Search Results (92)

The endoscopic capsule is a miniaturized device used for medical diagnosis, which is less invasive compared to traditional gastrointestinal endoscopy and can reduce patient discomfort. However, it faces challenges in communication transmission, such as high power consumption, serious signal interference, and low data transmission rate. To address these issues, this paper proposes an optimized modulation scheme that is low-cost, low-power, and robust in harsh environments, aiming to improve its transmission rate. The scheme is analyzed in terms of the in-body channel. The analysis and discussion for the scheme in wireless body area networks (WBANs) are divided into three aspects: bit error rate (BER) performance, energy efficiency (EE), and spectrum efficiency (SE), and complexity. These correspond to the following issues: transmission rate, communication quality, and low power consumption. The results demonstrate that the optimized scheme is more suitable for improving the communication performance of endoscopic capsules. Full article

The increasing demand for sustainable and renewable energy solutions has made radio frequency energy harvesting (RFEH) a promising technique for powering low-power electronic devices. RFEH captures ambient RF signals from wireless communication systems, such as mobile networks, Wi-Fi, and broadcasting stations, and converts them into usable electrical energy. This approach offers a viable alternative for battery-dependent and hard-to-recharge applications, including streetlights, outdoor night/security lighting, wireless sensor networks, and biomedical body sensor networks. This article provides a comprehensive review of the RFEH techniques, including state-of-the-art rectenna designs, energy conversion efficiency improvements, and multi-band harvesting systems. We present a detailed analysis of recent advancements in RFEH circuits, impedance matching techniques, and integration with emerging technologies such as the Internet of Things (IoT), 5G, and wireless power transfer (WPT). Additionally, this review identifies existing challenges, including low conversion efficiency, unpredictable energy availability, and design limitations for small-scale and embedded systems. A critical assessment of current research gaps is provided, highlighting areas where further development is required to enhance performance and scalability. Finally, constructive recommendations for future opportunities in RFEH are discussed, focusing on advanced materials, AI-driven adaptive harvesting systems, hybrid energy-harvesting techniques, and novel antenna–rectifier architectures. The insights from this study will serve as a valuable resource for researchers and engineers working towards the realization of self-sustaining, battery-free electronic systems. Full article

The development of wearable sensor devices brings significant benefits to patients by offering real-time healthcare via wireless body area networks (WBANs). These wearable devices have gained significant traction due to advantageous features, including their lightweight nature, comfortable feel, stretchability, flexibility, low power consumption, and cost-effectiveness. Wearable devices play a pivotal role in healthcare, defence, sports, health monitoring, disease detection, and subject tracking. However, the irregular nature of the human body poses a significant challenge in the design of such wearable systems. This manuscript provides a comprehensive review of recent advancements in wearable and flexible smart sensor devices that can support the next generation of such sensor devices. Further, the development of direct ink writing (DIW) and direct writing (DW) methods has revolutionised new high-resolution integrated smart structures, enabling the design of next-generation soft, flexible, and stretchable wearable sensor devices. Recognising the importance of keeping academia and industry informed about cutting-edge technology and time-efficient fabrication tools, this manuscript also provides a thorough overview of the latest progress in various fabrication methods for wearable sensor devices utilised in WBAN and their evaluation using body phantoms. An overview of emerging challenges and future research directions is also discussed in the conclusion. Full article

Wireless body area networks (WBANs) have great potential to supply society with vital technical services, but the low power of network nodes severely hampers their development. To solve this problem, Energy-Efficient, a low-power cluster-based routing system intended for precise biological data gathering in WBANs, is presented in this study. This approach comprises three main stages: data aggregation, cluster head (CH) selection, and cluster creation. The suggested approach balances biosensor energy and optimizes energy usage by utilizing the modified snake swarm optimization algorithm (MSSOA) for routing and the adaptive binary bird swarm optimization algorithm (ABBSOA) for cluster formation and CH selection. The suggested technique outperforms the most recent WBAN routing protocols, including MT-MAC, ALOC, DHCO, and M-GWO, by using a power-balancing routing tree and considering biosensor distance and remaining energy. The experimental results demonstrate that the proposed ABBSOA-MSSOA model achieves a jitter protocol value of 0.3 ms at 100 nodes, a buffer occupancy ratio of 2.5%, a cluster lifetime of 600 s, a cluster building time of 12.2 s, an energy consumption of 42 mJ, a communication overhead of 8.3%, a packet delivery ratio of 98.2%, and an average end-to-end delay of 25 ms compared to other existing methods. Full article

