Body Area Networks Research Articles

DIWGAN‐WBSN: A novel health monitoring approach for wireless body sensor networks

SummaryWireless body sensor network (WBSN) is essential for monitoring patients' health problems and offers a low‐cost option for various healthcare applications. In this manuscript, a Novel Health Monitoring Approach for WBSNs (DIWGAN‐WBSN) is proposed, which uses Dual Interactive Wasserstein Generative Adversarial Network (DIWGAN) optimized with War Strategy Optimization Algorithm (WSOA). After sensing the aforementioned attribute information, it is the responsibility of WBSN nodes to transfer the sensed data to the sink node. The Volcano Eruption Algorithm (VEA) is applied to select the optimum cluster heads in WBSN. The results from VEA are fed to the target node; it consists of DIWGAN to classify the health records and to portray the patient's health status. Generally, DIWGAN does not adopt any optimization methods for measuring the ideal parameters and guaranteeing accurate health monitoring and risk assessment. So the proposed WSOA is considered to enhance the DIWGAN. The proposed method is activated in MATLAB; its efficacy is estimated under performance metrics, like precision, specificity, accuracy, and energy utilization. The proposed approach attains 23.9%, 21.34%, and 51.09% higher accuracy; 21.45%, 13.94%, and 20.6% higher precision; 31.32%, 29.61%, and 11.03% higher specificity; and 20.9%, 19.87%, and 24.6% lower energy utilization for HD classification using the Cleveland database than the existing methods like back propagation neural network‐based risk detection in WBSN for health monitoring, random forest algorithm–based health monitoring in WBSN, and ensemble deep learning and feature fusion for health monitoring using WBSN methods, respectively.

A robust near-field body area network based on coaxially-shielded textile metamaterial

A body area network involving wearable sensors distributed around the human body can continuously monitor physiological signals, finding applications in personal healthcare and athletic evaluation. Existing solutions for near-field body area networks, while facilitating reliable and secure interconnection among battery-free sensors, face challenges including limited spectral stability against external interference. Here we demonstrate a textile metamaterial featuring a coaxially-shielded internal structure designed to mitigate interference from extraneous loadings. The metamaterial can be patterned onto clothing to form a scalable, customizable network, enabling communication between near-field reading devices and battery-free sensing nodes placed within the network. Proof of concept demonstration shows the metamaterial’s robustness against mechanical deformation and exposure to lossy, conductive saline solutions, underscoring its potential applications in wet environments, particularly in athletic activities involving water or significant perspiration, offering insights for the future development of radio frequency components for a robust body area network at a system level.

Design of an optimized energy-efficient routing protocol for reliable wireless body area networks

Energy limitation is one of the essential parameters in the design of a Wireless body area networks (WBANs) as it is important to improve the lifetime of the network. WBAN routing is an effective approach for establishing energy efficiency sets and assign time slots for the network. Many algorithms that deal with interference model treats the whole WBAN as a minimum interference unit and increase their lifetime cycle. In this research, we report an effective low-energy adaptive clustering hierarchy (LEACH) routing protocol using MATLAB simulation and related C++ simulation codes to enhance the overall performance of the network by improving the energy efficiency and network lifetime cycles. Furthermore, the study sheds light up on the comparison of the protocol and proposes a modified protocol for WBAN. Based on the results obtained from conducting different configurations in the proposed design, the base station should be situated near the network to insure high network performance.

A new highly efficient MAC protocol for WBAN: exceptional performance in the face of selfish behaviors

Over the last two decades, wireless body area networks (WBANs) have gained significant traction in healthcare applications. These networks facilitate connections among various sensors, which can be integrated into clothing, placed directly on the body, or implanted beneath the skin. While these sensors typically serve a single application, they generate traffic with diverse requirements. Managing this diversity necessitates tailored treatment to meet specific traffic needs while satisfying application requirements such as reliability and timeliness. In this paper, we propose a novel, flexible, and power-efficient medium access control (MAC) protocol designed to seamlessly complement existing solutions. Our protocol, available in two versions as an enhancement to the beacon-enabled mode of IEEE 802.15.4, aims to optimize quality of service (QoS) for periodic traffic applications within WBANs, irrespective of traffic and density conditions, without compromising energy efficiency. Our results demonstrate significant improvements compared to the standardized IEEE 802.15.4-MAC protocol across all test scenarios, even in the presence of selfish behaviors. These findings underscore the protocol’s efficacy in enhancing reliability and efficiency in wireless healthcare systems.

