Special Issue "Integrity and Multimedia Data Management in Healthcare Applications using IoT"

Submission Deadline: 01 June 2021 (closed)
Guest Editors
Dr. Gaurav Dhiman, Government Bikram College of Commerce, India.
Dr. Ashutosh Sharma, Southern Federal University, Russia.
Prof. Mukesh Soni, S. R. Patel Engineering College, India.
Prof. Victor Chang, Teesside University, UK.
Prof. Atulya Nagar, Liverpool Hope University, UK.


In the present era of research and technology, several emerging concepts like Wireless Sensor Networks (WSN), Body Wireless Sensor Networks (BWSN), Internet of Things (IoT), Cloud, Fog, Edge, SDN and Big Data Analytics can support IoT for design and development of intelligent systems in diverse domains, e.g., Transportation, Education, Enterprise and Industry etc. Besides these systems, the role of IoT can be seen in different types of healthcare applications such as tele-healthcare system for chronic diseases, medications intake management support, homecare etc.

Emerging technology (Cloud, Fog, Edge, SDN, Big Data, IOT, Deep Learning\Confidence) computing provides scalability, flexibility, agility, and ubiquity in terms of data acquisition, data storage, data management and communications. The combination of multimedia and cloud for healthcare enhances many technical issues for many media-rich applications such as video streaming, serious games, rehabilitation exercise, health sports, e-healthcare and so forth. Some of the issues are: seamless access of medical media content by heterogeneous devices (e.g., mobile phone, laptop, and IPTV), resources capacity demands (e.g., bandwidth, memory, storage, and processors), medical multimedia’s quality of service/Experience/Context (m-QoS/m-QoE/m-QoC) requirements, and dynamic resource allocation for processing of media content.

Topics to be discussed in this special issue include (but are not limited to) the following:
• Multimedia and Service Networking in E-healthcare
• Biomedical Image Processing
• Security and Privacy in Medical Data
• Artificial Intelligence and Machine Learning in Biomedical
• Neural Networks and Fuzzy Logic in Biomedical
• Biologically Inspired Computing
• IoT/Cyber Physical Systems for E-healthcare
• VANET/MANET/WSN Applications for E-healthcare
• Emerging Technology-based multimedia processing for healthcare
• Emerging applications for managing medical media data
• Real-time analytics on streaming medical media data
• Mobile multimedia emerging technologies for health care
• Emerging Technologies based health monitoring
• M-QoE/M-QoS/M-QoC variations in health-emerging technologies applications
• Emerging technologies -based remote display Protocol for health care
• Media-cloud based resource allocation approaches
• Emerging technologies based model for speech-enabling healthcare
• Emerging media cloud protocols, surveys, applications and new research approaches

Published Papers
  • Efficient MAC Protocols for Brain Computer Interface Applications
  • Abstract Brain computer interface (BCI) systems permit individuals with motor disorders to utilize their thoughts as a mean to control external devices. BCI is a promising interdisciplinary field that gained the attention of many researchers. Yet, the development of BCI systems is facing several challenges, such as network lifetime. The Medium Access Control (MAC) Protocol is the bottle- neck of network reliability. There are many MAC protocols that can be utilized for dependable transmission in BCI applications by altering their control parameters. However, modifying these parameters is another source of concern due to the scarcity in knowledge about the effect of… More
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  • Virtual Reality-Based Random Dot Kinematogram
  • Abstract This research implements a random dot kinematogram (RDK) using virtual reality (VR) and analyzes the results based on normal subjects. Visual motion perception is one of visual functions localized to a specific cortical area, the human motion perception area (human analogue for the middle temporal/middle superior temporal area) located in the parieto–occipito–temporal junction of the human brain. The RDK measures visual motion perception capabilities. The stimuli in conventional RDK methods are presented using a monitor screen, so these devices require a spacious dark room for installation and use. Recently, VR technology has been implemented in different medical domains. The test… More
  •   Views:622       Downloads:496        Download PDF