Real-Time WBAN Monitoring: An Adaptive Framework for Selective Signal Restoration and Physiological Trend Prediction.

The evolution and empowerment of Wireless Body Area Network (WBAN) is achieved through the rapid advancement in the wireless communication technologies. The use of different kinds of sensors which are utilized in the health care applications for patient monitoring are helped for diagnosis of life threatening disease which can be improved by using WBAN. These wearable systems help in controlling the life of patient is as they play essential role to save patient’s life. In recent past, the system architecture is constructed for WBAN for monitoring of health care application and enhancing the technical requirements in a WBAN network. Although, Wireless Body Area Networks (WBAN) is one of the emanate technology which utilizes the patient health condition for monitoring in real time, several issues that are faced by WBAN are Quality of Service (QoS), security, data loss, authentication, channel issues and energy efficiency. Most of the WBANs utilizes wireless channel for process of communication in which these typical sensors with single transceiver device transmits the information with low power by utilizing a single channel using Medium Access Control (MAC) layer in WBAN. However, the degradation in performance of these devices is high when the sensors density is increased. The solution to overcome this performance degradation is carried out by making use of multiple channels, due to which the channels are optimally utilized and the cooperation among the sensor nodes is achieved. In this paper, the survey of different protocols used for WBAN under different channel conditions is discussed in WBANs with its merits.

Networks play an important role in the day-to-day life of every individual. Networks are involved in the transmission of necessary information between the sender and receiver in the channel. Wireless Body Area Network (WBAN) is a major advancement in the field of network communication. Due to the arrival of the Micro Electromechanical System (MEMS) and several intelligent sensors, collaboration with WBAN makes accurate predictions of parameters in the human body. WBAN has numerous applications in medical and non-medical fields. WBANs have demonstrated remarkable capabilities in real-time health monitoring, facilitating the collection of vital physiological data from individuals in diverse environments. Firstly, their low-power and energy-efficient design ensures prolonged device operation, making them suitable for continuous monitoring over extended periods. Additionally, the miniaturization of sensors and the integration of wireless communication technologies enable seamless data transmission to centralized healthcare systems. Furthermore, the integration of artificial intelligence and machine learning algorithms in WBAN systems has enabled personalized health analytics, allowing for more precise and context-aware health monitoring. This paper gives a survey of the WBAN standard, security in WBAN, several authentication approaches, routing, and MAC protocols. In addition, this paper describes the challenges faced by WBAN, such as network partitioning, changes in postures, lifetime issues, and quality of service (QoS). At last, the advancement in WBAN is for future improvement in the area of body area networks.

Real-time health monitoring in WBANs using hybrid Metaheuristic-Driven Machine Learning Routing Protocol (MDML-RP)

Wireless body area networks (WBANs) are an emerging technology expected to revolutionize mobile healthcare via the real-time monitoring and analysis of medical data. This article describes the generalized WBAN concept and examples of WBAN medical applications for a variety of users and scenarios. The properties of wireless communication channels used in WBANs - specifically the human body communications channel and the 60 GHz Millimeter-wave (mmWave) - highlight the challenges facing modern WBAN development. Several research topics related to WBAN implementation in 5G networks are examined, including simulating extremely high-frequency communications, routing protocols, energy harvesting, tailoring WBANs to individual users, and user satisfaction. Future WBAN developments related to 6G networks and quantum technologies are also explored to demonstrate the potential future of mobile health.

Intelligent wireless body area networks (WBANs) have entered into an incredible explosive popularization stage. WBAN technologies facilitate real-time and reliable health monitoring in e-healthcare and creative applications in other fields. However, due to the limited space and medical resources, deeply deployed WBANs are suffering severe interference problems. The interference affects the reliability and timeliness of data transmissions, and the impacts of interference become more serious in mobile WBANs because of the uncertainty of human movement. In this paper, we analyze the dynamic interference taking human mobility into consideration. The dynamic interference is investigated in different situations for WBANs coexistence. To guarantee the performance of different traffic types, a health critical index is proposed to ensure the transmission privilege of emergency data for intra- and inter-WBANs. Furthermore, the performance of the target WBAN, i.e., normalized throughput and average access delay, under different interference intensity are evaluated using a developed three-dimensional Markov chain model. Extensive numerical results show that the interference generated by mobile neighbor WBANs results in 70% throughput decrease for general medical data and doubles the packet delay experienced by the target WBAN for emergency data compared with single WBAN. The evaluation results greatly benefit the network design and management as well as the interference mitigation protocols design.

