Healthcare Information Technology for the Extreme and Remote Environments

Submission Deadline: 10 April 2019

IEEE Access invites manuscript submissions in the area of Healthcare Information Technology for the Extreme and Remote Environments.

IEEE Access invites manuscript submissions in the area of Healthcare Information Technology for Extreme and Remote Environments (HITERE). Extreme and rural medicine means having to treat health issues in the most challenging and sometimes inhospitable environments. It can occur in places completely removed from all of the standard procedures, comforts, protocols, and technologies, or during a crisis such as floods, tsunamis, and earthquakes that result in power failures and computer inoperability.. Knowing how to deal with the unique challenges encountered saves lives and communities. Hospitals and clinicians are being challenged to do more with less, yet there are limited attempts to develop solutions and applications that work in such challenging environments. This Special Section in IEEE Access aims to provide researchers and practitioners a platform to present innovative solutions based on emerging technologies like IoT, blockchain, electronic data interchange (EDI) and wireless sensors networks.  The main focus of this Special Section is to address the current research challenges by encouraging submissions related to the advanced Healthcare Information technologies.

The topics of interest include, but are not limited to:

  • Architecture, models, and design for trustworthiness for Extreme Environments
  • Network and system trustworthiness
  • Data trust, device trust and user trust
  • Identity management and identity trust
  • Modeling, Simulation and Protocols for Extreme Environments
  • Backup Technologies for Extreme Environments
  • Patient data delivery over unsecured channels
  • Medical images processing for Extreme Environments
  • Robustness against Environmental changes (cryosphere, land, oceans, and atmosphere)
  • Remote sensoring, and their associated technologies
  • Smart OTA Healthcare Apps for Extreme Environments
  • OTA Telepresence
  • Survivable Systems
  • Robotics and unmanned vehicles for Extreme Environments
  • IoT and Wearables for Extreme Environments
  • Navigation and Communication Technologies for Extreme Environments
  • Cloud Computing for Extreme Environments

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Sabah Mohammed, Lakehead University, Canada


Guest Editors:

  1. Tai-hoon Kim, Sungshin W. University, Korea
  2. Osvaldo Gervasi, University of Perugia, Italy
  3. Jinan Fiaidhi, Lakehead University, Canada


Relevant IEEE Access Special Sections:

 

  1. Heterogeneous Crowdsourced Data Analytics
  2. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems
  3. Healthcare Big Data


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: sabah.mohammed@lakeheadu.ca

 

Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications

Submission Deadline:  28 February 2019

IEEE Access invites manuscript submissions in the area of Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications.

Smart health is bringing vast promising possibilities on the way to pervasive health management. Smart health applications are strongly data-centric, and thus empowered by two key factors: information sensing and information learning. In a smart health system, it is crucial to effectively sense individuals’ health information, and afterwards intelligently learn from it high level health insights. These two factors are also closely coupled. For example, to enhance the signal quality, a sensing array requires advanced information learning techniques to fuse the information; and to enrich medical insights in mobile health monitoring, we need to combine ‘multimodal signal processing and machine learning techniques’ and ‘nonintrusive multimodality sensing methods’. In new smart health application exploration, challenges arise in both information sensing and learning, and especially their interaction areas.

This Special Section in IEEE Access invites academic and industrial experts to make their contributions to information sensing and learning in smart health systems. Studies are expected to build new bridges on many gaps between human subjects and their health insights, leveraging information sensing and learning technologies, such as physiological sensing, motion sensing, multimodal signal processing, health data representation techniques, machine learning, deep learning, data mining, computing platforms, and other related techniques. These technologies are required to build a whole data flow from humans to the health insights we pursue. This Special Section will allow readers to identify advancements, challenges and new opportunities in information sensing and learning for emerging smart health applications.

