Body Area Networks Research Articles

Secure Data Aggregation and Transmission System for Wireless Body Area Networks Using Twofish Symmetric Key Generation

Nowadays, Wireless Body Area Networks (WBANs) are mostly used in the healthcare industry. They represent a portable, inexpensive network that exhibition adaptability. The data developed using WBAN devices is vulnerable to transmission-related internal and external attacks; nevertheless, this vulnerability arises due to resource restrictions; by employing data aggregation technologies to conduct statistical analyses of medical data while protecting patient privacy, medical professionals can enhance the precision of diagnoses and assist medical insurance firms in selecting optimal plans for their clients. Maintaining the confidentiality and integrity of sensitive health information becomes more stimulating at the stages of aggregation and transmission due to security issues. This study proposes a novel method, Twofish Symmetric Key Generation (TFSKG), combined into a Secure Data Aggregation (SDA) and transmission system intended for WBANs. The Twofish technique is animatedly employed to make the secure symmetric keys chosen for its robust encryption capabilities. These keys are used to encrypt and decrypt aggregated health data through transmission. The proposed TFSKG-SDA method implements effective algorithms for aggregating data to safeguard end-to-end privacy and preserve data accuracy while reducing bandwidth consumption. Thus, for improved performance, an innovative genetic algorithm for data security is presented in this study. This paper introduces TFSKG-SDA, a system that, by employing rigorous simulation testing, enhances security protocols, resistance against recognized threats, and data transmission efficacy in the context of resource-constrained WBANs. We assess the encryption strength, computational cost, and communication efficiency of the TFSKG- SDA method to prove its significance to real-world healthcare applications.

Copper Paste Printed Paper‐Based Dual‐Band Antenna for Wearable Wireless Electronics

AbstractWearable wireless electronics is becoming a significant research area because of the unique features of this technology. Within this field printed antennas are the key electrical component accomplishing the signal transmission and energy harvesting tasks and at the same these antennas need to be lightweight, environmentally friendly, safe to wear, and easy to conform. Currently, the majority of available paper‐based antennas are designed for RFID, sensing, UWB, WLAN, and medical applications, with just a few being utilized in wearable applications, particularly for wireless body area network (WBAN). Furthermore, few studies have been conducted on the usage of printable copper conductive materials and low‐temperature plasma technique for the fabrication of such antennas. This study demonstrates the realization of a dual‐band paper‐based wearable antenna by screen‐printing of a plasma‐sintered conductive copper paste. The copper paste, composed of 51 wt% solid particles, can easily produce desired conductive patterns on photo paper after printing and a subsequent plasma sintering, with a good adhesion. The antenna designed on photopaper operates in the frequency bands of 1.73–2.55 GHz and 7.66–8.89 GHz. Free‐space simulation and measurement results reveal that the antenna exhibits stable radiation performance in the targeted WBAN (2.4–2.4835 GHz) and X uplink (7.9–8.4 GHz) frequency bands, together with low profile, excellent conformality and acceptable SAR values on the body and no electronic waste formed after disposal, making it a competitive candidate for usage in wearable wireless electronics.

Optimizing relay node selection in cooperative wireless body area networks with modified POA

In the realm of Wireless Body Area Networks (WBANs), cooperative communications emerge as a crucial research focus, lauded for their capacity to mitigate fading and optimize spectral efficiency. Choosing the appropriate relay in cooperative communication is vital for ensuring spatial diversity, as incorrect relay selections can lower the network's overall performance. This study utilizes an optimization method referred to as M-POA(Modified Pelican Optimization Algorithm) to tackle the relay selection problem. This paper introduces a M-POA specifically designed for cooperative networks in Wireless Body Area Networks (WBAN). The core concept behind the M-POA is to mimic the hunting behavior of pelicans in nature. Here, the relay selection is determined using the M-POA, with channel gain as a fitness function. The proposed strategy integrates the Decode-and-Forward (DF) relay protocol to significantly enhance communication efficiency and reliability. The proposed method is assessed in comparison with other relay selection techniques through a Bit Error Rate (BER) analysis, evaluating the effectiveness of each approach across different Signal-to-Noise Ratio (SNR) scenarios. The simulation results analysis elucidates that M-POA provides well-balanced performance in both exploration and exploitation aspects. By calculating the Bit Error Rate (BER), we assessed the effectiveness of the optimized relay selection strategy, with the objective of minimizing BER to enhance overall communication reliability. By studying the convergence curve, we evaluated the relay selection technique's performance and gauged how effectively it improved with each iteration. The proposed scheme effectively addresses both key requirements of WBAN: improving communication system reliability and optimizing relay selection.

