/193 |
work_keys_str_mv |
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