The topics of interest include, but are not limited to:

  • Physiological sensing: Heart ECG, Brain EEG, Muscle EMG, Optical PPG, Bioelectrical Impedance, etc.
  • Motion and activity sensing: movement, daily activities, behavior, etc.
  • Multichannel biomedical signal sensing and processing
  • Multimodal biomedical signal sensing and processing
  • Motion artifacts suppression techniques in wearable health monitoring
  • Data representation techniques for smart health data
  • Machine/deep learning from smart health data
  • Transfer learning applied to smart health applications with limited data
  • Time series analysis techniques using deep learning
  • Biomedical image and image processing
  • Platforms for computing intensive and/or low power smart health applications
  • Human-computer interaction for assisted living
  • Mobile health and precision medicine applications
  • Medical decision support systems
  • Wearable feedback systems for rehabilitation

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Qingxue Zhang, Harvard University, USA

Guest Editors:

 

  1. Vincenzo Piuri, University of Milan, Italy
  2. Edward A. Clancy, Worcester Polytechnic Institute, USA
  3. Dian Zhou, University of Texas at Dallas & Fudan University, USA & China
  4. Thomas Penzel, Charite University Hospital, Germany
  5. Walter Hu, University of Texas at Dallas & One-Chip Co., Ltd., USA & China
  6. Liang Peng, Huawei Silicon Valley Center, USA

Relevant IEEE Access Special Sections:

 

  1. Mobile Multimedia for Healthcare
  2. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions
  3. Human-Centered Smart Systems and Technologies


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: qingxue.zhg@gmail.com

Big Data Learning and Discovery

Submission Deadline: 01 October 2018

IEEE Access invites manuscript submissions in the area of Big Data Learning and Discovery.

We are now witnessing a dramatic growth of heterogeneous data, consisting of a complex set of cross-media content, such as text, images, videos, audio, graphics, spatio-temporal data, multivariate time series, and so on. The inception of informatics has offered very robust and hi-tech solutions for data and information analysis, collection, storage and organization, as well as product and service delivery to the customers. Recently, technological advancements, particularly in the form of Big Data, have resulted in the storage of enormous amounts of potentially valuable data in a wide variety of formats. This situation is creating new challenges for the development of effective algorithms and frameworks to meet the requirements of big data representation and analysis, knowledge understanding and discovery. Computer vision, for example, has a huge potential in many aspects for automated understanding of big data and has been used successfully to speed up and improve applications such as large-scale image segmentation, object detection, object tracking, event modeling, scene parsing, 3D reconstruction, image classification and retrieval and so on. Moreover, deep learning has revolutionized diverse key areas, such as speech recognition, object detection, image classification, and machine translation, with the data-driven representation learning. Therefore, it is now necessary to explore advanced theories and techniques for heterogeneous big data learning and discovery. This includes theory related to: data acquisition, feature representation, time series analysis, knowledge understanding, data-based modeling, dimension reduction, semantic modeling and the novel and promising big data analytic research direction, e.g. image/video captioning, affection computing, multimedia storytelling, Internet commerce, healthcare, earth system, communications, augmented/virtual reality and elsewhere.

This Special Section in IEEE Access invites contributions from diverse research fields, such as deep learning, feature extraction and fusion, big data indexing and retrieval, complex network analysis of time series (big data), brain-computer interface and EEG data analysis, healthcare big data analysis, ocean observing data mining, etc…

The topics of interest include, but are not limited to:

  • Architecture design for big data processing pipeline
  • Multi-modal and diverse big data collection
  • Complex network analysis of time series (big data)
  • Time series analysis and its applications
  • Deep learning methodology and its applications
  • Brain-computer interface and EEG data analysis
  • Benchmark for specific big data applications
  • Big data indexing and retrieval
  • Robust feature extraction for heterogeneous big data representation
  • Robust similarity measure and learning
  • Multi-modal and multi-view feature fusion and selection
  • Deep Learning for big data discovery
  • Multi-task/Transfer learning for big data understanding
  • Domain Adaptation for big data prediction
  • Optimal design of the underwater vehicles based on the big ocean observing data
  • Ocean observing data mining from underwater vehicles
  • Earth observing system data analysis
  • Real-world applications based on big data learning
  • Survey papers with regards to topics of big data learning and discovery
  • Big data learning for developing new prediction schemes and their applications to neuroscience, climatology, finances, infrastructure and cyberattacks etc.
  • Deep learning methodology for understanding of tipping points in large complex systems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Zhong-Ke Gao, Tianjin University, China

