Search Results (333)

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

As an emerging information technology, Wireless Body Area Networks (WBANs) provide a lot of convenience for the development of the medical field. A WBAN is composed of many miniature sensor nodes in the form of an ad hoc network, which can realize remote medical monitoring. However, the data transmission between sensor nodes in the WBAN not only consumes the energy of the node but also causes the temperature of the node to rise, thereby causing human tissue damage. Therefore, in response to the energy consumption problem in the Wireless Body Area Network and the hot node problem in the transmission path, this paper proposes a temperature state awareness-based energy-saving routing protocol (TSAER). The protocol senses the temperature state of nodes and then calculates the data receiving probability of nodes in different temperature state intervals. A benefit function based on several parameters such as the residual energy of the node, the distance to sink, and the probability of receiving data was constructed. The neighbor node with the maximum benefit function was selected as the best forwarding node, and the data was forwarded. The simulation results show that compared with the existing M-ATTEPMT and iM-SIMPLE protocols, TSAER effectively prolongs the network lifetime and controls the formation of hot nodes in the network. 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

Air pollution is a major environmental and public health challenge, especially in urban areas where fine-grained air quality data are essential to effective interventions. Traditional monitoring networks, while accurate, often lack spatial resolution and public engagement. This study presents a novel wearable wireless sensor node (WSN) that was developed within the Horizon Europe SOCIO-BEE project to support air quality monitoring through citizen science (CS). The low-cost, body-mounted WSN measures NO₂, O₃, and PM_2.5. Three pilot campaigns were conducted in Ancona (Italy), Maroussi (Greece), and Zaragoza (Spain), and involved diverse user groups—seniors, commuters, and students, respectively. PM_2.5 sensor data were validated through two approaches: direct comparison with reference stations and spatial clustering analysis using K-means. The results show strong correlation with official PM_2.5 data (R² = 0.75), with an average absolute error of 0.54 µg/m³ and a statistical confidence interval of ±3.3 µg/m³. In Maroussi and Zaragoza, where no reference stations were available, the clustering approach yielded low intra-cluster coefficients of variation (CV = 0.50 ± 0.40 in Maroussi, CV = 0.28 ± 0.30 in Zaragoza), indicating that the measurements had high internal consistency and spatial homogeneity. Beyond technical validation, user engagement and perceptions were evaluated through pre-/post-campaign surveys. Across all pilots, over 70% of participants reported satisfaction with the system’s usability and inclusiveness. The findings demonstrate that wearable low-cost sensors, when supported by a structured engagement and data validation framework, can provide reliable, actionable air quality data, empowering citizens and informing evidence-based environmental policy. Full article

The parameters of electromagnetic emissions from the antenna of a wearable radio communication module (parameterizing device functionality) were investigated at different positions near the body where an antenna is located. The specific absorption rate (SAR) coefficient was also investigated as a way of parameterizing the absorption of electromagnetic radiation in the user’s body adjacent to the antenna in various locations. The modeled exposure scenarios concerned a body-worn device with a 2.45 GHz ISM band antenna (used, e.g., for Wi-Fi 2G/Bluetooth applications). The antennas were modeled as follows: (1) located directly on the body (considered to be a model of a disposable, adhesive device) or (2) next to the body (considered to be a model of a classic, reusable, wearable electronic device located inside a plastic housing). Several body sections adjacent to the antenna were considered: head, arm, forearm, and chest (simplified and anatomical body models were used). The numerical models of the exposure scenarios were verified by relevant laboratory tests using physical models. It was found that the use of simplified models of the human body (numerical or physical) may be sufficient when analyzing antenna performance and SAR in a user’s body, such as in studies regarding microwave imaging and sensing, wireless implantable devices, wireless body-area networks or SAR estimation. Full article

