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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Main Authors: Jianjun Wei, Zhenyuan Wang, Xinpeng Xing
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/1/193
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spelling 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 AT jianjunwei awirelesshighsensitivityfetalheartsoundmonitoringsystem
AT zhenyuanwang awirelesshighsensitivityfetalheartsoundmonitoringsystem
AT xinpengxing awirelesshighsensitivityfetalheartsoundmonitoringsystem
AT jianjunwei wirelesshighsensitivityfetalheartsoundmonitoringsystem
AT zhenyuanwang wirelesshighsensitivityfetalheartsoundmonitoringsystem
AT xinpengxing wirelesshighsensitivityfetalheartsoundmonitoringsystem
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