EADA: Energy-Aware Adaptive Duty-Cycle Adjustment in Superframe for IEEE 802.15.6-Based Wireless Body Area Networks

EADA: Energy-Aware Adaptive Duty-Cycle Adjustment in Superframe for IEEE 802.15.6-Based Wireless Body Area Networks

Analyzing Human-Centric Wireless Energy Harvesting for Sustainable and Resilient Energy Systems

Discussions around wireless communications and energy harvesting in the literature are elitist and techno-centric. There is a need for more studies on a human-centric approach that simplifies the concept and links energy harvesting with human empowerment and well-being. Also, studies so far on the implementation of wireless energy harvesting in rural settlements have been scanty despite the important role wireless communication plays in social interactions and financial transactions within rural communities. The challenge of little awareness of the human sustainability impact of WEH is impeding stakeholders’ advocacy and advancement of wireless energy harvesting (WEH) despite its real and perceived benefits. So far, research efforts as reported in the literature are less than proportionate to the potential of WEH. Apart from providing sustainable energy for wireless devices and networks, its generation of nonelectric renewable energy is a huge plus for ensuring access to affordable, reliable, sustainable, and modern energy for all as contained in the United Nations Sustainable Development Goal 7 (SDG 7). Given the astronomical growth in the use of wireless devices globally, more research studies are needed to create more awareness for massive WEH advocacy. This study uses a model-driven approach to simplify and highlight critical aspects of WEH such as wireless body area network, sources of non-electric renewable energy sources, green energy (environmental protection), intermittent nature of renewable wireless energy sources, and research directions. Also, the application of WEH for the sustenance of lives and livelihood in rural economies is examined using the rural community of Adum-Aiona in Nigeria as a case study. It is expected that the information provided will create more awareness and foster further discussions around the human-centric angle of WEH even as advances in technology continue to be made.

Secure Patient Data Monitoring and Efficient Routing Optimization using a Hyperelliptic Curve Cryptography with Fuzzy-based Priority in WBSN

Aims and Background: Wireless Body Sensor Network (WBSN) technology is one of the major research areas in the medical and entertainment industries. A wireless sensor network (WSN) is a dense sensor network that senses environmental conditions, processes, and outgoing data at the sink node. A WBSN develops patient monitoring systems that provide the flexibility and mobility needed to monitor patient health. In data communications, it is difficult to find flexible optical routing paths, switching capabilities, and packet processing in the composition of optical networks. Information-centric networks (ICNs) are a new network model and are different from information- centric models. The priority of the information-centric model is the communication network. Objectives: In the existing literature, such methods are typically developed using computationally expensive procedures, such as bilinear pairing, elliptic curve operations, etc., which are unsuitable for biomedical devices with limited resources. Using the concept of hyperelliptic curve cryptography (HECC), we propose a new solution: a smart card-based two-factor mutual authentication scheme. In this new scheme, HECC’s finest properties, such as compact parameters and key sizes, are utilized to enhance the real-time performance of an IoT-based TMIS system. Methodology: A fuzzy–based Priority Aware Data Sharing (FPADS) method is introduced to schedule the priority data and monitor the transmission length. The child node adjusts the transmission speed of the cluster head with the help of a fuzzy logic controller (FLC). Results: The proposed model estimated the traffic load of the child node and the priority of the different amounts of data to be transmitted. The principle of scheduling data packets to be developed is based on the precedence of the data with the lowest transmit length in the network. Conclusion: The proposed FPADS performance increases in terms of scheduling time utilisation, traffic distribution, and mean delay. Simulations have been done using NS2, and the outcomes have shown that the proposed methodology is efficient and improves the overall QoS of the system.

