Topic Editors

1. Department of Computer Science and Engineering, Kuwait College of Science and Technology, Kuwait City, Kuwait
2. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada
Dr. Ali Karime
Department of Electrical and Computer Engineering, Royal Military College of Canada, Kingston, ON, Canada

Intelligent Health Monitoring and Assistance Systems and Frameworks

Abstract submission deadline
20 June 2023
Manuscript submission deadline
20 August 2023
Viewed by
4543

Topic Information

Dear Colleagues,

Healthcare systems and frameworks have evolved over the years and have become significantly autonomous. Healthcare monitoring, assistance, and treatment have greatly benefited from advances in artificial intelligence (AI), computer processing, data storage, communication, and networking. With the recent pandemic came new and innovative solutions for health monitoring and assistance. Drones were used to deliver medicine to remote areas. Image processing and machine learning solutions were used to identify potential viral infections. In-home health assistance was available through advanced IoT-based sensors and devices. Such advances have led researchers and health practitioners to envision new state-of-the-art solutions that rely heavily on AI-based mechanisms. In that context, this Special Issue invites researchers both in academia and industry to submit their original contributions in the area of AI-enabled health monitoring and assistance systems. The topics may include areas in networking, security, machine learning, haptics, modeling, and IoT-based health tools.

Dr. Ismaeel Al Ridhawi
Dr. Ali Karime
Topic Editors

Keywords

  • artificial intelligence
  • electronic health
  • haptics
  • blockchain
  • next-generation networks
  • internet of things

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.838 3.7 2011 14.9 Days 2300 CHF Submit
Electronics
electronics
2.690 3.7 2012 14.4 Days 2000 CHF Submit
Healthcare
healthcare
3.160 2.0 2013 19.1 Days 2000 CHF Submit
Journal of Sensor and Actuator Networks
jsan
- 6.9 2012 18.4 Days 1600 CHF Submit
Sensors
sensors
3.847 6.4 2001 15 Days 2400 CHF Submit

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Published Papers (4 papers)

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Article
Telemedicine: A Survey of Telecommunication Technologies, Developments, and Challenges
J. Sens. Actuator Netw. 2023, 12(2), 20; https://doi.org/10.3390/jsan12020020 - 02 Mar 2023
Viewed by 1259
Abstract
The emergence of the COVID-19 pandemic has increased research outputs in telemedicine over the last couple of years. One solution to the COVID-19 pandemic as revealed in literature is to leverage telemedicine for accessing health care remotely. In this survey paper, we review [...] Read more.
The emergence of the COVID-19 pandemic has increased research outputs in telemedicine over the last couple of years. One solution to the COVID-19 pandemic as revealed in literature is to leverage telemedicine for accessing health care remotely. In this survey paper, we review several articles on eHealth and Telemedicine with emphasis on the articles’ focus area, including wireless technologies and architectures in eHealth, communications protocols, Quality of Service, and Experience Standards, among other considerations. In addition, we provide an overview of telemedicine for new readers. This survey reviews several telecommunications technologies currently being proposed along with their standards and challenges. In general, an encompassing survey on the developments in telemedicine technology, standards, and protocols is presented while acquainting researchers with several open issues. Special mention of the state-of-the-art specialist application areas are presented. We conclude the survey paper by presenting important research challenges and potential future directions as they pertain to telemedicine technology. Full article
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Article
A Smart Monitoring System for Self-Nutrition Management in Pediatric Patients with Inherited Metabolic Disorders: Maple Syrup Urine Disease (MSUD)
Healthcare 2023, 11(2), 178; https://doi.org/10.3390/healthcare11020178 - 06 Jan 2023
Viewed by 828
Abstract
A metabolic disorder is due to a gene mutation that causes an enzyme deficiency which leads to metabolism problems. Maple Syrup Urine Disease (MSUD) is one of the most common and severe hereditary metabolic disorders in Saudi Arabia. Patients and families were burdened [...] Read more.
A metabolic disorder is due to a gene mutation that causes an enzyme deficiency which leads to metabolism problems. Maple Syrup Urine Disease (MSUD) is one of the most common and severe hereditary metabolic disorders in Saudi Arabia. Patients and families were burdened by complex and regular dietary therapy menus because of the lack of information on food labels, it was also difficult to keep track of MSUD’s typical diet. The prototype smart plate system proposed in this work may help patients with MSUD and their caregivers better manage the patients’ MSUD diet. The use of knowledge-based, food identification techniques and a device could provide a support tool for self-nutrition management in pediatric patients. The requirements of the system are specified by using questionaries. The design of the prototype is divided into two parts: software (mobile application) and hardware (3D model of the plate). The knowledge-based mobile application contains knowledge, databases, inference, food recognition, food plan, monitor food plan, and user interfaces. The hardware prototype is represented in a 3D model. All the patients agreed that a smart plate system connected to a mobile application could help to track and record their daily diet. A self-management application can help MSUD patients manage their diet in a way that is more pleasant, effortless, accurate, and intelligent than was previously possible with paper records. This could support dietetic professional practitioners and their patients to achieve sustainable results. Full article
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Article
IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database
Healthcare 2023, 11(1), 139; https://doi.org/10.3390/healthcare11010139 - 01 Jan 2023
Viewed by 1062
Abstract
In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of [...] Read more.
In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data. Full article
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Article
Sleep Pattern Analysis in Unconstrained and Unconscious State
Sensors 2022, 22(23), 9296; https://doi.org/10.3390/s22239296 - 29 Nov 2022
Viewed by 729
Abstract
Sleep accounts for one-third of an individual’s life and is a measure of health. Both sleep time and quality are essential, and a person requires sound sleep to stay healthy. Generally, sleep patterns are influenced by genetic factors and differ among people. Therefore, [...] Read more.
Sleep accounts for one-third of an individual’s life and is a measure of health. Both sleep time and quality are essential, and a person requires sound sleep to stay healthy. Generally, sleep patterns are influenced by genetic factors and differ among people. Therefore, analyzing whether individual sleep patterns guarantee sufficient sleep is necessary. Here, we aimed to acquire information regarding the sleep status of individuals in an unconstrained and unconscious state to consequently classify the sleep state. Accordingly, we collected data associated with the sleep status of individuals, such as frequency of tosses and turns, snoring, and body temperature, as well as environmental data, such as room temperature, humidity, illuminance, carbon dioxide concentration, and ambient noise. The sleep state was classified into two stages: nonrapid eye movement and rapid eye movement sleep, rather than the general four stages. Furthermore, to verify the validity of the sleep state classifications, we compared them with heart rate. Full article
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