REVIEW ARTICLE
Internet of Medical Things – The Future of Healthcare
Pranay Wal1, *, Ankita Wal1, Neha Verma1, Rohini Karunakakaran2, 3, 4, Anupriya Kapoor5
Article Information
Identifiers and Pagination:
Year: 2022Volume: 15
E-location ID: e187494452212150
Publisher ID: e187494452212150
DOI: 10.2174/18749445-v15-e221215-2022-142
Article History:
Received Date: 28/8/2022Revision Received Date: 27/9/2022
Acceptance Date: 20/10/2022
Electronic publication date: 30/12/2022
Collection year: 2022
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background:
The Internet of Medical Things (IoMT) is now being connected to medical equipment to make patients more comfortable, offer better and more affordable health care options, and make it easier for people to get good care in the comfort of their own homes.
Objective:
The primary purpose of this study is to highlight the architecture and use of IoMT (Internet of Medical Things) technology in the healthcare system.
Methods:
Several sources were used to acquire the material, including review articles published in various journals that had keywords such as, Internet of Medical Things, Wireless Fidelity, Remote Healthcare Monitoring (RHM), Point-of-care testing (POCT), and Sensors.
Results:
IoMT has succeeded in lowering both the cost of digital healthcare systems and the amount of energy they use. Sensors are used to measure a wide range of things, from physiological to emotional responses. They can be used to predict illness before it happens.
Conclusion:
The term “Internet of Medical Things” refers to the broad adoption of healthcare solutions that may be provided in the home. Making such systems intelligent and efficient for timely prediction of important illnesses has the potential to save millions of lives while decreasing the burden on conventional healthcare institutions, such as hospitals. patients and physicians may now access real-time data due to advancements in IoM.