Radiation analysis of optimized wearable antenna sensor at 2.4GHz on human body for Wireless Body Area Network Applications

Radiation analysis of optimized wearable antenna sensor at 2.4GHz on human body for Wireless Body Area Network Applications

Elderly care and health monitoring using smart healthcare technology: An improved routing scheme for wireless body area networks

AbstractHypertensive patients need regular checkups and constant monitoring for taking time critical decisions by the medical experts. Unfortunately, it is hard to maintain uninterrupted patient health surveillance due to limited medical staff resulting in an increasing mortality rate annually. Thanks to recent developments in wireless sensor networking, we can monitor constantly and efficiently diverse parameters of a network. Similarly, Wireless Body Area Networks (WBANs) have become a well‐known sub‐branch of Wireless Sensor Networks. Such sensor networks can be leveraged for patient health monitoring, minimising the medical staff workload. Wireless Body Area Networks require tiny sensor nodes with limited battery power. Therefore, it is always desirable to design effective routing schemes that can enhance network lifetime, and reduce packet drop ratio. In this paper, we re‐simulate and explain in detail the results of a selected published journal article for WBANs and provide some modifications to improve the network's overall performance. Based on these amendments, the modified protocol successfully extends the operational time of the network than the original. Our performance evaluation parameters are dead nodes, throughput, residual energy, and path loss versus the number of rounds. These analyses support effective solutions that improve network performance and data delivery ratio.

Modeling and simulation of Fuzzy-rule based WBAN using multi-level fuzzy colored petri-nets and reinforcement learning

By developing IoTs (Internet of Things), a new concept is arising in WBANs (Wireless Body Area Networks), called IoBs (Internet of Bodies). WBANs are the safety-critical devices that use rule-based knowledge with fuzzy variables for monitoring patients. There are two issues with the knowledgebase: (1) appropriate knowledge representation and inference and (2) handling the situations for which there is no rule in the knowledgebase. In this paper, for the first issue we present MFCPN (Multi-level Fuzzy Colored Petri-nets) and for the second one we present a RL (Reinforcement Learning) mechanism for decision making based on the past device’s feedback to the environment. Through a few scenarios and two datasets, the proposed approach has been applied to pacemakers to show the approach's effectiveness. The comparison between decision making by our approach and two real datasets indicates the proposed approach has 79.3 % accuracy.

Investigation of optically transparent metasurfaces for gain improvement of an ultrawideband antenna for wireless body area networks and vehicular communications

Abstract Due to higher frequencies which cause signal deterioration, 5G enabled antennas are prone to substantial attenuation. To circumvent this problem, several access points, signal repeaters, and base stations must be installed closer together on building windows, streetlights, and other infrastructure. Optically transparent antennas preserve the aesthetics of the windows by offering the requirements for access points and base stations for providing network connectivity to the cars and pedestrians passing by those buildings. Here we report an ultrawideband (UWB) high gain optically transparent antenna operating from 4-12 GHz. Indium tin oxide (ITO) coated glass has been used as an optically transparent substrate for designing the antenna and metasurface. Two optically transparent metasurfaces have been proposed for band-stop filtering action across the UWB frequency range 4-12 GHz. In absence of the metasurface, the antenna operates in the frequency band ranging from 3.8 to 15 GHz. Average gain enhancement is 5.2 dB with radiation efficiency higher than 93% across the UWB frequency band from 4-12 GHz. Numerical simulations have been carried out for analysis of the proposed antenna and metasurfaces. These simulations have been validated by experimental measurements of the fabricated prototypes.