Guest Editors:

  1. An-An Liu, Tianjin University, China
  2. Yan-Hui Wang, Tianjin University, China
  3. Michael Small, The University of Western Australia, Australia
  4. Xiaojun Chang, Carnegie Mellon University, USA
  5. Jürgen Kurths, Potsdam Institute for Climate Impact Research, Humboldt University, Germany

 

Relevant IEEE Access Special Sections:

  1. Healthcare Big Data
  2. Real-Time Edge Analytics for Big Data in Internet of Things
  3. Advanced Signal Processing Methods in Medical Imaging

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: zhongkegao@tju.edu.cn

Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in Internet of Medical Things

Submission Deadline: 31 October 2018

IEEE Access invites manuscript submissions in the area of Trends, Perspectives and Prospects of Machine Learning Applied to Biomedical Systems in Internet of Medical Things.

The recent advancement in Internet of Medical Things (IoMT) paradigm aims to enrich our perception of healthcare reality, and incorporating new technologies for such applications. In the context of the IoMT, several medical devices connected to healthcare IT infrastructure can offer superior and more personalized health services. The combination of IoMT data, machine learning, streaming analytics distributed computing, and biomedical systems has become more powerful by enabling the storage and analysis of more data and many different types of data much faster. Machine learning plays a crucial role in the medical imaging field, comprising computer-aided diagnosis, registration and fusion, image segmentation, image-guided therapy, and image database retrieval for providing a better understanding of medical data applied to biomedical systems in IoMT. Moreover, the potential of big data in IoMT is a critical concern to constructing and running the kinds of big data analytics applications are obligatory for IoMT data. Thus it necessitates key focus from academia and industries.

Medical data is central to the IoMT paradigm: from acquiring critical medical sensor data or imaging data to analyzing, processing, and storing of health information, which adds new insights to our view of the world. Machine learning is essential to challenges related to the data source applied to biomedical devices using IoMT. Machine learning and data-driven methods represent a paradigm shift, and they are bound to have a transformative impact in the area of medical data and imaging processing. Many challenges arise as the IoMT permeates our world, especially for low-power resource-constrained devices for accumulating patient’s data, medical data integrity, privacy and security, and network lifetime and quality of service among others. The primary goal of this Special Section in IEEE Access is to provide an overview of the current state-of-the-art advances in machine learning of data source for understanding IoMT.

Topics of interest include, but are not limited to:

  • Computer-aided detection or diagnosis applied to biomedical systems in IoMT
  • New imaging modalities or methodologies for IoMT
  • Innovative machine-learning algorithms or applications in IoMT
  • Medical data security and privacy techniques for healthcare
  • Energy harvesting and big data analytics strategies in IoMT
  • Deep learning for optimizing medical big data in IoMT
  • Low-power resource-constrained medical devices for IoMT
  • Associative rule learning and reinforcement learning in IoMT
  • Smart medical systems based on cloud-assisted body area networks
  • Flexible and wearable sensors for prognosis and follow-up based on IoMT Paradigm
  • Healthcare Informatics to analyze patient health records, for enabling better clinical decision making and improved healthcare outcomes

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Kelvin KL Wong, Western Sydney University, Australia

Guest Editors:

  1. Dhanjoo N Ghista, University 2020 Foundation, USA
  2. Giancarlo Fortino, University of Calabria (Unical), Italy
  3. Wanqing Wu, Chinese Academy of Sciences, China

 

Relevant IEEE Access Special Sections:

  1. Mobile Multimedia for Healthcare
  2. Health Informatics for the Developing World
  3. Soft Computing Techniques for Image Analysis in the Medical Industry – Current trends, Challenges and Solutions

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: Kelvin.Wong@westernsydney.edu.au

Wearable and Implantable Devices and Systems

Submission Deadline: 15 June 2018

IEEE Access invites manuscript submissions in the area of Wearable and Implantable Devices and Systems.