Performance evaluation of the congestion severity aware rate regulation (CSRR) algorithm in wireless body area networks

SummaryWireless body area network (WBAN) is a potential low‐cost technology for privacy‐sensitive telemedicine and e‐health monitoring and services. However, it faces limited protocol and physical resource support challenges, which can result in packet transfer difficulties. In particular, WBAN requires an emergency‐aware technology that ensures a promising quality of service (QoS). One significant issue affecting QoS and energy efficiency in WBAN is congestion. Effective congestion control techniques are essential for achieving proper load balancing. To address these challenges, we propose a congestion severity aware rate control (CSRR) algorithm that enhances packet transmission rate by reducing packet losses and retransmissions. The CSRR algorithm incorporates a fuzzy controller to predict congestion rates based on runtime metrics. To regulate congestion window growth in different algorithm phases, we introduce sequences such as the Fibonacci retracement sequence, knight's move sequence, and the binary logarithm of the primorial sequence to regulate congestion window growth in the different phases of the proposed algorithm. We mathematically analyze the proposed CSRR algorithm using a Markov model. The simulation results demonstrate the superiority of our algorithm compared to existing approaches. Specifically, our algorithm achieves significant optimizations in terms of throughput (52.92%), packet loss (38.11%), delay (37.23%), and remaining energy (36.86%) when compared to existing algorithms.

Systematic survey on data security in wireless body area networks in IoT healthcare system.

In the Internet of Things (IoT) healthcare sector, the wireless body area network (WBAN) is being used to optimize medical results by tracking and treating patients as they go about their daily lives. Health insurance has also been one of the cybercriminal's main goals. The Systematic Review of IoT Healthcare systems particularly wireless body area networks is significant, to reach the benefits and challenges faced by existing methods in the domain. This study provides a systematic survey of WBAN data protection. Various types of devices are used in medical science to detect and diagnose diseases. The network is an integral part of medical science in today's era. In medical sciences, sensors take data from a problematic place like cancerous cells. This research discussed a lot of techniques in the literature review. Most of them are not able to fulfill the requirements. If an unauthorized person reaches the data that can be a severe issue, like the diagnosed disease was blood cancer, and after unauthorized access manipulation can change even the diagnosed issue in the database. A doctor can prescribe the medication based on provided data that has been manipulated by unauthorized persons. Several existing schemes are explored in the literature to determine how the protection of sharing patients' healthcare data can be improved. The systematic literature review (SLR) of multiple security schemes for WBAN is presented in this survey paper.

Designing of Textile-based Wearable Antennas at 2.45 GHz

In the recent times, there are a continuous development and distinctive growth in the implementation of wearable sensors and flexible devices in real lifes. These devices are exploited to monitor signals in healthcase applications, for the intents of geo‐positioning of the rescue, and in military personnel. There are abundant of frequency bands have been introduced worldwide such for the narrow-band versions 2.36–2.40 GHz for the medical body area network, 2.40–2.48 GHz as the industrial, scientific, and medical band, and 3.1–10.6 GHz for the ultra‐wideband applications. In designing of wearable antennas, we find many challenges due to the practical implementation of antennas next to human body. The human body presents as very loss structures and its presence affects the form of the radiation pattern of the antenna and also can shift its operational frequency. Moreover, placement of the antenna on convex structures with different curvature radii also affects its performance due to overall change in electrical length. In this study, we analyze wearable antennas based on textile flexible materials for WBAN implementation. The type of the antennas is a metasurface implementation of microstrip antennas. In this way, we can reduce the thickness of the material significantly to prevent the radiation efficiency of the antennas. We will observe the bending effect on the radiation patterns of the antenna.

An Efficient Certificateless Anonymous Signcryption Scheme for WBAN.