This paper presents a novel design of a compact dual-band dual-mode wearable antenna. The antenna is fed through a single coaxial feed probe, which excites TM₀₁ and TM₁₁ modes at 2.45 GHz and 5.8 GHz, respectively. These modes exhibit distinct radiation characteristics. The omnidirectional TM₀₁ mode at 2.45 GHz is suitable for on-body communication, while the directional TM₁₁ mode at 5.8 GHz is more appropriate for off-body communication. The antenna prototype was fabricated and measured. The measured performance is consistent with the simulations. Additionally, further simulations and measurements were conducted to verify the interactions between the proposed antenna and the human body. The results demonstrate that the proposed antenna exhibits significant potential as a candidate for wireless body area network (WBAN) communications. Full article

A circularly polarized (CP) textile antenna is investigated for concurrent on- and off-body wireless communications in the 2.38 GHz medical body area network and 5.8 GHz industrial, scientific, and medical bands in the wireless body area network. The proposed scheme consists of a square microstrip patch antenna (MPA), in which four shorting pins are employed to tune the two resonate modes of TM₁₀ and TM₀₀. Notably, the slant corners on MPA are cut symmetrically to realize unidirectional CP radiation, enabling off-body communication. Moreover, four rotating L-shaped parasite elements are loaded to excite the horizontal polarization mode (TM_hp), which is combined with the TM₀₀ mode to implement CP omnidirectional radiation along the human body. For verification, a proof-of-concept prototype with the dimensions of 45 mm × 45 mm × 2 mm was fabricated and characterized. The measured −10 dB impedance bandwidths of 2.5% and 6.7%, the 3 dB AR bandwidths of 2.5% and 2.7%, and the maximum realized gains of −2.8 and 6.8 dBic are achieved in dual bands, respectively. The experimental tests, such as human body loading, structural deformation, and humidity variation, were carried out. In addition, the wireless communication capability was measured and the radiation safety is evaluated. These performances show that the proposed antenna is an appropriate choice for multifunctional wearable applications. Full article

Mental health is an important aspect of an individual’s overall well-being. Positive mental health is correlated with enhanced cognitive function, emotional regulation, and motivation, which, in turn, foster increased productivity and personal growth. Accurate and interpretable predictions of mental disorders are crucial for effective intervention. This study develops a hybrid deep learning model, integrating CNN and BiLSTM applied to EEG data, to address this need. To conduct a comprehensive analysis of mental disorders, we propose a two-tiered classification strategy. The first tier classifies the main disorder categories, while the second tier classifies the specific disorders within each main disorder category to provide detailed insights into classifying mental disorder. The methodology incorporates techniques to handle missing data (kNN imputation), class imbalance (SMOTE), and high dimensionality (PCA). To enhance clinical trust and understanding, the model’s predictions are explained using local interpretable model-agnostic explanations (LIME). Baseline methods and the proposed CNN–BiLSTM model were implemented and evaluated at both classification tiers using PSD and FC features. On unseen test data, our proposed model demonstrated a 3–9% improvement in prediction accuracy for main disorders and a 4–6% improvement for specific disorders, compared to existing methods. This approach offers the potential for more reliable and explainable diagnostic tools for mental disorder prediction. Full article

Intrabody communication (IBC) establishes a wireless connection between devices in a Wireless Body Area Network (WBAN) by utilizing the human body as a transmission medium. The characteristics of the IBC channel are significantly influenced by the geometric and biological features of the human body and tissues. This paper analyzes a dataset with experimental real subjects’ data on signal loss in a galvanic IBC channel, models IBC identification using the K-Nearest Neighbors (KNN) algorithm, and proposes a novel IBC WBAN architecture incorporating an identification function. The analysis of the dataset revealed that the IBC channel gain exhibits a wide range of variations depending on individual human body characteristics such as height, weight, body mass index, and body composition. Consequently, biometric identification can be leveraged within the IBC WBAN paradigm. Through modeling IBC identification on cleaned and labeled data, we demonstrated an identification accuracy of 99.9% based on the results of our modeling. The proposed IBC WBAN architecture with an integrated identification function is anticipated to enhance the application scope and accelerate the development of IBC WBANs. Full article

