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Review
. 2022 Jun 9;22(12):4362.
doi: 10.3390/s22124362.

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Saima Gulzar Ahmad  1 , Tassawar Iqbal  1 , Anam Javaid  1 , Ehsan Ullah Munir  1 , Nasira Kirn  2 , Sana Ullah Jan  3 , Naeem Ramzan  3
Affiliations
Review

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review

Saima Gulzar Ahmad et al. Sensors (Basel). .

Abstract

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.

Keywords: artificial intelligence; healthcare; infant; machine learning; maternal; wearable sensors; wireless sensors.

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Conflict of interest statement

The authors declare that they have no conflict of interests.

Figures

Figure 1
Figure 1
General classification of healthcare services.
Figure 2
Figure 2
Architecture of healthcare systems.
Figure 3
Figure 3
Resource databases and article screening.
Figure 4
Figure 4
The structure of review.
Figure 5
Figure 5
General framework to predict patient’s health status using ML.
See this image and copyright information in PMC

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