Special Issue "Advances in IoMT for Healthcare Systems"
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 31 August 2023 | Viewed by 13885
Special Issue Editors

Interests: wireless sensor networks; internet-of-things; mobile and wireless networks
Special Issues, Collections and Topics in MDPI journals

Interests: Internet of Things; vehicle-to-everything communication; smart cities; machine learning, computational intelligence; data science; human factors engineering
Special Issues, Collections and Topics in MDPI journals

Interests: intelligent systems; big data; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: security; Blockchain; Cloud computing; IoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid development of micro-computing devices such as sensors, actuators, RFID tags, and machine-to-machine (M2M) communications has enabled new Internet of Things (IoT) solutions to reshape many network applications. One example of this is the healthcare system, which has been revolutionized by the IoT solutions by the introduction of a branch of the Internet of Medical Things (IoMT) system. The IoMT solution has attracted a great deal of attention because of its ability to autonomously acquire, analyze, and share data on the Internet with the help of micro-computing medical devices, data-processing algorithms, and supporting communication protocols. Modern healthcare services widely use IoMT applications to remotely monitor patients with chronic diseases and improve quality of life. However, the adoption of IoMT faces many challenges, such as the interoperability between medical systems, the design of wearable (and/or ambient) medical devices, medical data analysis, the security and privacy of patient records, and the interaction between patients and medical devices. In this regard, modern computing technologies (such as machine learning, cloud/edge computing, and data mining), soft computing methods, and dedicated communication protocols may help provide services for the IoMT system to improve timely patient diagnosis; improve disease control, treatment methods, and drug management; and improve the user experience of the patient and medical staff.
The purpose of this Special Issue is to provide the latest reference materials on theoretical and practical challenges, as well as innovative ideas and solutions for IoMT for healthcare systems. The scope of this Special issue includes (but is not limited to): high-performance resilient infrastructure for IoMT systems; ontology-based recommendation and disease identification systems; innovative wearable and/or ambient IoMT devices; collection, modeling, and evaluation of big data for IoMT systems; in-hospital and in-home healthcare functions for IoMT systems; M2M interoperability and communication protocols for IoMT systems; optimized data security, privacy, and trust for IoMT systems; AI-based IoMT in telehealth virtual consulting and patient monitoring; innovative human–computer interaction models for IoMT systems; legal, ethical, and social considerations in IoMT for healthcare systems; AI-based signal and image processing applied to health; data analysis for health issues; EEG signals and systems.
Dr. Jin-Ghoo Choi
Dr. Muhammad Shafiq
Prof. Dr. Habib Hamam
Dr. Omar Cheikhrouhou
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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Keywords
- Internet of Medical Things
- smart healthcare
- telehealth virtual consulting
- remote pain/patient monitoring
- Medical Big Data Analytics
- EEG signals
- Artificial Intelligence applied to health
- Data Analysis
- RFID
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Interactive Cardio System for Healthcare Improvement
Abstract: The paper presents an interactive cardio system that can be used to improve healthcare. The presented system receives, processes and analyzes cardio data using an Internet-based software platform. The system enables the acquisition of biomedical data by means of various means of recording cardiac signals located in remote locations around the world. The recorded discretized cardio information is transmitted to the system for processing and mathematical analysis. At the same time, the recorded cardio data can be stored online in established databases. The article presents the algorithms for preprocessing and mathematical analysis of cardio data. The presented system can be used for remote monitoring of patients with cardiovascular chronic diseases, patients in remote settlements (where, for example, there may be no hospitals), control and assistance in the process of treatment and taking prescribed drugs and thus help to improve people's quality of life. The issue of ensuring security of cardio information and confidentiality of personal data of health users is considered
Authors: Galya Georgieva-Tsaneva
Affiliation: Institute of Robotics, Bulgarian Academy of Science, 1113 Sofia, Bulgaria
Title: Real-Time FMCW Radar-Based Respiration Rate Monitoring Using Adaptive Waveform Filtering
Authors: Ying-Ren Chien (a), Yu-Hui Shen (a), and Shih-Hau Fang (b)
Affiliation: (a)Department of Electronic Engineering, National Ilan University, Yilan, Taiwan
(b)Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan