A signal quality assessment method for fetal QRS complexes detection
Objective: Non-invasive fetal ECG (NI-FECG) provides a non-invasive method to monitor the health of the fetus. However, the NI-FECG is easily interfered by noise, which makes the signal quality decline, leading to the fetal heart rate (FHR) monitoring becoming a challenging task. Methods: In th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2023-02-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023344?viewType=HTML |
| _version_ | 1797870669023674368 |
|---|---|
| author | Wei Zhong Li Mao Wei Du |
| author_facet | Wei Zhong Li Mao Wei Du |
| author_sort | Wei Zhong |
| collection | DOAJ |
| description | Objective:
Non-invasive fetal ECG (NI-FECG) provides a non-invasive method to monitor the health of the fetus. However, the NI-FECG is easily interfered by noise, which makes the signal quality decline, leading to the fetal heart rate (FHR) monitoring becoming a challenging task.
Methods:
In this work, an algorithm for dynamic evaluation of signal quality is proposed to improve the multi-channel FHR monitoring. The innovation of the method is to assess the signal quality in the process of multi-channel fetal QRS (FQRS) complexes detection. Specifically, the detected FQRS is used as quality unit. Each quality unit can be a true R peak (TR) or a false R peak (FR). It is the basic quality information in this work. The signal quality of each channel is estimated by estimating the correctness of the detection results. Further, the TRs of all channels can be fused to obtain more reliable fetal heart rate monitoring.
Main results:
Analysis results demonstrate that the proposed algorithm is capable of selecting the good quality signal for FQRS detection achieving 97.40% PPV, 98.33% SE and 97.86% F<sub>1</sub>.
Significance:
This work sheds light on the quality assessment of fetal monitoring signal. |
| first_indexed | 2024-04-10T00:30:57Z |
| format | Article |
| id | doaj.art-7ca0898ff7fa4b7181bb54409ca0616f |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-04-10T00:30:57Z |
| publishDate | 2023-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-7ca0898ff7fa4b7181bb54409ca0616f2023-03-15T01:11:51ZengAIMS PressMathematical Biosciences and Engineering1551-00182023-02-012057943795610.3934/mbe.2023344A signal quality assessment method for fetal QRS complexes detectionWei Zhong 0Li Mao1Wei Du2 Guangdong Police College, Guangzhou 510000, China Guangdong Police College, Guangzhou 510000, ChinaGuangdong Police College, Guangzhou 510000, ChinaObjective: Non-invasive fetal ECG (NI-FECG) provides a non-invasive method to monitor the health of the fetus. However, the NI-FECG is easily interfered by noise, which makes the signal quality decline, leading to the fetal heart rate (FHR) monitoring becoming a challenging task. Methods: In this work, an algorithm for dynamic evaluation of signal quality is proposed to improve the multi-channel FHR monitoring. The innovation of the method is to assess the signal quality in the process of multi-channel fetal QRS (FQRS) complexes detection. Specifically, the detected FQRS is used as quality unit. Each quality unit can be a true R peak (TR) or a false R peak (FR). It is the basic quality information in this work. The signal quality of each channel is estimated by estimating the correctness of the detection results. Further, the TRs of all channels can be fused to obtain more reliable fetal heart rate monitoring. Main results: Analysis results demonstrate that the proposed algorithm is capable of selecting the good quality signal for FQRS detection achieving 97.40% PPV, 98.33% SE and 97.86% F<sub>1</sub>. Significance: This work sheds light on the quality assessment of fetal monitoring signal.https://www.aimspress.com/article/doi/10.3934/mbe.2023344?viewType=HTMLsignal quality assessmentdata fusionconvolutional neural networkfetal monitoring |
| spellingShingle | Wei Zhong Li Mao Wei Du A signal quality assessment method for fetal QRS complexes detection Mathematical Biosciences and Engineering signal quality assessment data fusion convolutional neural network fetal monitoring |
| title | A signal quality assessment method for fetal QRS complexes detection |
| title_full | A signal quality assessment method for fetal QRS complexes detection |
| title_fullStr | A signal quality assessment method for fetal QRS complexes detection |
| title_full_unstemmed | A signal quality assessment method for fetal QRS complexes detection |
| title_short | A signal quality assessment method for fetal QRS complexes detection |
| title_sort | signal quality assessment method for fetal qrs complexes detection |
| topic | signal quality assessment data fusion convolutional neural network fetal monitoring |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2023344?viewType=HTML |
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