This paper describes an all-digital clock and data recovery (CDR) circuit for implementing edge processing with a wireless body area network (WBAN). The CDR circuit performs delay-locked loop (DLL)-based and phase-locked loop (PLL)-based operations depending on the use of an external reference clock and is implemented using a digital method that is robust against external noise. The clock generator circuit shared by the two operation methods is described in detail, and the CDR circuit recovers 42 Mb/s input data and a 42 MHz clock, which are the specifications of human body communication (HBC). In DLL-based CDR operation, the clock generator operates as a digitally controlled delay line (DCDL) that delays the reference clock by more than one period. In PLL-based CDR operations, it operates as a digitally controlled oscillator (DCO) that oscillates the 42 MHz clock and adjusts the clock frequency. The proposed all-digital CDR is fabricated in 65 nm CMOS technology with an area of 0.091 mm² and operates with a supply voltage of 1.0 V. Post-layout simulation results show that the lock time for DLL-based CDR operation is 1.6 μs, the clock peak-to-peak jitter is 0.38 ns, and the power consumption is 341.8 μW. For PLL-based CDR operations, the lock time is 6 μs, the clock peak-to-peak jitter is 2.92 ns, and the power consumption is 280.2 μW, respectively. Full article

Wireless body area networks (WBANs), which continually gather and transmit patient health data in real time, are essential for improving healthcare administration. Patient outcomes can be improved by sending these data to medical professionals for prompt review and treatment. For the effective deployment of WBANs, communication solutions are necessary to maximize critical performance parameters, such as low power consumption, minimal delay, and acceptable data rates, while guaranteeing dependable transmission. Two prominent technologies in this field are LoRaWAN, which is renowned for its long-range capabilities and energy efficiency, and IEEE 802.15.6, which was created especially for short-range medical applications with high data throughput. This study provides a comparative evaluation of these two technologies to determine their suitability for diverse WBAN healthcare scenarios. By using the NS3, a simulation was performed to calculate six key performance metrics: throughput, arrival rate, delay, energy consumption, packet delivery ratio (PDR), and network lifetime. The study analyzed each technology’s performance under varying node counts. At a density of 50 nodes, IEEE 802.15.6 demonstrated superior throughput, with 45 kbps, compared to LoRaWAN, and a higher PDR of 30%. Additionally, IEEE 802.15.6 showed a higher arrival rate, of 0.33%, than LoRaWAN. On the other hand, LoRaWAN showed notable strengths in energy consumption, with only 42 J, compared to IEEE 802.15.6, and significantly lower delay, with a delay of 7 s. Additionally, LoRaWAN offered an extended network lifetime, of 18 h, compared to IEEE 802.15.6. Full article

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data. Full article

Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and transmission of vital physiological data. However, the energy constraints of the battery-powered sensor nodes in WBANs pose a significant challenge to ensuring long-term operational efficiency. Two-hop routing protocols have been suggested to extend the stability period and maximize the network’s lifetime. These protocols select appropriate parent nodes or forwarders with a maximum of two hops to relay data from sensor nodes to the sink. While numerous energy-efficient routing solutions have been proposed for WBANs, reliability has often been overlooked. Our paper introduces an energy-efficient routing protocol called a Hybrid Clustering Approach for Extending WBAN Lifetime (HCEL) to address these limitations. HCEL leverages a utility function to select parent nodes based on residual energy (RE), proximity to the sink node, and the received signal strength indicator (RSSI). The parent node selection process also incorporates an energy threshold value and a constrained number of serving nodes. The main goal is to extend the overall lifetime of all nodes within the network. Through extensive simulations, the study shows that HCEL outperforms both Stable Increased Throughput Multihop Protocol for Link Efficiency (SIMPLE) and Energy-Efficient Reliable Routing Scheme (ERRS) protocols in several key performance metrics. The specific findings of our article highlight the superior performance of HCEL in terms of increased network stability, extended network lifetime, reduced energy consumption, improved data throughput, minimized delays, and improved link reliability. Full article

