A comprehensive survey of wireless body area networks on PHY, MAC, and network layers solutions

Recent advances in microelectronics and integrated circuits, system-on-chip design, wireless communication and intelligent low-power sensors have allowed the realization of a Wireless Body Area Network (WBAN). A WBAN is a collection of low-power, miniaturized, invasive/non-invasive lightweight wireless sensor nodes that monitor the human body functions and the surrounding environment. In addition, it supports a number of innovative and interesting applications such as ubiquitous healthcare, entertainment, interactive gaming, and military applications. In this paper, the fundamental mechanisms of WBAN including architecture and topology, wireless implant communication, low-power Medium Access Control (MAC) and routing protocols are reviewed. A comprehensive study of the proposed technologies for WBAN at Physical (PHY), MAC, and Network layers is presented and many useful solutions are discussed for each layer. Finally, numerous WBAN applications are highlighted

Particle Swarm Optimization for Interference Mitigation of Wireless Body Area Network: A Systematic Review

Wireless body area networks (WBAN) has now become an important technology in supporting services in the health sector and several other fields. Various surveys and research have been carried out massively on the use of swarm intelligent (SI) algorithms in various fields in the last ten years, but the use of SI in wireless body area networks (WBAN) in the last five years has not seen any significant progress. The aim of this research is to clarify and convince as well as to propose a answer to this problem, we have identified opportunities and topic trends using the particle swarm optimization (PSO) procedure as one of the swarm intelligence for optimizing wireless body area network interference mitigation performance. In this research, we analyzes primary studies collected using predefined exploration strings on online databases with the help of Publish or Perish and by the preferred reporting items for systematic reviews and meta-analysis (PRISMA) way. Articles were carefully selected for further analysis. It was found that very few researchers included optimization methods for swarm intelligence, especially PSO, in mitigating wireless body area network interference, whether for intra, inter, or cross-WBAN interference. This paper contributes to identifying the gap in using PSO for WBAN interference and also offers opportunities for using PSO both standalone and hybrid with other methods to further research on mitigating WBAN interference

Compressive Sensing with Low-Power Transfer and Accurate Reconstruction of EEG Signals

Tele-monitoring of EEG in WBAN is essential as EEG is the most powerful physiological parameters to diagnose any neurological disorder. Generally, EEG signal needs to record for longer periods which results in a large volume of data leading to huge storage and communication bandwidth requirements in WBAN. Moreover, WBAN sensor nodes are battery operated which consumes lots of energy. The aim of this research is, therefore, low power transmission of EEG signal over WBAN and its accurate reconstruction at the receiver to enable continuous online-monitoring of EEG and real time feedback to the patients from the medical experts. To reduce data rate and consequently reduce power consumption, compressive sensing (CS) may be employed prior to transmission. Nonetheless, for EEG signals, the accuracy of reconstruction of the signal with CS depends on a suitable dictionary in which the signal is sparse. As the EEG signal is not sparse in either time or frequency domain, identifying an appropriate dictionary is paramount. There are a plethora of choices for the dictionary to be used. Wavelet bases are of interest due to the availability of associated systems and methods. However, the attributes of wavelet bases that can lead to good quality of reconstruction are not well understood. For the first time in this study, it is demonstrated that in selecting wavelet dictionaries, the incoherence with the sensing matrix and the number of vanishing moments of the dictionary should be considered at the same time. In this research, a framework is proposed for the selection of an appropriate wavelet dictionary for EEG signal which is used in tandem with sparse binary matrix (SBM) as the sensing matrix and ST-SBL method as the reconstruction algorithm. Beylkin (highly incoherent with SBM and relatively high number of vanishing moments) is identified as the best dictionary to be used amongst the dictionaries are evaluated in this thesis. The power requirements for the proposed framework are also quantified using a power model. The outcomes will assist to realize the computational complexity and online implementation requirements of CS for transmitting EEG in WBAN. The proposed approach facilitates the energy savings budget well into the microwatts range, ensuring a significant savings of battery life and overall system’s power. The study is intended to create a strong base for the use of EEG in the high-accuracy and low-power based biomedical applications in WBAN

Diseños de capa cruzada para redes inalámbricas de área corporal energéticamente eficientes: una revisión

