Empowering Healthcare with IoMT: Evolution, Machine Learning Integration, Security, and Interoperability Challenges

Abstract

The Internet of Medical Things (IoMT) is the subset of the Internet of Things (IoT) that connects multiple medical devices, collect information/data from devices, and transmits and process data in real-time. IoMT is crucial for increasing electronic device accuracy, reliability, and productivity in the healthcare industry. IoMT has emerged as a next-generation bio-analytical tool that converges network-linked biomedical devices with relevant software applications for advancing human health. Adapting IoMT and associated technologies has fixed several problems using telemedicine, remote monitoring, sensors, robotics, etc. However, adopting IoMT technologies for a large population is challenging due to extensive data management, privacy, security, upgradation, scalability, etc. Although significant research has been carried out in this domain, identifying emerging trends and highlighting the technological advancement and challenges within IoMT is required for its success. Moreover, it will aid policymakers, scientists, healthcare practitioners, and researchers to measure the pertinence of IoMT in healthcare sectors more efficiently. This review discusses the evolution of IoMT, Machine Learning Integration, Security, and interoperability challenges of IoMT devices.