A Wireless Body Area Network (WBAN), introduced into the healthcare sector to improve patient care and enhance the efficiency of medical services, also brings the risk of the leakage of patients' privacy. Therefore, maintaining the communication security of patients' data has never been more important. However, WBAN faces issues such as open medium channels, resource constraints, and lack of infrastructure, which makes the task of designing a secure and economical communication scheme suitable for WBAN particularly challenging. Signcryption has garnered attention as a solution suitable for resource-constrained devices, offering a combination of authentication and confidentiality with low computational demands. Although the advantages offered by existing certificateless signcryption schemes are notable, most of them only have proven security within the random oracle model (ROM), lack public ciphertext authenticity, and have high computational overheads. To overcome these issues, we propose a certificateless anonymous signcryption (CL-ASC) scheme suitable for WBAN, featuring anonymity of the signcrypter, public verifiability, and public ciphertext authenticity. We prove its security in the standard model, including indistinguishability, unforgeability, anonymity of the signcrypter, and identity identifiability, and demonstrate its superiority over relevant schemes in terms of security, computational overheads, and storage costs.

Levy flight based momentum search and Circle Rock Hyrax swarm optimization algorithms for energy effective clustering and optimal routing in wireless body area networks

In recent years, the connectivity of a new dimension has been brought to Wireless Body Area Networks (WBANs) through the concept of the Wearable Internet of Things (WIoT). WIoT offers valuable functionalities like data collection, analysis, and transmission for real-time health monitoring services. However, WBANs are characterized by a large number of battery-powered sensor nodes, making them resource-constrained. While keeping standard WSN abilities, WBAN's significant obstacles are data communication, social mobility, high interference in dense deployment, latency, and energy consumption of sensor nodes. As a result, the implementation and design of an application require dependable data transfer and an energy-efficient architecture. It proved critical to have as little delay as possible while delivering correct data. To overcome these issues, this study developed a novel energy-efficient clustered and optimized routing scheme in WBAN. Due to its effective scalability, this work employs an Improved Self-Executing Active Cross-Propagated (ISAC) clustering approach to form clusters in Wireless Body Area Networks (WBANs). Subsequently, the selection of the best Cluster Heads (CHs) is facilitated by the Levy Flight-based Momentum Search Algorithm (LFMSA). The Circle Rock Hyrax Swarm Optimization (CRH) algorithm is then utilized for energy-efficient routing. In determining the CH in each cluster, consideration is given to both residual energy and connectivity. The proposed framework minimizes the number of transmissions and overall transmission distance, optimizing inter and intra-cluster transmission distances. Additionally, the framework ensures energy-efficient packet delivery from CHs to the sink node. Performance comparisons, conducted using various statistical measures and simulated on the NS-2 platform, demonstrate that the proposed framework outperforms existing routing protocols and clustering methodologies. In comparison to previous methodologies, the proposed framework consistently achieves superior results.

Thermal-energy-efficient-secured-link reliable and delay-aware routing protocol (TESLDAR) for wireless body area networks

Wireless Body Area Networks (WBANs) have emerged as a transformative technology for health monitoring, leveraging sensor nodes placed on or within the human body. This paradigm offers real-time insights into physiological parameters, enabling remote healthcare applications and enhancing patient well-being. However, the WBANs bring challenges that demand innovative solutions to ensure their seamless integration into healthcare ecosystems. Secondly, trustworthiness becomes paramount in healthcare applications, where the sensitivity of health-related data necessitates secure and reliable communication. Lastly, congestion issues, arising from bandwidth constraints and concurrent data transmissions, affect the performance of WBANs, impacting data integrity, energy consumption, and quality of service. Therefore, this paper proposes a TESLDAR protocol that incorporates the proposed Jellyfish Updated Aquila Narrow ExploExpand (JUANE) method aims to address issues such as hotspot-induced thermal stress, trustworthiness concerns, and congestion challenges. The proposed algorithm incorporates Jellyfish Optimization (JFO), inspired by the adaptable movement of jellyfish, with characteristics inspired by the Aquila bird. The method's innovative integration of jellyfish and bird-inspired behaviors positions it as a promising solution for efficient route maintenance in WBANs addressing thermal, trust, and congestion challenges for enhanced reliability in healthcare monitoring applications.