Recent developments in sensors, wireless communications, and data processing technologies are the main drivers for adopting the Internet of Things (IoT) in healthcare systems. IoT-based healthcare systems can enhance the quality of life significantly and help prevent the occurrence of health problems and epidemics. Deploying IoT-based healthcare on a massive scale raises several issues and challenges. One of the main challenges is the management of the end-to-end network connections of the IoT-based healthcare system. This paper presents a comprehensive survey of smart network management protocols that improve IoT-based healthcare efficiency, ensuring real-time monitoring, secure data transmission, and effective device management. Moreover, a reference architecture has been proposed for the network management of IoT-based smart healthcare systems to ensure the sustainability of service delivery to patients and caregivers. The architecture avoids health-related risks and anomalies by incorporating proper network management techniques and operational requirements pertaining to smart healthcare systems. This paper also discusses architectural implementation insights supported by new technologies such as software-defined networking (SDN) and deep learning (DL). Finally, this paper explores emerging paradigms to advance next-generation network management protocols for future smart healthcare 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) are human-centric wireless networks, and implantable antennas represent a vital communication component within WBANs. The dielectric properties of human tissue are highly complex, with each layer exhibiting distinct dielectric constants that significantly influence the performance of implanted antennas. It is therefore imperative that a compact broadband implantable antenna be designed in order to address the instability in communication of medical implant devices. The antenna, coated in silicone, is a single-layer structure fed by a coaxial cable, with a volume of just 6 mm × 6 mm× 0.53 mm. A metallic patch is etched on the upper surface of the substrate, and the compact antenna design is enhanced with the introduction of S-shaped, F-shaped, and rectangular slots on the patch. The bottom side of the substrate is etched with rectangular ground planes, which broaden the impedance bandwidth of the antenna. The simulation results demonstrate that the antenna attains an impedance bandwidth of 23.8% (2.08–2.64 GHz), encompassing the entirety of the Industrial, Scientific, and Medical (ISM) band (2.4–2.48 GHz). In order to simulate the working environment of the antenna within the human body, physical tests were conducted on the antenna in pork tissue. The test results demonstrate that the antenna exhibits a measured bandwidth of 28% (2.3–3.03 GHz), with a radiation pattern that displays omnidirectional radiation characteristics. The antenna’s impedance matching and radiation characteristics remain essentially consistent in both bent and unbent states, indicating structural robustness. In comparison to other implantable antennas, this antenna displays a wider impedance bandwidth, a lower Specific Absorption Rate (SAR), and superior implant performance. 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 review provides a comprehensive analysis of the design, materials, fabrication techniques, and applications of flexible wearable antennas, with a primary focus on their roles in Wireless Body Area Networks (WBANs) and healthcare technologies. Wearable antennas are increasingly vital for applications that require seamless integration with the human body while maintaining optimal performance under deformation and environmental stress. Return loss, gain, bandwidth, efficiency, and the SAR are some of the most important parameters that define the performance of an antenna. Their interactions with human tissues are also studied in greater detail. Such studies are essential to ensure that wearable and body-centric communication systems perform optimally, remain safe, and are in compliance with regulatory standards. Advanced materials, including textiles, polymers, and conductive composites, are analyzed for their electromagnetic properties and mechanical resilience. This study also explores innovative fabrication techniques, such as inkjet printing, screen printing, and embroidery, which enable scalable and cost-effective production. Additionally, solutions for SAR optimization, including the use of metamaterials, electromagnetic band gap (EBG) structures, and frequency-selective surfaces (FSSs), are discussed. This review highlights the transformative potential of wearable antennas in healthcare, the IoT, and next-generation communication systems, emphasizing their adaptability for real-time monitoring and advanced wireless technologies, such as 5G and 6G. The integration of energy harvesting, biocompatible materials, and sustainable manufacturing processes is identified as a future direction, paving the way for wearable antennas to become integral to the evolution of smart healthcare and connected systems. 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