Future electronics and sensing systems will be implantable and wearable. Large and ever-growing advances in developing and implementing such technologies have already exhibited the potential utility of this unique class of platforms to realize next-generation of sensing systems. Applications include wearable and implantable electronics, healthcare monitoring systems, soft robotics, as well as wireless implants. The field has started to see interesting developments in the areas of circuits and systems, involving studies related to low-power electronics, wireless sensor networks, wearable devices and sensors, real-time monitoring, connectivity of sensors and Internet of Things.

This Special Section in IEEE Access invites contributions from leading experts from both academia and industry. We believe that the novel approaches towards circuits and systems will allow readers to identify the requirements, challenges and future directions related to the burgeoning field of electronic circuits and systems for future wearable and implantable systems, from electronics to communications. Further, this Special Section will allow the biomedical researchers to identify new opportunities, which this exciting field may lead to.

The topics of interest include, but are not limited to:

  • Wearable and implantable sensing technologies
  • Readout circuits for wearable and implantable systems
  • Wireless power transfer/delivery
  • Low-Power circuits and sensors
  • Sensor Interfaces and A/D Converters
  • Implantable Electronics
  • Body sensor networks
  • wearable and mobile health monitoring
  • CMOS Sensors and Imaging
  • Antennas and sensors for wearables and wireless implants
  • Implantable and wearable diagnostic and therapeutic systems
  • Channel modelling for wearables and implants
  • Energy efficiency in wearable sensing systems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Qammer H. Abbasi, University of Glasgow, UK

Guest Editors:

  1. Yejun He, Shenzhen University, China
  2. Asimina Kiourti, The Ohio State University, USA
  3. Hadi Heidari, University of Glasgow, UK
  4. Majid E. Warkiani, University of Technology Sydney, Australia
  5. Akram Alomainy, Queen Mary University of London, UK

Relevant IEEE Access Special Sections:

  1. Ambient Intelligence Environments with Wireless Sensor Networks from the Point of View of Big Data and Smart & Sustainable Cities
  2. Mobile Multimedia for Healthcare
  3. Human-Centered Smart Systems and Technologies

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact:  qammer.abbasi@glasgow.ac.uk

Information Security Solutions for Telemedicine Applications

Submission Deadline: 31 March 2018

IEEE Access invites manuscript submissions in the area of Information Security Solutions for Telemedicine Applications.

In recent times, implementing telemedicine solutions has become a trend amongst the various research teams at an international level. Telemedicine refers to the use of modern information and communication technologies to meet the needs of citizens, patients, healthcare professionals, healthcare providers, as well as policy makers. Telemedicine applications are very promising and have great potential. They can play a very important role in service provision by improving access, equity and quality through connecting healthcare facilities and healthcare professionals and diminishing geographical and physical barriers. However, the transmission and access technologies of medical information raise critical issues that urgently need to be addressed, especially those related to security. Further, medical identity theft is a growing and dangerous crime. Stolen personal information can have negative financial impacts, and cuts to the very core of personal privacy. The medical identity theft is a growing crime, which already costs billions of dollars each year, and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of handheld devices to store, access, and transmit medical information is outpacing the privacy and security protections on those devices. Therefore, the authenticity of the information and related medical images is vital as they form the basis of inference for diagnostic purposes. In such applications, tamper proofing and guaranteed originality of medical data/information is achieved by embedding various watermark(s) which must be secure and robust against malicious attacks. Researchers are using watermarking and cryptography to disseminate the security of the medical data. Further, researchers are using watermarking techniques in the field of healthcare for addressing the health data management issues. It includes source and data authentication, efficient image archiving and retrieval, save bandwidth, and highlighting of diagnostically significant regions.