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz must provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT). They must also be fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide P_OUT range of from 12.1 to −31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm P_OUT. The calibrated HD2 level is −82.2 dBc at 9.93 dBm P_OUT, resulting in a transmitter figure of merit (TX_FoM) of −97.52 dB. Higher-order harmonic levels remain below −41.2 dBm even at 12.1 dBm P_OUT, meeting regulatory requirements. Full article

Ultra-wideband (UWB) antennas cover a frequency range of 3.1 to 10.6 GHz and have sparked a lot of research interest as an essential part of wireless communication systems as they provide high data transmission speeds, are less expensive, and consume less power. UWB antennas are widely used in radar imaging, radio frequency identification, public security, and other high-accuracy positioning devices such as altimetry. Some smart applications of UWB antennas are vehicular radar systems, surveillance systems, software-defined radios, spectrum analysis, proximity fuses, etc. Multiple-input-multiple-output (MIMO) is a multiplexing technology that adopts multiple antennas both at the transmitter and receiver, which can enhance the channel capacity. MIMO technology is extensively used in several applications, such as in portable devices, wireless body area networks (WBANs), vehicular communication, and satellite–terrestrial networks. Generally, the MIMO antennas are used to obtain high reliability, high capacity, high throughput, and high security. The UWB MIMO antennas (UMAs) are considered the best choice for wireless communication systems as they offer reliability and wide transmission capacity, in contrast to unit antenna elements (AEs), without increasing system bandwidth or transmission power. The present-day and future communications systems need higher throughput to meet the demands of users. The signal transfer rate can be improved by improving channel bandwidth or increasing the number of receiving antennas. However, the main issue in designing UMAs is to provide high isolation between AEs because mutual coupling interactions between them affect the generated radiation patterns, leading to worse performance and failing to meet the operative constraints and requirements. When introducing decoupling techniques (DTs), researchers experience numerous challenges, including an increase in antenna size, design complexity, and cross-polarization. This article offers an organized review and simulated study of the various DTs in UMAs. The simulated study has been carried out through the implementation of various types of DTs on the same two-port UMA, which consists of two microstrip-fed circular-shaped AEs with open-end slotted partial ground. In contrast with previously reported review articles, this article provides a detailed study of various types of DTs reported so far and a better understanding for selecting appropriate DTs, which help in designing UMAs with better performance. Full article

Wireless body area network (WBAN) is an emerging comprehensive technology that can deeply integrate with e-health and smart sports. As a wearable network, improving the quality of network service and user experience is crucial. Due to the miniaturized design of sensors, their available energy from batteries is limited, making the extension of their lifetime a key research challenge. Existing studies have proposed methods to improve energy efficiency, but there are still limitations in addressing dynamic adaptive aspects of differential energy distribution and channel conditions. In order to further extend the lifetime of sensor nodes and networks while ensuring quality of service, and to provide a reliable transmission mechanism for heterogeneous application data, this paper presents a cross-layer optimized MAC protocol mechanism. The protocol takes into account the transmission requirements of different types of data and redesigns the superframe. To improve the lifetime of nodes, we propose an energy-adaptive adjustment mechanism considering the channel conditions. At the same time, a cooperative transmission mechanism is proposed to further enhance network lifetime. In experiments conducted on two typical networks, compared to IEEE 802.15.6, the power adjustment scheme improves the network lifetime by 2.8 to 3.7 times, and the cooperative mechanism between nodes further increases the network lifetime by 17% to 44%. Our proposed scheme effectively extends the network lifetime while ensuring quality of service, avoiding frequent battery resets for users, and effectively improving the user experience quality. Full article

