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InECCE2019 pp 357-365 | Cite as

Review and Analysis of Risk Factor of Maternal Health in Remote Area Using the Internet of Things (IoT)

  • Marzia Ahmed
  • Mohammod Abul Kashem
  • Mostafijur Rahman
  • Sabira Khatun
Conference paper
  • 5 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 632)

Abstract

IoT is the greatest ingenious innovation in the modern era, which can exploit also in mission-critical like the healthcare industry. This paper demonstrates effective monitoring of pregnant women mostly in a rural area of a developing country, with the help of wearable sensing enabled technology, which also notifies the pregnant women and her family about the health conditions. There are many researchers have been researched to reduce the maternal and fetal mortality but the mortality rate is not reducing, where it should be in zero tolerance. This research intended to use machine learning algorithms for discovering the risk level on the basis of risk factors in pregnancy. In this research, an existing dataset (Pima-Indian-diabetes dataset) has been used for the analysis of risk factor and comparison of some machine learning algorithm shows that Logistic Model Tree (LMT) gives the highest accuracy in case of classification and prediction of the risk level. Regardless, few selected pregnant women’s data has been collected (through IoT enabled devices) and the same process also applied for this dataset also by using LMT. Comparison results show that the prediction of risks is the same for the existing and real dataset.

Keywords

Maternal risk factors Internet of things Wearable sensors 

Notes

Acknowledgements

Thanks to Dr. Shirin Shabnam for helping to prepare the categorization of risk parameter in a pregnancy-related medical dataset on the basis of intensity.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Marzia Ahmed
    • 1
    • 2
  • Mohammod Abul Kashem
    • 1
  • Mostafijur Rahman
    • 2
  • Sabira Khatun
    • 3
  1. 1.Department of Computer Science and EngineeringDhaka University of Science and TechnologyGazipur, DhakaBangladesh
  2. 2.Department of Software EngineeringDaffodil International UniversityDhakaBangladesh
  3. 3.Faculty of Electrical and Electronics EngineeringUniversity Malaysia PahangGambangMalaysia

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