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  1. Home
  2. Academic Research Output
  3. Journal Article
  4. IoT-Based Smart Health System for Ambulatory Maternal and Fetal Monitoring
 
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IoT-Based Smart Health System for Ambulatory Maternal and Fetal Monitoring

Date Issued
2021
Author(s)
Lobo Marques, Joao Alexandre 
Faculty of Business and Law 
Han, Tao
Wu, Wanqing
Madeiro, Joao Paulo do Vale
Neto, Aloísio Vieira Lira
Gravina, Raffaele
Fortino, Giancarlo
de Albuquerque, Victor Hugo C.
DOI
10.1109/JIOT.2020.3037759
Abstract
The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.
Subjects

Biomedical monitoring...

Fetal heart rate

Monitoring

Internet of Things

Cloud computing

Artificial intelligen...

convolutional neural ...

feature extraction

Feature extraction

fetal monitoring

health analytics

maternal monitoring

Medical diagnostic im...

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