Wireless Body Area Networks (WBANs) have become essential in healthcare, fitness, and emergency monitoring, where they support real-time data collection and transmission from wearable or implantable sensors. However, the effectiveness of WBANs depends heavily on reliable and secure node classification, as these networks face numerous challenges, including data integrity issues, privacy concerns, and resource constraints. This study addresses the critical problem of accurately and securely classifying nodes in WBANs to ensure that only trusted data sources contribute to network operations, thus minimizing risks related to data breaches, energy inefficiency, and misclassification. The primary objective of this study is to analyze and evaluate various classification algorithms—ranging from traditional machine learning techniques to advanced AI models—within the context of WBANs. Additionally, this study explores methods to enhance WBAN security and optimize resource consumption, focusing on power efficiency, latency reduction, and error mitigation. Our contributions include a comparative analysis of different algorithms based on performance metrics such as accuracy, precision, recall, F1 score, energy efficiency, and robustness. We also introduce a framework for incorporating security-enhanced classification techniques, such as encryption, data anonymization, and authentication, to safeguard WBAN data and maintain network integrity. By providing a comprehensive overview of current challenges and advanced classification methods, this study aims to inform the development of scalable, secure, and efficient classification models tailored to WBANs. Our findings underscore the importance of balancing accuracy, energy efficiency, and security to create WBAN systems that are both trustworthy and adaptable. This research contributes to the ongoing evolution of WBAN technology, paving the way for improved reliability in applications that demand high standards of data integrity and real-time monitoring.

Wireless Body Area Network (WBAN) is a modern technology having a wide range of possible applications. The development scope of WBANs can diverse from hardware and applications design to network performance optimization. Reliability is a vital performance factor in WBANs. Body shadowing, environmental interference and inefficient routing can make a WBAN unreliable, which may severely affect the patient under observation. However, an opportunistic routing technique can improve the reliability via multihops by using opportunistic relays. We investigate the performance of opportunistic routing with two different path loss models for wearable WBANs, i.e., Log-normal path loss model and IEEE 802.15.6 Channel Model (CM) 3A. The performance metrics for the analysis include network lifetime, Packet Loss Probability (PLP), end-to-end (ETE) delay, and energy used per data packet. By using opportunistic routing with IEEE 802.15.6 CM 3A in comparison to Log-normal path loss model, reliability and energy efficiency are improved up to 16% and 25% respectively.

Wireless Body Area Networks (WBANs) are usually designed for pervasive healthcare applications. Since the primary traffic in WBAN is vital physiological signals, guaranteeing the Quality of Service (QoS) is crucial while designing WBAN. However, QoS of WBAN will be degraded in strong inter-WBAN interference environment such as hospitals and senior communities, where WBANs are densely deployed. In this paper, by focusing on a more practical WBAN model, we propose a non- cooperative power control game to mitigate inter- WBAN interference, in which the cost function is well designed by considering both QoS requirement and energy constraint. The existence of at least one Nash equilibrium (NE) point for the game is proved and a sufficient condition for the uniqueness of the NE is derived. To guarantee non-cooperative among WBANs, an interference segmentation estimate (ISE) algorithm is proposed to obtain an approximation of the NE point. Simulation results demonstrate the effectiveness of the proposed ISE algorithm.

Nowadays, interests in Healthcare Monitoring System (HMS) based on Wireless Body Area Network (WBAN) have grown considerably due to the increasing aging population. HMS expected to reduce healthcare expenses by enabling the continuous monitoring of patient health remotely during their daily activities. From a medical point of view, WBAN will emerge as a key technology in providing real-time health monitoring and diagnoses of many life threatening diseases. Accordingly, several studies have been done in this area and already various journal and conference papers focusing either on WBAN or on healthcare services. Nevertheless, there is no extensive coverage on the HMS based on WBAN. This tutorial will focus on the WBAN in terms of emerging wireless technologies (supporting infrastructure and technology), HMS architecture and its applications (Continuous Monitoring and Assisted Living) and challenge design issues related to WBAN (PHY, MAC and routing layers as well as security, mobility and patient localization) and HMS (services). Furthermore, this tutorial can be considered as a deep technical overview of the state-of-the-art in the WBAN and HMS fields.

Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people's lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people's social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system's utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks.

We present a novel implementation of a distributed scheme for Dynamic Coexistence Management (DCM) of Wireless Body Area Networks (WBANs) of inertial sensors. WBANs are comprised of sensors placed on or implanted inside a person's body to collect physiological signals, activity or environmental data. Since WBANs are mobile systems by design, they can dynamically interfere with other WBANs when their users come within each other's transmission ranges. This situation which is referred to as homogeneous coexistence may result in loss of data as well as increased power consumption and transmission latencies. In this paper we present an implementation of the DCM mechanism for WBANs of inertial sensors that are designed for real-time activity monitoring and gesture recognition. The proposed scheme is implemented and evaluated on sensors that use Nordic wireless transceivers for communication; however, it can be adapted to other types of lowpower wireless standards such as IEEE 802.15.4. Our results indicate that using DCM we can achieve a close to perfect performance with 15-20% more successfully received frames when WBANs are exposed to dynamic coexistence.

