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FetalCare: A Home Telemonitoring System for Wearable Fetal-ECG and EHG Acquisition During Pregnancy

Authors :
Li, Hao
Liu, Liheng
Zhao, Jun
Li, Zhuo
Liu, Ming
Li, Tingting
Zhang, Jiarong
Hong, Zhiliang
Xu, Jiawei
Source :
IEEE Sensors Journal; 2024, Vol. 24 Issue: 9 p15175-15186, 12p
Publication Year :
2024

Abstract

A wearable and remote fetal monitoring system, FetalCare, is specifically developed for home use. It comprises a stretchable on-skin patch and a wearable pod to capture, process, and transmit fetal signals. Data received by a Bluetooth dongle are processed by edge computing to remove diverse noises and interferences and then displayed by a fetal monitoring platform integrated with cloud services. The highly integrated system can simultaneously measure up to 6-channel electrohysterography (EHG) and 3-channel fetal electrocardiogram (FECG) signals from the abdomen using just a 4-channel data acquisition (DAQ) chip. Electrically conductive composites (ECCs) and silicone implement the stretchable on-skin electrode. The compact wearable pod achieves low input noise of <inline-formula> <tex-math notation="LaTeX">$0.191 \mu $ </tex-math></inline-formula>Vrms (250 Hz bandwidth) while consuming 56 mW and can operate continuously for up to 36 h. We use edge computing to process fetal signals, which utilize fast independent component analysis (FastICA) and empirical mode decomposition (EMD) to obtain high-quality FECG and EHG signals. The fetal monitoring platform based on InfluxDB and Grafana supports real-time, remote monitoring with low latency and historical data retrieval. Finally, we used the contraction consistency index (CCI) to assess the EHG and used metrics such as sensitivity (Se), positive predictive accuracy (PPV), accuracy (ACC), and their harmonic mean (F1) to assess the FECG. The CCI for EHG signals measured by the FetalCare system is 0.8, which implies a highly consistent result with the clinical CTG equipment. The average Se, PPV, ACC, and F1 scores for FQRS complexes extraction are 97.97%, 98.62%, 96.58%, and 98.25%, respectively.

Details

Language :
English
ISSN :
1530437X and 15581748
Volume :
24
Issue :
9
Database :
Supplemental Index
Journal :
IEEE Sensors Journal
Publication Type :
Periodical
Accession number :
ejs66238638
Full Text :
https://doi.org/10.1109/JSEN.2024.3374332