Retraction Note: Design and evaluation of novel hybrid quantum resistant cryptographic system for enhancing security in wireless body sensor networks

Retraction Note: Design and evaluation of novel hybrid quantum resistant cryptographic system for enhancing security in wireless body sensor networks

Secured Fog-Body-Torrent : A Hybrid Symmetric Cryptography with Multi-layer Feed Forward Networks Tuned Chaotic Maps for Physiological Data Transmission in Fog-BAN Environment

Recently, the Wireless Body Area Networks (WBAN) have become a promising and practical option in the tele-care medicine information system that aids for the better clinical monitoring and diagnosis. The trend of using Internet of Things (IoT) has propelled the WBAN technology to new dimension in terms of its network characteristics and efficient data transmission. However, these networks demand the strong authentication protocol to enhance the confidentiality, integrity, recoverability and dependability against the emerging cyber-physical attacks owing to the exposure of the IoT ecosystem and the confidentiality of biometric data. Hence this study proposes the Fog based WBAN infrastructure which incorporates the hybrid symmetric cryptography schemes with the chaotic maps and feed forward networks to achieve the physiological data info security without consuming the characteristics of power hungry WBAN devices. In the proposed model, scroll chaotic maps are iterated to produce the high dynamic keys streams for the real time applications and feed-forward layers are leveraged to align the complex input-output associations of cipher data for subsequent mathematical tasks. The feed forward layers are constructed which relies on the principle of Adaptive Extreme Learning Machines (AELM) thereby increasing randomness in the cipher keys thereby increasing its defensive nature against the different cyber-physical attacks and ensuring the high secured encrypted-decrypted data communication between the users and fog nodes. The real time analysis is conducted during live scenarios. BAN-IoT test beds interfaced with the heterogeneous healthcare sensors and various security metrics are analysed and compared with the various residing cryptographic algorithms. Results demonstrates that the recommended methodology has exhibited the high randomness characteristics and low computational overhead compared with the other traditional BAN oriented cryptography protocol schemes

A Survey on Data-Driven Approaches for Reliability, Robustness, and Energy Efficiency in Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are pivotal in health care and wearable technologies, enabling seamless communication between miniature sensors and devices on or within the human body. These biosensors capture critical physiological parameters, ranging from body temperature and blood oxygen levels to real-time electrocardiogram readings. However, WBANs face significant challenges during and after deployment, including energy conservation, security, reliability, and failure vulnerability. Sensor nodes, which are often battery-operated, expend considerable energy during sensing and transmission due to inherent spatiotemporal patterns in biomedical data streams. This paper provides a comprehensive survey of data-driven approaches that address these challenges, focusing on device placement and routing, sampling rate calibration, and the application of machine learning (ML) and statistical learning techniques to enhance network performance. Additionally, we validate three existing models (statistical, ML, and coding-based models) using two real datasets, namely the MIMIC clinical database and biomarkers collected from six subjects with a prototype biosensing device developed by our team. Our findings offer insights into strategies for optimizing energy efficiency while ensuring security and reliability in WBANs. We conclude by outlining future directions to leverage approaches to meet the evolving demands of healthcare applications.

Modeling and analysis of propagation characteristics of WBAN in hospital ward scenarios

AbstractTo explore the feasibility of high‐frequency indoor wireless body area network (WBAN) communications, the propagation characteristics of WBAN in simulated hospital ward scenarios at 11 GHz are studied. Based on the extensive measured data, the impact of the patient's lying angle (LA) on channel characteristics has been analyzed, such as statistical characteristics of path loss (PL), shadowing effect, and root mean square delay spread. Moreover, a PL model with LA factor is presented for the hospital ward scene, and the influence of LA on PL in the presence of height difference is also analyzed. The research results indicate that, the PL caused by LA (abbreviated as PLA) follows a power function with respect to the LA in case of a fixed distance between the transmitter and receiver. When the LA is fixed, PLA exhibits a cubic function relationship with the distance between the transmitter and receiver. In addition, the presence of patient's LA can cause more significant multipath effect. However, the impact of LA gradually weakens as the height difference increases when there is a height difference. The research results provide a theoretical basis and practical basis for utilizing the 11 GHz frequency band in indoor WBAN in the future.

