Wearable and Implantable Wireless Sensor Network Solutions for Healthcare Monitoring

Wireless sensor network (WSN) technologies are considered one of the key research areas in computer science and the healthcare application industries for improving the quality of life. The purpose of this paper is to provide a snapshot of current developments and future direction of research on wearable and implantable body area network systems for continuous monitoring of patients. This paper explains the important role of body sensor networks in medicine to minimize the need for caregivers and help the chronically ill and elderly people live an independent life, besides providing people with quality care. The paper provides several examples of state of the art technology together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provides a comprehensive analysis of the various benefits and drawbacks of these systems. Although offering significant benefits, the field of wearable and implantable body sensor networks still faces major challenges and open research problems which are investigated and covered, along with some proposed solutions, in this paper

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

Development of miniaturized antennas and adaptive tuning solutions for body sensor network applications

Wireless Sensor Networks (WSNs) are currently having a revolutionary impact in rapidly emerging wearable applications such as health and fitness monitoring amongst many others. These types of Body Sensor Network (BSN) applications require highly integrated wireless sensor devices for use in a wearable configuration, to monitor various physiological parameters of the user. These new requirements are currently posing significant design challenges from an antenna perspective. This work addresses several design challenges relating to antenna design for these types of applications. In this thesis, a review of current antenna solutions for WSN applications is first presented, investigating both commercial and academic solutions. Key design challenges are then identified relating to antenna size and performance. A detailed investigation of the effects of the human body on antenna impedance characteristics is then presented. A first-generation antenna tuning system is then developed. This system enables the antenna impedance to be tuned adaptively in the presence of the human body. Three new antenna designs are also presented. A compact, low-cost 433 MHz antenna design is first reported and the effects of the human body on the impedance of the antenna are investigated. A tunable version of this antenna is then developed, using a higher performance, second-generation tuner that is integrated within the antenna element itself, enabling autonomous tuning in the presence of the human body. Finally, a compact sized, dual-band antenna is reported that covers both the 433 MHz and 2.45 GHz bands to provide improved quality of service (QoS) in WSN applications. To date, state-of-the-art WSN devices are relatively simple in design with limited antenna options available, especially for the lower UHF bands. In addition, current devices have no capability to deal with changing antenna environments such as in wearable BSN applications. This thesis presents several contributions that advance the state-of-the-art in this area, relating to the design of miniaturized WSN antennas and the development of antenna tuning solutions for BSN 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

Design and Application of Wireless Body Sensors

Hörmann T. Design and Application of Wireless Body Sensors. Bielefeld: Universität Bielefeld; 2019

A sudden death prevention system for babies

The growth of the smartphones market share has driven the entry of a large number of new opportunities to launch new applications/mobile tools both by companies but also by individuals’ entities. The prototype solution presented here fits in the increasing emerging of smartphones applications for the health sector. This dissertation presents a solution to prevent a sudden infant death syndrome. It includes biofeedback monitoring of babies, using body sensors to collect data that will be presented in two different mobile applications: the Main Application and the Client Application. Breathing, temperature, position, and heart rate are used, and placed to the baby’s body. The Main Application will receive the data collected by the sensors via Bluetooth. This contains a monitoring tool, which parses and transforms raw data to be readable and understandable for users. This application will send the data to a Web service to be stored in a database that supports the entire created solution. The Client Application will consume the data stored in the database every previous second. Both applications have an important functionality that allows the trigger of alert notifications when an error occurs with the data collected by the sensors and the caregiver is informed with an alert in a short time. This document describes in detail the whole process done to deploy a prototype that demonstrates and validates the proposed solution and is ready for use