Metasurface loaded dual band antenna for high gain on- and off- body communication

Metasurfaces are specially made materials designed to have unique properties not found in nature. They are categorized into different types, such as artificial magnetic conductor (AMC), partial reflecting surfaces (PRS), and frequency selective surfaces (FSS). Among these, FSS is commonly used in today’s technology to improve antenna performance, especially in boosting signal strength by blocking unwanted radiation. Recent research is focused on creating FSS-based antennas for Ultra-wideband (UWB) or single band applications, with a significant emphasis on enhancing signal strength. Unlike traditional methods, this study concentrates on designing antennas that are both simple in shape and offers broader frequency coverage, specifically for 2.45 GHz and 5.8 GHz applications. To enhance antenna performance, a dual-band FSS is employed, optimizing the system for improved operation at both resonating frequencies. This results in a high-gain antenna system, which is further investigated for body area network (BAN) systems, considering the crucial performance metric of specific absorption rate (SAR). The findings are compared with recently reported FSS-based antennas to underscore their scientific contribution and potential for high gain, low SAR applications within the 2.45 GHz and 5.8 GHz frequency bands.

Multi-Disjoint Path opportunistic networks with Hidden Markov Chain modeling

Advancing the efficiency and reliability of wireless sensor networks is a paramount pursuit in modern networking research. In this context, we introduce a groundbreaking approach based on Hidden Markov Chain (HMC) modeling with opportunistic routing, harnessed by the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism. Our innovative algorithm addresses key challenges in Wireless Body Area Networks, including delay, throughput, and bandwidth utilization. By strategically integrating the HMC model, which captures intricate state transitions and emission probabilities, our proposed method introduces a robust solution for optimizing node connections and routing decisions. This fusion of HMC and opportunistic routing capitalizes on the strengths of both paradigms, enhancing the network's ability to make intelligent decisions in dynamic scenarios. Through rigorous simulations, we showcase the algorithm's prowess in achieving efficient data transmission. The empirical evidence from these simulations underscores the algorithm's superiority when juxtaposed against state-of-the-art mechanisms such as Simple Multi-Packet Access (SMPA) and Priority-based Congestion-avoidance Routing Protocol (PCRP). Our algorithm not only outperforms existing solutions in terms of delay, throughput, and bandwidth utilization, but it also showcases its ability to adapt to varying network conditions, making it a versatile tool for diverse applications.

A mechanics and electromagnetic scaling law for highly stretchable radio frequency electronics

Many classes of flexible and stretchable bio-integrated electronic systems rely on mechanically sensitive electromagnetic components, such as various forms of antennas for wireless communication and for harvesting energy through coupling with external power sources. This efficient wireless functionality can be important for body area network technologies and can enable operation without the weight and bulky size of batteries for power supply. Recently, antenna designs have received increased attention because their mechanical and electromagnetic properties significantly influence the wireless performance of bio-integrated electronics, particularly under excessive mechanical loads. These mechanical factors are critical for skin-integrated electronics during human motion, as complex skin deformations can damage the conductive traces of antennas, such as those used for near-field communication (NFC), leading to yield or fracture and affecting their electromagnetic stability. Serpentine interconnects have been proposed as a geometric alternative to in-plane circular or rectangular spiral antenna designs to improve the elastic stretchability of the metallic traces in NFC antennas and prevent mechanical fractures. Despite the use of serpentine interconnects within the physiologically relevant strain range for skin (<20 %), the electromagnetic stability of the antennas decreases. This instability, reflected by shifts in resonance frequency and scattering parameters due to inductance changes, reduces the antennas' wireless power transfer efficiency and readout range. Therefore, maintaining the electromagnetic stability of antennas, specifically NFC antennas, under various mechanical deformations has become a critical challenge in practical wireless skin-integrated applications, such as sensing and physiological monitoring. Here, we establish a new mechanics and electromagnetic scaling law that quantifies the inductance changes under strain in a rectangular-loop serpentine structure typically used for NFC wireless communication in stretchable electronics. We present a systematic analysis of the antenna's geometric parameters, material properties of the antenna and substrate, and the applied strain on the inductance change. Our findings demonstrate that the relative change of inductance is solely influenced by the serpentine structure's width-radius ratio, arc angle, aspect ratio of the NFC antennas, and the applied strain. Additionally, under physiological strain conditions for the skin, the relative change of inductance can be minimized to preserve the NFC antenna's performance and prevent mechanical fracture and electromagnetic stability loss.