The objective of this Special Section in IEEE Access is to attract high-quality research articles and reviews that promote research and reflect the most recent advances in addressing and focusing the information security and privacy issues in telemedicine as well as other emerging areas. Authors are invited to submit original research and high-quality survey articles on topics including, but not limited to:

  • Watermarking, steganography, hidden data
  • Cryptographic algorithms/protocols
  • Electronic and Information security
  • Imaging
  • Health data management
  • Medical imaging modalities
  • Security and privacy of medical data
  • Systems and network security
  • Protection systems/ mechanism against patient identity theft
  • Bio‐signal Processing
  • display or secure transmission of images
  • Medical images processing
  • Biometrics
  • Image data compression
  • Patient data delivery over unsecured channels
  • Cyber Security in Telemedicine
  • Medical information security
  • Chaotic systems for privacy issues of medical data in healthcare centers

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Amit Kumar Singh, Jaypee University of Information Technology (JUIT), India

Guest Editors:

  1. S.K. Singh, Indian Institute of Technology (Banaras Hindu University), India
  2. Zhihan Lv, Chinese Academy of Science, China
  3. Charlie (Seungmin) Rho, Sungkyul University, South Korea
  4. Xiaojun Chang, Carnegie Mellon University, USA,
  5. William Puech, University of Montpellier, France

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: amit_245singh@yahoo.com

Health Informatics for the Developing World

Submission Deadline: 1 July 2017

IEEE Access invites manuscript submissions in the area of Health Informatics for the Developing World.

We live in a world with growing disparity between the lives of rich and poor. This difference is starkest when one compares the health facilities afforded to the rich living in developed countries and those available to the unprivileged in the developing world. Healthcare in the developing world is fraught with numerous problems—such as lack of health infrastructure and professionals and increasingly limited health coverage. In recent years, the field of health informatics has made great strides towards the improvement of public health systems in the developing world through augmentation of traditional health facilities using state-of-the-art Information and Communication Technologies (ICT). Through real-world deployment of these technologies, there is real hope that the health industry in the developing world will progress from its current, largely dysfunctional state to one that is more effective, personalized, and cost-efficient for all stakeholders. One of the most promising health informatics trends—buoyed by the rapid adoption of mobile phone technology throughout the world—is m-health (mobile-health). Such connected health informaticscan usher a new era of personalized health analytics, with the potential to transform healthcare in the developing world.

In conjunction with m-health many other important health informatics trends are also emerging. Exponentially growing heterogeneous data, with the help of big data analytics, has the potential to provide descriptive, predictive and prescriptive insights into future individual and population healthcare needs. Such systems could enhance the overall process of monitoring, diagnosis, and prognosis of chronic diseases. In particular, there is an immense potential for exploiting Artificial Intelligence (AI) and Machine Learning (ML) based health informatics in combination with cloud computing, and crowdsourcing for processing big health data and providing novel health services such as remote health diagnostics.

The aim of this Special Section in IEEE Access on “Health Informatics for the Developing World’’ is to present a snapshot of state-of-the-art technology in this important field. Our aim is to catalyze a convergence of growing research interest in health informatics from diverse fields such as ICT for development (ICTD); telemedicine; m-health; e-health; big data for development; biomedical engineering; human computer interaction (HCI), and to present a holistic integration of such approaches in this Special Section. Papers are solicited on novel concepts, models/architecture, and methodologies of health informatics, with a special focus on the viability of such approaches for the resource-constrained developing world. Topics of interest include, but are not limited, to the following:

Novel health informatics applications for the developing world:

  • Mobile health (m-health) solutions for the developing world
  • Low-cost health informatics solutions for the developing world (both hardware and software)
  • Point-of-care testing and diagnostic solutions for the developing world
  • Innovations in m-health for maternal and newborn health
  • Innovative telemedicine based solutions for the developing world
  • Personalized healthcare and wellbeing solutions for the developing world
  • Innovative health information dissemination solutions for the developing world
  • Energy efficient health informatics solutions for the developing world

Application of various health informatics techniques for the developing world:

  • Crowdsourcing-based health informatics solutions in the developing world
  • Artificial intelligence and machine learning based health informatics solutions in the developing world
  • Big data/ Multi-modal data analysis based health informatics solutions in the developing world
  • Natural language processing based health informatics solutions for the developing world
  • Personal health records and self-care systems for the developing world
  • Behavioral health informatics based interventions for the developing world
  • Signal (and image) processing based health informatics solutions in the developing world
  • Internet of things (IoT)-based health informatics solutions for the developing world