Ultra Low-Power Frequency Synthesizers for Duty Cycled IoT radios

Internet of Things (IoT), which is one of the main talking points in the electronics industry today, consists of a number of highly miniaturized sensors and actuators which sense the physical environment around us and communicate that information to a central information hub for further processing. This agglomeration of miniaturized sensors helps the system to be deployed in previously impossible arenas such as healthcare (Body Area Networks - BAN), industrial automation, real-time monitoring environmental parameters and so on; thereby greatly improving the quality of life. Since the IoT devices are usually untethered, their energy sources are limited (typically battery powered or energy scavenging) and hence have to consume very low power. Today's IoT systems employ radios that use communication protocols like Bluetooth Smart; which means that they communicate at data rates of a few hundred kb/s to a few Mb/s while consuming around a few mW of power. Even though the power dissipation of these radios have been decreasing steadily over the years, they seem to have reached a lower limit in the recent times. Hence, there is a need to explore other avenues to further reduce this dissipation so as to further improve the energy autonomy of the IoT node. Duty cycling has emerged as a promising alternative in this sense since it involves radios transmitting very short bursts of data at high rates and being asleep the rest of the time. In addition, high data rates proffer the added advantage of reducing network congestion which has become a major problem in IoT owing to the increase in the number of sensor nodes as well as the volume of data they send. But, as the average power (energy) dissipated decreases due to duty cycling, the energy overhead associated with the start-up phase of the radio becomes comparable with the former. Therefore, in order to take full advantage of duty cycling, the radio should be capable of being turned ON/OFF almost instantaneously. Furthermore, the radio of the future should also be able to support easy frequency hopping to improve the system efficiency from an interference point of view. In other words, in addition to high data rate capability, the next generation radios must also be highly agile and have a low energy overhead. All these factors viz. data rate, agility and overhead are mainly dependent on the radio's frequency synthesizer and therefore emphasis needs to be laid on developing new synthesizer architectures which are also amenable to technology scaling. This thesis deals with the evolution of one such all-digital frequency synthesizer; with each step dealing with one of the aforementioned issues. In order to reduce the energy overhead of the synthesizer, FBAR resonators (which are a class of MEMS resonators) are used as the frequency reference instead of a traditional quartz crystal. The FBAR resonators aid the design of fast-startup oscillators as opposed to the long latency associated with the start-up of the crystal oscillator. In addition, the frequency stability of the FBAR lends itself to open-loop architecture which can support very high data rates. Another advantage of the open-loop architecture is the frequency agility which aids easy channel switching for multi-hop architectures, as demonstrated in this thesis

Ultra Low Energy Communication Protocol for Implantable Wireless Body Sensor Networks

Abstract Title: Ultra Low Energy Communication Protocol for Implantable Wireless Body Sensor Networks. Fariborz Fereydouni_Forouzandeh, Ph.D. Concordia University, 2010 Medical science will soon start to benefit from wireless communication and implantable sensor technologies being developed for use in the human body. Such technologies have a potential to revolutionize the health-care industry by providing real-time patient monitoring capabilities to the health-care professionals. In this regard, implantable wireless body sensor networks (IWBSNs) have recently emerged as an important and growing area of research. The implantable sensors are required to be reliable and very small so that the body does not reject them. They must stay functional in the human body for years, and most importantly, they must not be a source of discomfort to the potential patients. The life time of their embedded batteries could vary from a few days to a few weeks using current hardware and software technologies. In order to make such devices suitable for implantation an order of magnitude reduction in energy use is required. Our research is motivated by this goal. In this thesis, we identify and analyze the sources of energy use in typical devices meant for Implantation in a human body. Our detailed mathematical analysis and computer simulations clearly demonstrate that improving the efficiency of communication protocols is the only realistic way of achieving this goal. Unfortunately, none of the existing low range low energy wireless communication protocols can be used in IWBSNs because of the small energy resources available in the implanted sensor nodes. We propose a new energy aware communication protocol which efficiently encodes data in time domain. It ensures accurate transmission of information. The encoding scheme does this by sending only a single signal from the sensor node to the base station. The protocol is called the Time Based Coded Data protocol or TBCD in short. For proper operation of this protocol reliable synchronization is required. Our proposed synchronization algorithm is energy efficient and stable under worst case conditions as compared to existing algorithms. A sensor node using existing state of the art technology that can only last for a few weeks can be made to last for few years using our proposed communication protocol and the synchronization algorithm

Review on biomedical sensors, technologies, and algorithms for diagnosis of sleep-disordered breathing: Comprehensive survey

This paper provides a comprehensive review of available technologies for measurements of vital physiology related parameters that cause sleep disordered breathing (SDB). SDB is a chronic disease that may lead to several health problems and increase the risk of high blood pressure and even heart attack. Therefore, the diagnosis of SDB at an early stage is very important. The essential primary step before diagnosis is measurement. Vital health parameters related to SBD might be measured through invasive or non-invasive methods. Nowadays, with respect to increase in aging population, improvement in home health management systems is needed more than even a decade ago. Moreover, traditional health parameter measurement techniques such as polysomnography are not comfortable and introduce additional costs to the consumers. Therefore, in modern advanced self-health management devices, electronics and communication science are combined to provide appliances that can be used for SDB diagnosis, by monitoring a patient's physiological parameters with more comfort and accuracy. Additionally, development in machine learning algorithms provides accurate methods of analysing measured signals. This paper provides a comprehensive review of measurement approaches, data transmission, and communication networks, alongside machine learning algorithms for sleep stage classification, to diagnose SDB