RESUMEN: El diseño de capa cruzada se considera una poderosa alternativa para dar solución a las complejidades introducidas por las comunicaciones inalámbricas en redes de área corporal (WBAN), donde el modelo clásico de comunicaciones no ha exhibido un desempeño adecuado. Respecto al problema puntual de consumo de energía, hemos preparado la presente revisión de las publicaciones más relevantes que tratan la eficiencia energética para WBAN usando diseño de capa cruzada. En este artículo se proporciona una revisión exhaustiva de los avances en aproximaciones, protocolos y optimizaciones de capa cruzada cuyo objetivo es incrementar el tiempo de vida de las redes WBAN mediante el ahorro de energía. Luego, se discute los aspectos relevantes y deficiencias de las técnicas de capa cruzada energéticamente eficientes. Además, se introducen aspectos de investigación abiertos y retos en el diseño de capa cruzada para WBAN. En esta revisión proponemos una taxonomía de las aproximaciones de capa cruzada, de modo que las técnicas revisadas se ajustan en categorías de acuerdo a los protocolos involucrados en el diseño. Una clasificación novedosa se incluye para hacer claridad en los conceptos teóricos involucrados en cada esquema de capa cruzada y para luego agrupar aproximaciones similares evidenciando las diferencias con otras técnicas entre sí. Nuestras conclusiones consideran los aspectos de movilidad y modelamiento del canal en escenarios de WBAN como las direcciones para futura investigación en WBAN y en aplicaciones de telemedicina.ABSTRACT: Cross-layer design is considered a powerful alternative to solve the complexities of wireless communication in wireless body area networks (WBAN), where the classical communication model has been shown to be inaccurate. Regarding the energy consumption problem, we have prepared a current survey of the most relevant scientific publications on energy-efficient cross-layer design for WBAN. In this paper, we provide a comprehensive review of the advances in cross-layer approaches, protocols and optimizations aimed at increasing the network lifetime by saving energy in WBANs. Subsequently, we discuss the relevant aspects and shortcomings of these energy-efficient cross-layer techniques and point out the open research issues and challenges in WBAN cross-layer design. In this survey, we propose a taxonomy for cross-layer approaches to fit them into categories based on the protocols involved in the cross-layer scheme. A novel classification is included to clarify the theoretical concepts behind each cross-layer scheme; and to group similar approaches by establishing their differences from the other strategies reviewed. Our conclusion considers the aspects of mobility and channel modeling in WBAN scenarios as the directions of future cross-layer research for WBAN and telemedicine applications

Real-time signal detection and classification algorithms for body-centered systems

El principal motivo por el cual los sistemas de comunicación en el entrono corporal se desean con el objetivo de poder obtener y procesar señales biométricas para monitorizar e incluso tratar una condición médica sea ésta causada por una enfermedad o el rendimiento de un atleta. Dado que la base de estos sistemas está en la sensorización y el procesado, los algoritmos de procesado de señal son una parte fundamental de los mismos. Esta tesis se centra en los algoritmos de tratamiento de señales en tiempo real que se utilizan tanto para monitorizar los parámetros como para obtener la información que resulta relevante de las señales obtenidas. En la primera parte se introduce los tipos de señales y sensores en los sistemas en el entrono corporal. A continuación se desarrollan dos aplicaciones concretas de los sistemas en el entorno corporal así como los algoritmos que en las mismas se utilizan. La primera aplicación es el control de glucosa en sangre en pacientes con diabetes. En esta parte se desarrolla un método de detección mediante clasificación de patronones de medidas erróneas obtenidas con el monitor contínuo comercial "Minimed CGMS". La segunda aplicacióin consiste en la monitorizacióni de señales neuronales. Descubrimientos recientes en este campo han demostrado enormes posibilidades terapéuticas (por ejemplo, pacientes con parálisis total que son capaces de comunicarse con el entrono gracias a la monitorizacióin e interpretación de señales provenientes de sus neuronas) y también de entretenimiento. En este trabajo, se han desarrollado algoritmos de detección, clasificación y compresión de impulsos neuronales y dichos algoritmos han sido evaluados junto con técnicas de transmisión inalámbricas que posibiliten una monitorización sin cables. Por último, se dedica un capítulo a la transmisión inalámbrica de señales en los sistemas en el entorno corporal. En esta parte se estudia las condiciones del canal que presenta el entorno corporal para la transmisión de sTraver Sebastiá, L. (2012). Real-time signal detection and classification algorithms for body-centered systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16188Palanci

MAC Protocol for UWB Wireless Body Area Network

Wireless Body Area Network (WBAN) is a networking concept that has evolved with the idea of monitoring vital physiological signals from low-power and miniaturized in-body or on-body sensors. Since WBAN sensor nodes are battery powered, they should be low power devices. The sensor tier communication of a WBAN involves the co-existence of WBAN hardware and Medium Access Control (MAC) protocol that enable the efficient communication of sensor data. The main focus of this paper is to investigate key aspects of MAC protocol used in WBAN systems focusing on Ultra Wideband (UWB) as the wireless technology, payingi attention to its ability to cater to the need of high data rate while operating at a low power. MAC protocol mentioned in this paper have considered manipulation of the physical layer properties of the UWB systems such as number of pulses per data bit (PPB), which can be incorporated with the MAC algorithm in order to make the system more dynamic in terms of Bit Error Rate (BER), data rate, and Quality-of-Service (QoS)