Wireless Body Area Networks Routing Protocols: A Review

Alhudhaif

Computers and Electrical Engineering

et al. 2021

Self Cite

Coronavirus is an infectious life-threatening disease and is mainly transmitted through infected person coughs, sneezes, or exhales. This disease is a global challenge that demands advanced solutions to address multiple dimensions of this pandemic for health and wellbeing. Different types of medical and technological-based solutions have been proposed to control and treat COVID-19. Machine learning is one of the technologies used in Magnetic Resonance Imaging (MRI) classification whereas nature-inspired algorithms are also adopted for image optimization. In this paper, we combined the machine learning and nature-inspired algorithm for brain MRI images of COVID-19 patients namely Machine Learning and Nature Inspired Model for Coronavirus (MLNI-COVID-19). This model improves the MRI image classification and optimization for better diagnosis. This model will improve the overall performance especially the area of brain images that is neglected due to the unavailability of the dataset. COVID-19 has a serious impact on the patient brain. The proposed model will help to improve the diagnosis process for better medical decisions and performance. The proposed model is evaluated with existing algorithms and achieved better performance in terms of sensitivity, specificity, and accuracy.

Section: Proposed Machine Learning and Nature Inspired Solution For Covid-19mentioning

confidence: 99%

Nature-inspired solution for coronavirus disease detection and its impact on existing healthcare systems

Alhudhaif

Computers and Electrical Engineering

et al. 2021

Self Cite

Journal of Network and Computer Applications

“…Electric and electromagnetic radiation causes temperature rise in the sensor devices which leads the tissue to absorb a part of the temperature. The effect of temperature rise and specific absorption ratio is discussed in [127]. There have been few researches to avoid overheating problem due to routing protocols.…”

Section: Overheatingmentioning

confidence: 99%

A comprehensive review of wireless body area network

Hasan

Biswas

Ahmed

et al. 2019

158

Recent development and advancement of information and communication technologies facilitate people in different dimensions of life. Most importantly, in the healthcare industry, this has become more and more involved with the information and communication technology-based services. One of the most important services is monitoring of remote patients, that enables the healthcare providers to observe, diagnose and prescribe the patients without being physically present. The advantage of miniaturization of sensor technologies gives the flexibility of installing in, on or off the body of patients, which is capable of forwarding physiological data wirelessly to remote servers. Such technology is named as Wireless Body Area Network (WBAN). In this paper, WBAN architecture, communication technologies for WBAN, challenges and different aspects of WBAN are illustrated. This paper also describes the architectural limitations of existing WBAN communication frameworks. blueFurthermore, implementation requirements are presented based on IEEE 802.15.6 standard. Finally, as a source of motivation towards future development of research incorporating Software Defined Networking (SDN), Energy Harvesting (EH) and Blockchain technology into WBAN are also provided.

“…The sensed data are then transferred to the patient's physician for further response through a central controller called hub. [1][2][3][4] WBAN's healthcare applications attracted the attention of research community to cope with the number of challenges and issues including traffic prioritization, handling of traffic heterogeneity, energy efficiency, and delay intolerant communication. 5,6 For this purpose, a separate task group of IEEE 802.15.6 was time-honored by IEEE 802 to provide data communication standard for wide-range applications for healthcare monitoring.…”

Section: Introductionmentioning

confidence: 99%

Dynamic superframe adaptation using group-based media access control for handling traffic heterogeneity in wireless body area networks

Zia

Bashir

International Journal of Distributed Sensor Networks

2020

Self Cite

Wireless body area network is a promising technology that brings healthcare to a new level of personalization. The applications of wireless body area network are not limited to healthcare monitoring applications but vastly used in entertainment applications. The applications are emerging at a fast pace and attract the attention of researchers. IEEE 802.15.6 provides a communication standard which specifies the physical layer and media access control layer operations for wireless body area networks. A fixed superframe structure is used for handling of heterogeneous traffics of wireless body area networks through pre-defined user priorities. This leads to inefficient use of superframe time duration because of fixed time phases for different types of data traffic. In this article, a novel group-based classification of traffic is introduced to avoid contention and inefficient use of superframe duration. A group-based media access control is developed to adjust the superframe duration according to high priority traffic whereas the rest of the traffic is controlled using node-based buffering. The experimental results showed that the proposed media access control outperformed adaptive beaconing medium access control and priority media access control, in terms of stability period, delay, throughput, transmission loss, and residual energy.