Modeling Telehealth Services with Generalized Nets

Stefanova-Pavlova, Maria; Andonov, Velin; Stoyanov, Todor; Angelova, Maia; Cook, Glenda; Klein, Barbara; Vassilev, Peter; Stefanova, Elissaveta

doi:10.1007/978-3-319-41438-6_16

Cited by 12 publications

(4 citation statements)

References 4 publications

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“…In this model, telecommunications and navigation technologies were used to monitor both active and mobile patients. The model used the current location of the patient as one of the vital variables [64].…”

Section: Resource Allocationmentioning

confidence: 99%

Taxonomic Exploration of Healthcare IoT: Challenges, Solutions, and Future Frontiers

Alashlam,

Alzubi

2023

Applied Sciences

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An Internet of things (IoT) ecosystem is a fast-developing network in which users can connect a heterogeneity of physical and virtual devices, including customized healthcare areas. As medical resources are scarce, populations are aging with chronic diseases and require remote monitoring, medical expenses are rising, and telemedicine is being demanded in developing nations, the IoT is an attractive topic in healthcare. Through the IoT, people can enjoy better health and diminish pressure on sanitary systems. In this study, previously published studies in Healthcare IoT (HIoT) systems are detailed, analyzed, and taxonomically classified. By categorizing the articles according to the types of HIoT systems, we dispense a detailed taxonomical study. In addition, different evaluation methodologies, tools, and metrics are discussed, along with their advantages and disadvantages. The studies indicate that power management, trust, privacy, fog computing, and resource management are among the open issues. The future of the Internet includes tactile networks, social networks, big data analytics, software-defined networking, network function virtualization, the Internet of nano things (IoNT), and blockchain. It would be beneficial to study and research HioT systems further in terms of interoperability, the implementation of real-world test beds, scalability, and mobility.

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Section: Resource Allocationmentioning

confidence: 99%

Taxonomic Exploration of Healthcare IoT: Challenges, Solutions, and Future Frontiers

Alashlam,

Alzubi

2023

Applied Sciences

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“…The earlier communication technologies, such as wired telephone lines, fax technology and networking technologies, supported quick and easy communication lines for the exchange of simple diagnostic information such as patient reports, treatment options, prescriptions, etc. The advent of wireless communication and the advancements in internet and satellite communication technologies have provided a significant boost to the delivery of healthcare [4]. They are necessary to revitalize primary healthcare since they contribute to the personalized monitoring of chronic diseases, increase access to healthcare for rural populations, and optimize data measurement and management.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Role of 6G Technology in Enhancing Quality of Experience for m-Health Multimedia Applications: A Comprehensive Survey

Nasralla

Khattak

Rehman

et al. 2023

Sensors

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Mobile-health (m-health) is described as the application of medical sensors and mobile computing to the healthcare provision. While 5G networks can support a variety of m-health services, applications such as telesurgery, holographic communications, and augmented/virtual reality are already emphasizing their limitations. These limitations apply to both the Quality of Service (QoS) and the Quality of Experience (QoE). However, 6G mobile networks are predicted to proliferate over the next decade in order to solve these limitations, enabling high QoS and QoE. Currently, academia and industry are concentrating their efforts on the 6G network, which is expected to be the next major game-changer in the telecom industry and will significantly impact all other related verticals. The exponential growth of m-health multimedia traffic (e.g., audio, video, and images) creates additional challenges for service providers in delivering a suitable QoE to their customers. As QoS is insufficient to represent the expectations of m-health end-users, the QoE of the services is critical. In recent years, QoE has attracted considerable attention and has established itself as a critical component of network service and operation evaluation. This article aims to provide the first thorough survey on a promising research subject that exists at the intersection of two well-established domains, i.e., QoE and m-health, and is driven by the continuing efforts to define 6G. This survey, in particular, creates a link between these two seemingly distinct domains by identifying and discussing the role of 6G in m-health applications from a QoE viewpoint. We start by exploring the vital role of QoE in m-health multimedia transmission. Moreover, we examine how m-health and QoE have evolved over the cellular network’s generations and then shed light on several critical 6G technologies that are projected to enable future m-health services and improve QoE, including reconfigurable intelligent surfaces, extended radio communications, terahertz communications, enormous ultra-reliable and low-latency communications, and blockchain. In contrast to earlier survey papers on the subject, we present an in-depth assessment of the functions of 6G in a variety of anticipated m-health applications via QoE. Multiple 6G-enabled m-health multimedia applications are reviewed, and various use cases are illustrated to demonstrate how 6G-enabled m-health applications are transforming human life. Finally, we discuss some of the intriguing research challenges associated with burgeoning multimedia m-health applications.

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“…Therefore, telecommunications and navigation technologies are also important, in which the technologies of artificial intelligence have been applied [ 26 , 27 ]. Stefanova-Pavlova et al proposed the refined generalized net (GN) to track users’ locations [ 28 ]. Silva et al used Petri nets to process the reliability and availability of wireless sensor networks in a smart hospital [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch

Tan

Shih

Liu

et al. 2023

Sensors

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Mobile health (mHealth) utilizes mobile devices, mobile communication techniques, and the Internet of Things (IoT) to improve not only traditional telemedicine and monitoring and alerting systems, but also fitness and medical information awareness in daily life. In the last decade, human activity recognition (HAR) has been extensively studied because of the strong correlation between people’s activities and their physical and mental health. HAR can also be used to care for elderly people in their daily lives. This study proposes an HAR system for classifying 18 types of physical activity using data from sensors embedded in smartphones and smartwatches. The recognition process consists of two parts: feature extraction and HAR. To extract features, a hybrid structure consisting of a convolutional neural network (CNN) and a bidirectional gated recurrent unit GRU (BiGRU) was used. For activity recognition, a single-hidden-layer feedforward neural network (SLFN) with a regularized extreme machine learning (RELM) algorithm was used. The experimental results show an average precision of 98.3%, recall of 98.4%, an F1-score of 98.4%, and accuracy of 98.3%, which results are superior to those of existing schemes.

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Modeling Telehealth Services with Generalized Nets

Cited by 12 publications

References 4 publications

Taxonomic Exploration of Healthcare IoT: Challenges, Solutions, and Future Frontiers

Taxonomic Exploration of Healthcare IoT: Challenges, Solutions, and Future Frontiers

Exploring the Role of 6G Technology in Enhancing Quality of Experience for m-Health Multimedia Applications: A Comprehensive Survey

Using a Hybrid Neural Network and a Regularized Extreme Learning Machine for Human Activity Recognition with Smartphone and Smartwatch

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