Wireless Body Area Network (WBAN) plays an important role in e-health, sports training, and entertainment to monitor human bodies wirelessly and remotely. One critical challenge for WBAN is to guarantee the quality of user experience and improve the network performance within such a resource-constrained and dynamic network. In the proposed paper, we investigate a cooperative radio frequency energy harvesting-based WBAN. Herein, we primarily focus on improving the energy efficiency and network performance through intelligent cooperation among nodes, allowing sensors with sufficient energy to assist other sensors in data uploading. We propose a relay selection method that considers both energy demand and energy harvest efficiency. Each sensor calculates the transmission power threshold required for data uploading based on the perceived channel state and determines whether it can act as a potential relay node in conjunction with its own energy harvest efficiency. The coordinator is responsible for optimizing collaborative transmission plans based on real-time network status. Experimental results show that the cooperative scheme performs better than the common single-hop scheme in terms of packet reception rate and packet arrival rate. In a network consisting of 10 sensors, the increase in packet reception rate ranges from 4.9% to 7.8% when the sensors are placed in preset fixed positions. When the sensors are randomly placed, the increase in packet reception rate ranges from 0.9% to 7.9% and from 0.7% to 7.4%, corresponding to $\delta$ values of 0.7 and 0.9, respectively. Full article

Determining the amount of electromagnetic wave energy absorbed by the human body is an important issue in the analysis of wireless systems. Typically, numerical methods based on Maxwell’s equations and numerical models of the body are used for this purpose. This approach is time-consuming, especially in the case of high frequencies, for which a fine discretization of the model should be used. In this paper, the surrogate model of electromagnetic wave absorption in human body, utilizing Deep-Learning, is proposed. In particular, a family of data from finite-difference time-domain analyses makes it possible to train a Convolutional Neural Network (CNN), in view of recovering the average and maximum power density in the cross-section region of the human head at the frequency of 3.5 GHz. The developed method allows for quick determination of the average and maximum power density for the area of the entire head and eyeball areas. The results obtained in this way are similar to those obtained by the method based on Maxwell’s equations. Full article

Internet of things (IoT)-enabled wireless body area network (WBAN) is an emerging technology that combines medical devices, wireless devices, and non-medical devices for healthcare management applications. Speech emotion recognition (SER) is an active research field in the healthcare domain and machine learning. It is a technique that can be used to automatically identify speakers’ emotions from their speech. However, the SER system, especially in the healthcare domain, is confronted with a few challenges. For example, low prediction accuracy, high computational complexity, delay in real-time prediction, and how to identify appropriate features from speech. Motivated by these research gaps, we proposed an emotion-aware IoT-enabled WBAN system within the healthcare framework where data processing and long-range data transmissions are performed by an edge AI system for real-time prediction of patients’ speech emotions as well as to capture the changes in emotions before and after treatment. Additionally, we investigated the effectiveness of different machine learning and deep learning algorithms in terms of performance classification, feature extraction methods, and normalization methods. We developed a hybrid deep learning model, i.e., convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), and a regularized CNN model. We combined the models with different optimization strategies and regularization techniques to improve the prediction accuracy, reduce generalization error, and reduce the computational complexity of the neural networks in terms of their computational time, power, and space. Different experiments were performed to check the efficiency and effectiveness of the proposed machine learning and deep learning algorithms. The proposed models are compared with a related existing model for evaluation and validation using standard performance metrics such as prediction accuracy, precision, recall, F1 score, confusion matrix, and the differences between the actual and predicted values. The experimental results proved that one of the proposed models outperformed the existing model with an accuracy of about 98%. Full article

In the wireless body area network (WBAN), radio propagations from devices that communicate with the human body are very complex and distinctive compared to other environments. As we know, the human body is a lossy channel that significantly attenuates the propagation of electromagnetic waves (EMW). Therefore, channel models are critical in evaluating the communication link. One of the most predominant models is the path loss channel model, which is used to cover a wide range of communication channels and frequency bands in WBAN. This paper investigates the EMW in a human model irradiated by an incident electromagnetic plane wave. A planar multilayer structure is used for modeling human tissue. Moreover, the steady-state electromagnetic distribution is calculated by solving the differential and integral equations (DIE) by using the method of moments (MoM). The obtained results demonstrate the great use of performing a theoretical analysis for path loss (PL) and power loss density (PLD) estimation. The magnitude of the electric field inside muscle tissue at various depths, and with the most important frequencies in medical applications, is evaluated. This investigation provides evidence that the penetration of EMW in biological tissue strongly depends on the frequency and thickness of the tissue involved. Thus, for different examined conditions, an excellent agreement between recent results that were obtained by an analytical method, finite element (FEM), and the proposed MoM method is verified to be valid in this investigation, and it is found that the distribution of the field, PL, and PLD for different communication scenarios is very promising to determine the quality of communication for WBAN technology. Full article