UPDEMIN: an efficient protocol for predicting patient upcoming situation, decision and intervention in wireless body sensor network

UPDEMIN: an efficient protocol for predicting patient upcoming situation, decision and intervention in wireless body sensor network

Analysis of Weighting and Network Selection Methods for Vertical Handoff in Wireless Body Area Network

Analysis of Weighting and Network Selection Methods for Vertical Handoff in Wireless Body Area Network

Advancing Security in Lightweight S-WBSN for E-Healthcare

Wireless body sensor networks (WBSNs) are a critical component of e-healthcare, enabling continuous monitoring of vital signs and other health parameters. However, the limited capacity of WBSNs poses a significant challenge to securing data transmission. A novel architecture for Secure Wireless Body Sensor Networks (S-WBSN) has been introduced, focusing on efficiency and robust security. The S-WBSN architecture employs a combination of the OTP-Q stream block cipher and the Diffie-Hellman key exchange algorithm to ensure secure data transmission and mutual authentication between critical components. The OTP-Q algorithm encrypts data obtained from WBSN sensors, while the Diffie-Hellman algorithm establishes a secure communication channel between the WBSN, Local Processing Center (LPC), and Data Server. This innovative approach effectively meets essential security requirements, including mutual authentication and privacy preservation. It also demonstrates notable efficiency, consuming fewer CPU cycles than existing state-of-the-art security approaches. Comparative analysis showcases reduced processing time for encryption and decryption, making the S-WBSN architecture an attractive solution for e-healthcare data monitoring security. In summary, the S-WBSN architecture significantly enhances the security posture of e-healthcare data transfer, prioritizing efficiency, and robust protection. It sets itself apart from contemporary healthcare data monitoring security methodologies by delivering a comprehensive solution that addresses the unique challenges of WBSNs.

Optimal interference mitigation with deep learningbased channel access in wireless body area networks

SummaryWireless body area networks (WBANs) are essential for medical applications, especially in remote health monitoring, as they transmit crucial and time‐sensitive data collected by nodes positioned around or within the body. However, the coexistence of WBANs with wireless channels can degrade performance due to interference. This study introduces OIM‐DLCAM, an optimal interference mitigation scheme for WBANs, which utilizes a deep learning‐based channel access method. OIM‐DLCAM addresses interference through the multiobjective Hungarian optimization (MOHO) algorithm, considering design constraints such as node transmission power, packet delivery ratio, and interference range. Additionally, it employs a deep probabilistic neural network‐based channel access method (DPNN‐CAM) to effectively mitigate interference by making decisions regarding contention window size, frame length, and buffer size. The proposed OIM‐DLCAM scheme ensures fairness between users while enhancing system performance. Simulation results from both static and dynamic sensor node scenarios demonstrate its effectiveness under various conditions, showcasing its potential to improve WBAN performance in medical applications. The simulations reveal that OIM‐DLCAM outperforms existing state‐of‐the‐art schemes across various scenarios, with efficiency gains of up to 86.187%, 72.452%, and 47.954% for WBAN node density, mobility, and packet arrival rate, respectively. Moreover, it significantly reduces the average end‐to‐end delay and packet drop rate while improving throughput and packet delivery ratio compared with existing schemes. Additionally, comparisons with industry standards, such as the IEEE 802.15.4e norm, validate the suitability of OIM‐DLCAM for cofounded WBANs.