Health informatics issues:

  • Reports of practical health informatics deployments in the developing world
  • Accuracy and precision of clinical decision support systems
  • Privacy, security, and governance issues related to health data
  • Ease of usability of health informatics devices
  • Health informatics ethical issues

(Note: Research papers from authors of developed countries that could be relevant for the developing world, are also welcome, on any of the topics above)

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Junaid Qadir, Information Technology University (ITU), Punjab, Pakistan

Guest Editors:

  1. Muhammad Mujeeb-U-Rahman, Integrated Medical Sensors (USA) & Information Technology University (ITU), Punjab, Pakistan
  2. Mubashir Husain Rehmani, COMSATS Institute of Information Technology, Wah Cantt., Pakistan
  3. Al-Sakib Khan Pathan, Southeast University, Bangladesh
  4. Muhammad Ali Imran, University of Glasgow, United Kingdom
  5. Amir Hussain, University of Stirling, United Kingdom
  6. Rajib Rana, University of Southern Queensland, Australia
  7. Bin Luo, Anhui University, China

Related IEEE Access Special Sections:

  1. Healthcare Big Data
  2. Advances of Multisensory Services and Technologies for Healthcare in Smart Cities
  3. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: Bora M. Onat, Managing Editor, IEEE Access (Phone: (732) 562-6036, specialsections@ieee.org)

Body Area Networks

Submission Deadline: 10 April 2017

IEEE Access invites manuscript submissions to the Special Section on Body Area Networks. This Special Section will collect the best of “Bodynets 2016,” a conference that “aims to provide a world-leading and unique opportunity for bringing together researchers and practitioners from diverse disciplines to plan, analyze, design, build, deploy and experiment with/on Body Area Networks (BANs)” http://bodynets.org/2016/show/home.

The novel requirements of the healthcare sector, facing among other issues, the strong demographic changes associated with aging population put researchers in front of new and exciting challenges. Advanced electronic and networked systems allowing real time health monitoring can strongly reduce medication time and costs. Timely intervention of physicians on individuals living alone or in remote areas, is possible if an appropriate data transmission infrastructure is available. One part of this complex architecture is the Body Area Network (BAN), i.e. the part of the communication infrastructure that directly interacts with the human body. It should be able to support both the sensing part, connected to the relative data transmission from the person under monitoring to the physician, and the possibility to receive notifications and/or alerts once data is processed. Such technologies are already starting to enter into routine clinical practice. However, novel technologies such as nano-communication, intra/extra body communication, and others open the door for increasingly accurate future diagnostics.

Today, research activity is strongly driven by non-invasive exploration of living bodies. Wide-band reflectometry using adequate antennas system represents one possible way, but sometimes more accuracy can be achieved by the use of implantable sensors that can closely investigate the interested tissues and are able to communicate with the external systems. For some applications, this communication can be unidirectional for monitoring purposes, however the transceiver should be carefully designed to obtain the necessary data while generating as low as possible radiofrequency power within the tissue. The received signal is processed locally or sent to a remote medical center for further processing. The algorithms to extract the information are quite complex, and the low signal-to noise ratio makes the analysis even more challenging. A bi-directional communication on the other hand represents a considerable advancement, when the sensor nodes are remotely controlled based on the feedback of the received data. Nevertheless, the reduced transmitter-receiver distance and the presence of different high-loss tissues introduce strong reflections. Healthcare is very likely the main but not the only application for BANs. Wellness, social interactions, emergency and rescue, as well as military are other important application areas for BANs; all of them would profit from advances in BANs and in how BANs will be developed and deployed in real-working, even large scale, testbeds.

The Special Section in IEEE Access proposes to publish state-of-the-art results in related field to the BAN, as (i) Wearable Computing, (ii) Embedded Devices and Medical Applications, (iii) Communications and Networking, (iv) Systems and Applications, and (v) Antenna Applications and Propagation, that are the main topics of the Bodynets 2016 Conference. Research results in the fields of electronics, medicine, materials science, electromagnetics, signal processing, etc. and more importantly the significance of the inter-disciplinary aspects between them that provides a successful solution are expected to be brought together.