The emergence of biomedical sensor devices, wireless communication, and innovation in other technologies for healthcare applications result in the evolution of a new area of research that is termed as Wireless Body Area Networks (WBANs). WBAN originates from Wireless Sensor Networks (WSNs), which are used for implementing many healthcare systems integrated with networks and wireless devices to ensure remote healthcare monitoring. WBAN is a network of wearable devices implanted in or on the human body. The main aim of WBAN is to collect the human vital signs/physiological data (like ECG, body temperature, EMG, glucose level, etc.) round-the-clock from patients that demand secure, optimal and efficient routing techniques. The efficient, secure, and reliable designing of routing protocol is a difficult task in WBAN due to its diverse characteristic and restraints, such as energy consumption and temperature-rise of implanted sensors. The two significant constraints, overheating of nodes and energy efficiency must be taken into account while designing a reliable blockchain-enabled WBAN routing protocol. The purpose of this study is to achieve stability and efficiency in the routing of WBAN through managing temperature and energy limitations. Moreover, the blockchain provides security, transparency, and lightweight solution for the interoperability of physiological data with other medical personnel in the healthcare ecosystem. In this research work, the blockchain-based Adaptive Thermal-/Energy-Aware Routing (ATEAR) protocol for WBAN is proposed. Temperature rise, energy consumption, and throughput are the evaluation metrics considered to analyze the performance of ATEAR for data transmission. In contrast, transaction throughput, latency, and resource utilization are used to investigate the outcome of the blockchain system. Hyperledger Caliper, a benchmarking tool, is used to evaluate the performance of the blockchain system in terms of CPU utilization, memory, and memory utilization. The results show that by preserving residual energy and avoiding overheated nodes as forwarders, high throughput is achieved with the ultimate increase of the network lifetime. Castalia, a simulation tool, is used to evaluate the performance of the proposed protocol, and its comparison is made with Multipath Ring Routing Protocol (MRRP), thermal-aware routing algorithm (TARA), and Shortest-Hop (SHR). Evaluation results illustrate that the proposed protocol performs significantly better in balancing of temperature (to avoid damaging heat effect on the body tissues) and energy consumption (to prevent the replacement of battery and to increase the embedded sensor node life) with efficient data transmission achieving a high throughput value.

Wireless body area network (WBAN) is an emerging technology that has enormous potential to be implemented in medical applications. However, the performance of WBANs can be severely degraded by concomitant inter-WBAN interference in some specific environments, where the multiple WBANs are densely deployed, e.g., hospitals and senior citizen communities. In this paper, a novel coexisting mechanism is proposed to deal with the multi-WBANs coexisting which can provide differentiated communication QoS for different WBANs according to their own priority conditions. The proposed mechanism consists of four parts which are time slot allocation, access control, active part interleaving, and power control. Specifically, the time slot allocation is designed based on the game theory. Access control and Active period scheduling are designed referring to the coexisting methods specified in IEEE 802.15.6 standard. In addition, the power control utilizes mobility prediction to adjust transmitting power for each coexisting WBAN. The simulation results demonstrate that the proposed mechanism is stable and convergent in varying coexisting scenarios and can realize differentiated time slot allocation depending on WBANs' priority conditions. Furthermore, when compared with the original mechanisms specified in IEEE 802.15.6, transmission performance of coexisting WBANs is improved in terms of transmission outage probability, transmission energy efficiency, and overall throughput.

In ubiquitous health-care monitoring (HCM), wireless body area networks (WBANs) are envisioned as appealing solutions that may offer reliable methods for real-time monitoring of patients’ health conditions by employing the emerging communication technologies. This paper therefore focuses more on the state-of-the-art wireless communication systems that can be explored in the next-generation WBAN solutions for HCM. Also, this study addressed the critical issues confronted by the existing WBANs that are employed in HCM. Examples of such issues include wide-range health data communication constraint, health data delivery reliability concern, and energy efficiency, which are attributed to the limitations of the legacy short range, medium range, and the cellular technologies that are typically employed in WBAN systems. Since the WBAN sensor devices are usually configured with a finite battery power, they often get drained during prolonged operations. This phenomenon is technically exacerbated by the fact that the legacy communication systems, such as ZigBee, Bluetooth, 6LoWPAN, and so on, consume more energy during data communications. This unfortunate situation offers a scope for employing suitable communication systems identified in this study to improve the productivity of WBANs in HCM. For this to be achieved, the emerging communication systems such as the low-power wide-area networks (LPWANs) are investigated in this study based on their power transmission, data transmission rate, data reliability in the context of efficient data delivery, communication coverage, and latency, including their advantages, as well as disadvantages. As a consequence, the LPWAN solutions are presented for WBAN systems in remote HCM. Furthermore, this research work also points out future directions for the realization of the next-generation of WBANs, as well as how to improve the identified communication systems, to further enhance their productivity in WBAN solutions for HCM.