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Machine Learning-Based Monitoring Devices for Pregnant Women

Machine Learning-Based Monitoring Devices for Pregnant Women

Selvanayaki Palanisamy (Dr. Mahalingam College of Engineering and Technology, India), Muthanantha Murugavel A. S (Dr. Mahalingam College of Engineering and Technology, India), Sathiyamurthi Pattusamy (Bannari Amman Institute of Technology, India), and S. Deepa (Dr. Mahalingam College of Engineering and Technology, India)
Copyright: © 2023 |Pages: 13
DOI: 10.4018/979-8-3693-1718-1.ch010
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Abstract

The improvements in IoT technology in the medical field over the last few years have offered a lot of benefits for pregnant women. The internet of things, together with cloud computing and wearable technologies, are all working together to improve maternal healthcare. The amount of time that is required to be contributed by medical professionals and registered nurses has been cut down. There are three distinct modes of operation for the internet of things technology that is implemented for the purpose of monitoring pregnant women. The initial layer is referred to as the perception layer, and some of its responsibilities include the authentication of users, the assumption of cognitive control, and the collection of physiological data. The second layer is referred to as the network layer, and it is the one that is accountable for receiving these data and putting them to use in a variety of different ways. The application layer, which is the third layer, is in charge of health management tasks including the diagnosis of diseases and the monitoring of the foetal well-being.
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Introduction

The improvements in IoT technology that have been made in the medical field over the course of the last several years have offered a great lot of benefit, particularly to pregnant women. The platform for the Internet of Things (IoT), together with cloud computing and wearable technologies are all working together to improve maternal healthcare. It is now much simpler for expectant mothers to have frequent consultations with their physicians because to improvements in technology, which has the effect of improving the overall quality of the medical treatment that they get. The amount of time that is required to be contributed by medical professionals and registered nurses has been cut down. There are three distinct modes of operation for the Internet of Things technology that is implemented for the purpose of monitoring pregnant women. The initial layer is referred to as the perception layer, and some of its responsibilities include the authentication of users, the assumption of cognitive control, and the collection of physiological data. The second layer is referred to as the network layer, and it is the one that is accountable for receiving these data and putting them to use in a variety of different ways. Some examples of these uses include uploading them to the cloud, determining whether or not there are any auxiliary devices present, and routing the data. The application layer, which is the third layer, is in charge of health management tasks including the diagnosis of diseases and the monitoring of the foetal well-being. This layer is also in charge of the communication between the mother and the foetus. In order to complete the computation, the information that was acquired via the use of the questionnaire was utilised. The fact that the majority of pregnant women shared the same viewpoint suggests that they have confidence in the increasing dependence that the medical industry is placing on the Internet of Things (IoT) and wearable technologies.

Maternal Monitoring to Reduce Pregnancy Complications

The introduction of sensors, wearable technology, and other devices has made it possible to improve prenatal care, neonatal healthcare, patient communication, and real-time monitoring of a wide range of disorders. Machine learning techniques are being used to this field of medicine. In the instance of an ectopic pregnancy, for example, an early diagnosis is attainable through the utilisation of high-resolution, portable ultrasonography as well as complete blood count (CBC) blood test equipment, amongst other diagnostic instruments. In addition, an early diagnosis is attainable through the utilisation of other diagnostic instruments. During miscarriage screenings, having dilation and curettage (D&C) performed at the proper time and monitoring haemoglobin (Hb) levels can help lessen the probability of difficulties occurring. Monitoring one's blood pressure may be accomplished using any one of the many digital devices that are now on the market (BP). The early detection of congenital abnormalities, monitoring of hypertension, diabetes, mother and foetal care, detection of postpartum depression, and other similar pregnancy complications can all contribute to a reduction in the number of stillbirths and deaths of unborn foetuses. Pregnancy care, monitoring of hypertension, diabetes, and care for both the mother and the foetus can also contribute to this reduction. Both cardiotocography (CTG), which is also known as tracing of the foetal heart, and anomaly scans are able to assist in the early diagnosis of congenital abnormalities in a foetus. Hence, wearable sensors can increase communication between patients and healthcare providers, which eventually leads in improved outcomes for pregnant women. Wearable sensors have the potential to revolutionise the healthcare industry. It is possible that incubators that are enabled by technology, that are properly equipped, and that include intelligent nasogastric (NG) tubes for nasogastric feed preterm babies might assist enhance in-time reaction in the field of new born healthcare.

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