Other related hot topics in the current research community are Antennas and Propagation in Body Area Networks, Body Area NanoNETworks: Electromagnetic, Materials and Communications, Cloud-assisted Body Area Networks, Human Body Communications Millimeter-Wave Body Area Networks, Privacy, Security and Trust in Body Area Networks, Sensors and Algorithms for Human Motion Analysis and Classification, Ultra Wideband for Body Area Networking, just to mention some.

We invite researchers from diverse backgrounds and specializations to contribute original practical and/or review papers tackling challenges related to the topic of this Special Section.

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles

Associate Editor: Ladislau Matekovits, Politecnico di Torino, Italy

Guest Editors:

  1. Giancarlo Fortino, University of Calabria, Italy
  2. Zhelong Wang Dalian University of Technology, China
  3. Hassan Ghasemzadeh, Washington State University, USA
  4. Valeria Loscrì, INRIA, France
  5. Ildiko Peter, Politecnico di Torino, Italy
  6. Matti Hämäläinen, University of Oulu, Finland

Relevant IEEE Access Special Sections:

  1. Bio-Compatible Devices and Bio-Electromagnetics for Bio-Medical Applications
  2. Optimization for Emerging Wireless Networks: IoT, 5G and Smart Grid Communication Networks
  3. Healthcare Big Data

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: Bora M. Onat, Managing Editor, IEEE Access (Phone: (732) 562-6036, specialsections@ieee.org)

Advanced Signal Processing Methods in Medical Imaging

Submission Deadline: 1 August 2017

IEEE Access invites manuscript submissions in the area of Advanced Signal Processing Methods in Medical Imaging.

Medical Imaging is a technique to create visual representations of the interior of the body, with the aim of making accurate diagnosis and optimized treatments. Many medical imaging techniques are widely used to produce images, such as computer tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI)/functional MRI (fMRI).

Manual interpretation and analysis of medical images is tedious and prone to error, causing overlooked, slight lesions that occasionally result in misdiagnosis. It is critical to develop advanced signal processing methods for a wide range of low-level (image reconstruction, contrast enhancement, image segmentation, etc.) and high-level applications (interpretation, classification, and grading of image findings in diagnoses, and the planning, monitoring, and evaluation of treatment) in medical imaging for accurate diagnosis and personalized treatment. These applications need novel, advanced techniques in the areas of, but not limited to, computer vision, artificial intelligence/machine learning/pattern recognition, and evolution algorithm and optimization.

This Special Section in IEEE Access aims to collect a diverse and complementary set of articles that demonstrate new developments and applications of advanced signal processing in medical imaging. It will help both physicians and radiologists in the image interpretation, and help technicians to exchange the latest technical progresses. These topics of interest include, but are not limited to the following:

  • Medical imaging modalities (CT and low dose CT, X-ray, ultrasound, PET, SPECT, MRI, MRSI, DTI, fMRI, Hyper-spectrum, etc.)
  • New Algorithms, models and applications of advanced signal processing methods using
    • Computer vision
    • Artificial intelligence/machine learning/pattern recognition (e.g., Perceptron, Bayesian network, support vector machine, fuzzy logic, etc.)
    • Wavelet transform
    • Deep learning
    • Chaos theory
  • 3D Bio-printing
  • Smart and interactive medical system
  • Global optimization and evolutionary algorithm
  • Metaheuristics and swarm intelligence
  • Fractional Signal Processing
  • Medical security

 

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Yudong Zhang, Nanjing Normal University, China

Guest Editors:

  1. Yin Zhang, Zhongnan University of Economics and Law, China
  2. Zhengchao Dong, Columbia University, USA
  3. Ti-Fei Yuan, Nanjing Normal University, China
  4. Liangxiu Han, Manchester Metropolitan University, UK
  5. Ming Yang, Nanjing Children’s Hospital, Nanjing Medical University, China
  6. Carlo Cattanti, University of Tuscia, Italy
  7. Huimin Lu, Kyushu Institute of Technology, Japan

 

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