Call for Papers: Special Issue on “Advanced Internet of Things in a Personalized Healthcare System: Validation, Analysis and Utilization”

Call for Papers: Special Issue on “Advanced Internet of Things in a Personalized Healthcare System: Validation, Analysis and Utilization” 194 121 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

Download Call for Papers (PDF)
Submission Deadline Extended to November 30, 2017
Due to the exponential growth of wearable devices and mobile apps, healthcare as a field is being transformed by Internet of Things (IoT)-enabled technology. The traditional hubs of healthcare, such as hospitals and clinics, are being transformed into personalized healthcare systems–especially the mobile environment. However, most research in IoT-enabled healthcare has focused on domain-specific studies on designated sensors, algorithms and applications. There is still a paucity of research on a methodological level that explores and delivers high-level innovative and comprehensive informatics methods in the field. Innovative informatics methodologies in IoT-enabled healthcare will benefit the establishment and enhance the efficiency of practical, interoperable IoT systems for care delivery and research, as well as adequate data and knowledge standards for self-empowerment and sound clinical decision-making. The goal of this special issue, Advanced Internet of Things in a Personalized Healthcare System: Validation, Analysis and Utilization, is to bring together researchers and practitioners from both academia and industry into a single forum, to explore state-of-the-art research and applications in innovative technology for IoT-enabled personalized healthcare systems, including improvement of quality of life, clinical diagnosis, mental health, diet/exercise, and chronic disease self-management. Accepted papers will present efficient scientific and engineering solutions, address the needs and challenges for integration with new technologies, and provide a vision for future research and development. The special issue is especially focused on four major aspects of IoT-enabled healthcare: (1) Artificial Intelligence patterns or data mining algorithms for effectively and efficiently analyzing IoT-based personalized healthcare and clinical data. (2) Personalized knowledge models or systems to assist clinicians in decision-making for diagnosis and medication selection. (3) Interoperable and interactive IoT systems or applications to support heterogeneous devices in accessing, sharing, visualizing and exploring long-term individual behavior information.
Topics to be covered include, but are not limited to:

  • Personalized preventive medication in IoT-enabled personalized healthcare systems
  • Clinical decision support systems
  • Clinical translation and healthcare innovation in IoT-enabled healthcare
  • Clinical data storage and communication
  • Virtual reality, mixed and augmented reality
  • Mobile sensing and interaction techniques
  • Behavior change and analysis models in IoT-enabled personalized healthcare systems
  • Data mining and exploration of health data
  • Healthcare monitoring
  • Knowledge acquisition, discovery, modeling and management for IoT-enabled personal health
  • Ontologies, knowledge technologies, semantic web systems
  • Technology and models for behavioral intervention development
  • Evidenced-based approaches in behavioral health
  • IoT technology for social and emotional support
  • Emerging eHealth IoT application
  • IoT technology for medication management and adherence
  • Life-logging devices and technologies

Important Dates

  • Submission deadline EXTENDED: November 30, 2017

Papers should be submitted through: Choose the paper type: Special Issue: Advanced Internet of Things
For detailed submission information, please refer to “Information for Authors” on this website.

Guest Editors

  • Dr Po Yang, Liverpool John Moores University, UK,
  • Dr Julija Voicehovsak, Riga Stradins University, Latvia,
  • Prof Li Da Xu, Old Dominion University Norfolk, US,
  • Dr Baoquan Liu, Huawei UK Research Centre, UK,
  • Dr Srini Tridandapani, Emory University School of Medicine, US,

Download Call for Papers (PDF)