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

Gulzar Ahmad, Saima; Iqbal, Tassawar; Javaid, Anam; Ullah Munir, Ehsan; Kirn, Nasira; Jan, Sana Ullah; Ramzan, Naeem

Authors

Saima Gulzar Ahmad

Tassawar Iqbal

Anam Javaid

Ehsan Ullah Munir

Nasira Kirn

Naeem Ramzan



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.

Journal Article Type Article
Acceptance Date May 23, 2022
Online Publication Date Jun 9, 2022
Publication Date Jun 9, 2022
Deposit Date Jun 17, 2022
Publicly Available Date Jun 20, 2022
Journal Sensors
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 22
Issue 12
Article Number 4362
DOI https://doi.org/10.3390/s22124362
Keywords healthcare; maternal; infant; artificial intelligence; machine learning; wearable sensors; wireless sensors
Public URL http://researchrepository.napier.ac.uk/Output/2879785

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open access article distributed under the Creative Commons Attribution License (CC-BY 4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.





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