Internet of Medical Things (Iomt) in Clinical Instrumentation: Design, Integration, and Applications

Abstract

The foundation of medical IoT devices is the daily circumstances, technological advancements in the Internet of Things, artificial intelligence-based machine learning technology, and the demand for more advanced health care. Thus, IoMT activities revolve around gathering and processing patient data to support better health management and control, e.g. wearable devices to collect health data, send them to a cloud-based platform for communication, processing, an online interface for healthcare professionals to analyze and visualize the information. Recently, demand for a more advanced health care system, i.e. massive health data collection, advanced processing systems producing preventive alerts and offers for patients, have raised new research questions surrounding this technology. The motivation to better respond to these aspects lies in the complexity of the IoMT environments, which enables the presence of a huge number of devices, connections, and interactions, on a geographical scale that is often unknown or not controllable, e.g. by health care professionals, exposing to communication and processing that are often performed by unknown actors over unknown networks and geographically dispersed data storing, all in a context sensitive to human well-being .

Given the increasing number of personal health monitoring devices connected to IoMT infrastructure and adding the energy constraint, as some devices cannot be plugged continuously to a power supply, experts and researchers are facing emergent problems, involving hardware and software debugging, pollution of medical data with excessive alerts (alarms) and missing diagnoses alerts by important events. Strategies for conducting continuous data reception and synchronization, as well as real-time alert/failure checking and feedback provision, are elaborated. At last, open issues and future research direction on medical IoT operations are discussed.