Special Issues
Table of Content

Integrity and Multimedia Data Management in Healthcare Applications using IoT

Submission Deadline: 01 June 2021 (closed) View: 147

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.

Summary

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.


Keywords

RECOMMENDED TOPICS:
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


  • Open Access

    ARTICLE

    Artifacts Reduction Using Multi-Scale Feature Attention Network in Compressed Medical Images

    Seonjae Kim, Dongsan Jun
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3267-3279, 2022, DOI:10.32604/cmc.2022.020651
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract Medical image compression is one of the essential technologies to facilitate real-time medical data transmission in remote healthcare applications. In general, image compression can introduce undesired coding artifacts, such as blocking artifacts and ringing effects. In this paper, we proposed a Multi-Scale Feature Attention Network (MSFAN) with two essential parts, which are multi-scale feature extraction layers and feature attention layers to efficiently remove coding artifacts of compressed medical images. Multi-scale feature extraction layers have four Feature Extraction (FE) blocks. Each FE block consists of five convolution layers and one CA block for weighted skip connection. More >

  • Open Access

    ARTICLE

    An IoT Based Secure Patient Health Monitoring System

    Kusum Yadav, Ali Alharbi, Anurag Jain, Rabie A. Ramadan
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3637-3652, 2022, DOI:10.32604/cmc.2022.020614
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract Internet of things (IoT) field has emerged due to the rapid growth of artificial intelligence and communication technologies. The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients, proper administration of patient information, and healthcare management. However, the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintained while transferring over an insecure network or storing at the administrator end. In this manuscript, the authors have developed a secure IoT healthcare monitoring system… More >

  • Open Access

    ARTICLE

    AMBO: All Members-Based Optimizer for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi, Sajjad Amiri Doumari, Mohammad Dehghani, Zeinab Montazeri, Pavel Trojovský, Gaurav Dhiman
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2905-2921, 2022, DOI:10.32604/cmc.2022.019867
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in… More >

  • Open Access

    ARTICLE

    Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

    Jinsu Kim, Sungwook Ryu, Namje Park
    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, More >

  • Open Access

    ARTICLE

    Medical Image Compression Method Using Lightweight Multi-Layer Perceptron for Mobile Healthcare Applications

    Taesik Lee, Dongsan Jun, Sang-hyo Park, Byung-Gyu Kim, Jungil Yun, Kugjin Yun, Won-Sik Cheong
    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 2013-2029, 2022, DOI:10.32604/cmc.2022.019604
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    Abstract As video compression is one of the core technologies required to enable seamless medical data streaming in mobile healthcare applications, there is a need to develop powerful media codecs that can achieve minimum bitrates while maintaining high perceptual quality. Versatile Video Coding (VVC) is the latest video coding standard that can provide powerful coding performance with a similar visual quality compared to the previously developed method that is High Efficiency Video Coding (HEVC). In order to achieve this improved coding performance, VVC adopted various advanced coding tools, such as flexible Multi-type Tree (MTT) block structure… More >

  • Open Access

    ARTICLE

    Efficient MAC Protocols for Brain Computer Interface Applications

    Shams Al Ajrawi, Ramesh Rao, Mahasweta Sarkar
    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 589-605, 2021, DOI:10.32604/cmc.2021.016930
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    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… More >

  • Open Access

    ARTICLE

    Virtual Reality-Based Random Dot Kinematogram

    Jun Ma, Hyo-Jung Kim, Ji-Soo Kim, Eek-Sung Lee, Min Hong
    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4205-4213, 2021, DOI:10.32604/cmc.2021.018080
    (This article belongs to the Special Issue: Integrity and Multimedia Data Management in Healthcare Applications using IoT)
    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… More >

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