Journal of Healthcare Engineering

Internet of Medical Things for Healthcare Engineering


Publishing date
01 Jan 2021
Status
Closed
Submission deadline
28 Aug 2020

Lead Editor

1Hangzhou Dianzi University, Hangzhou, China

2Massachusetts Institute of Technology (MIT), Cambridge, USA

3Nanjing University of Aeronautics and Astronautics, Nanjing, China

This issue is now closed for submissions.

Internet of Medical Things for Healthcare Engineering

This issue is now closed for submissions.

Description

As the world population is rapidly ageing, the need for convenient biomedical diagnosis and proactive health management is growing tremendously. Novel biomedical diagnostic devices, circuits, and microsystems for healthcare can lead to new strategies for health management.

Those devices, circuits, and microsystems involve biosensors, bioelectronics, integrated circuits for biomedical applications, lab-on-a-chip systems for biophysical and biochemical parameter detection and monitoring, etc. Due to the multidisciplinary nature of healthcare-related technologies, it has attracted experts from every major field including electronics, chemistry, physics, biology, materials science, computer science, bioengineering, and informatics, etc.

This Special Issue is dedicated to the state-of-the-art Internet of Medical Things in healthcare engineering-related topics and emphasizes the bioelectronics, biophysics, biochemistry, and microsystems related topics for healthcare engineering. Through a collection of original research as well as review articles, this Special Issue aims to promote the awareness of this enabling technology in the community of healthcare engineering and encourage research collaboration across fields to address critical and urgent healthcare concerns.

Potential topics include but are not limited to the following:

  • Internet of Medical Things: implementation and applications
  • Biomedical sensors and microsystems for healthcare engineering
  • Microfluidics and lab-on-a-chip applications
  • Point of care diagnostic instrumentation for healthcare engineering
  • Machine learning/deep learning for healthcare engineering
  • Biomedical informatics for healthcare engineering
  • Healthcare system architecture
  • Rehabilitation systems and applications

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