A TECHNIQUE TO SECURE DATA TRANSMISSION IN WIRELESS BODY AREA NETWORKS

The wireless body area networks have contributed to the changes in healthcare sector by enabling continuous monitoring of biomedical parameters remotely on the patient body and offering real time data transmission. Upon collection of the vital signs, they are transmitted to the gateway node which then forwards them to the remote hospital medical servers. Here, these physiological data items are analyzed and necessary action is taken. Such physiological data include electrocardiograms (ECGs), blood pressure, body temperature, blood oxygen levels, respiratory rate, Electroencephalogram (EEG), Electromyogram (EMG), glucose levels, physical activity and Electrodermal Activity (EDA). In this paper, we develop a technique for securely transmitting this sensitive data from the body sensor unit (BSU) to the remote hospital medical server (HMS). KEYWORDS: Sensors, BSU, WBAN, security, privacy

Performance Optimization and Link Reliability in Wireless Body Area Networks

Long-lasting connectivity and energy-efficient systems are needed for wireless body area networks (WBANs). In addition to the growing commercialization of WBANs, health monitoring applications demand improved quality of service (QoS). For WBAN performance characteristics to improve, it is essential to develop a dependable and energy-efficient link. We provide a cross-layer routing strategy for improving WBAN quality of service in this study. This method employs a cost function that linearly combines the individual absorption rate functions, node energy ratio, and link dependability. This research investigates how the performance of the network varies depending on the parameter combinations used and the size of the contention window, and we use parametric modelling of the cost function. While the development of the QoS focuses on enhancing the packet delivery success rate and network throughput for applications of WBANs, the suggested algorithm primarily increases network lifetime durability by decreasing the node energy consumption with acceptable throughput. WBAN performance optimization criteria using advanced particle swarm optimization (APSO) are proposed in this research to emphasize increasing energy economy, decreasing end-to-end delay and increasing network throughput in various existing methods. The number of live nodes for the proposed method is higher than those of the PSO-LSMR, M-ATTEMPT and EERP. The value of First Node Died is 6301. The value of residual energy, 34.7 J, is also higher for the proposed method than for the compared state-of-the-art algorithms.

Low SAR Based Modified Circular Patch Antenna for Future Biomedical Applications and Body Area Networks

Low SAR Based Modified Circular Patch Antenna for Future Biomedical Applications and Body Area Networks

An Adaptive Reinforcement Learning-Based Mobility-Aware Routing for Heterogeneous Wireless Body Area Networks

An Adaptive Reinforcement Learning-Based Mobility-Aware Routing for Heterogeneous Wireless Body Area Networks

Knowledge Transfer for Body Sensor Networks: Characterization and Resistance of Negative Transfer in Overconstrained Environments

Knowledge Transfer for Body Sensor Networks: Characterization and Resistance of Negative Transfer in Overconstrained Environments

Energy efficient and reliable data transmission in WBAN using multivariate gradient divergence African buffalo optimization

SummaryWireless body area network (WBAN), a popular radio communication technique, tracks patients' health conditions remotely using small, low‐power, portable sensors positioned on the body to sense vital signs and send data to a control node. To sustain long‐term health monitoring, WBANs require significant energy from the nodes. This research proposes an energy efficient and reliable data transmission using multivariate gradient divergence African buffalo optimization (EEMGDABO) to minimize the delay of critical node data transmission by identifying the optimal path to the control node. The protocol comprises two key processes: winsorized correlative segmented symbolic regression with reinforcement learning (WCS‐SRRL) and the walrus optimization algorithm (WaOA) for accurate priority‐based classification of health data (normal, abnormal, and critical). The second process involves transferring these priority‐based data with reduced energy consumption and delay while increasing throughput by determining the best path from the critical node to the destination (hospital/doctor) using EEMGDABO, which calculates node distance and energy fitness value. Implemented in MATLAB with a health monitoring WBAN dataset, the proposed protocol demonstrates 23% less energy consumption, 12.33% less delay, and 23.44% higher network lifetime compared to existing optimization approaches.

Investigating the impact of body node coordinator position on communication reliability in wireless body area networks

Investigating the impact of body node coordinator position on communication reliability in wireless body area networks

MEDCO: an efficient protocol for data compression in wireless body sensor network

MEDCO: an efficient protocol for data compression in wireless body sensor network

Efficient data transmission mechanisms in energy harvesting wireless body area networks: A survey

Efficient data transmission mechanisms in energy harvesting wireless body area networks: A survey