Collection
Internet of Medical Things (IoMT)
The origins of the Internet of Things in the fields of pervasive computing and ubiquitous computing viewed the autonomous communication of many devices as beneficial for interceding for users. Many areas of life would benefit from this intercession, but perhaps none more than medicine. The Precision Medicine Initiative from 2015 called out a need for individualized medical interventions that consider the characteristics of a person. Wearable sensors and interconnected devices provide an exciting opportunity to realize this at a personal scale. These kinds of devices as applied to healthcare is given the term “Internet of Medical Things (IoMT). However, our current IoMT infrastructure is lacking in the ability to communicate these characteristics and sensor data easily, pervasively, and safely in a manner that can be interpreted at the point of care facility. Accuracy and context of these data are critical in the decision-making process. Data ownership represents a similar issue, especially when the underlying characteristic can be considered protected health information. These issues have so far prevented a fully realized IoMT.
The Topical Collection has two main focuses. First, we welcome submissions that demonstrate novel scholarly research on connected wearable medical things. In this focus, we hope to identify new mechanisms to engage users, medical professionals, and the data infrastructure for enabling precision medicine through connected devices. Second, we welcome submissions that describe internet architectures and data exchange mechanisms that can enable these interventions to take place at scale. We expect this topical collection to provide contributions in multiple fields, but with an emphasis on bringing the IoMT closer to technological readiness.
Keywords:
Internet of Things, Human Computer Interaction, Precision Medicine, Distributed Systems, Wearable Computing
Editors
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Alexander Nelson
Prof Alexander Nelson, University of Arkansas, USA He earned a PhD in Computer Engineering from the University of Maryland, Baltimore County (UMBC). He contributed to the NIST Smart Cities and Communities framework series and has experience with research and development of connected devices for medicine. He collaborates closely with medical researchers, practitioners, and end users. He leads the ÆSIR (Applied Embedded Systems and IoT Research) Laboratory at the University of Arkansas.
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David Andrews
Prof David Andrews, University of Arkansas, USA He has over 30 years experience performing research and development in parallel and distributed real time systems. He worked at the Electronics Laboratory, Advanced Technology Laboratories, and the Underwater Systems Division at General Electric. He has held faculty positions at the University of Kansas and University of Arkansas. He received his PhD in Computer Science from Syracuse University, and BSEE and MSEE degrees from the University of Missouri-Columbia.
