A wireless ECG plaster for real-time cardiac health monitoring in body sensor networks

10.1109/BioCAS.2011.61077632011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011205-20

EMBEDDED HARDWARE AND SOFTWARE DESIGN FOR LOW-POWER WIRELESS ECG DEVICE

Master'sMASTER OF ENGINEERIN

Implementation of Health Care Monitoring System using low power MCU’s and ARM CORTEX A8

The present common goal in the medical information technology is the design and implementation of telemedicine solutions, which provides a reliable and quality of services to patients. With the advent of recent development in sensors, low-power integrated circuits (IC’s), and wireless communications have brought the design of miniature, low-cost, and intelligent body sensor modules. These modules are capable of measuring, processing, communicating one or more physiological parameters, and can be integrated into a wireless personal area network. In this paper, we proposed a wireless body sensor module, based on low power microcontrollers and RF devices that perform the measurements and transmit the different bio sensors data to a Local Sensor Network server. Local Sensor Network (LSN) server will run a signal monitor application which  receives the information from wireless sensor module and draw the signal graph on the display according to received data and further updated to central health care surveillance centre. The LSN server should be able to connect all the nearby sensor modules through wireless media and update its data periodically.  Any sudden urge found in the signal will alarm the corresponding doctor. In order to handle such more number of sensor module connections, the Local sensor network server should be implemented with high performance processor. In this paper, the ARM Cortex A8 processor is one of the best choices to meet all the requirements o

DESIGN OF ENERGY EFFICIENT WEARABLE ECG SYSTEM AND LOW POWER ASYNCHRONOUS MICROCONTROLLER

Master'sMASTER OF ENGINEERIN

A WI-FI BASED SMART DATA LOGGER FOR CAPSULE ENDOSCOPY AND MEDICAL APPLICATIONS

Wireless capsule endoscopy (WCE) is a non-invasive technology for capturing images of a human digestive system for medical diagnostics purpose. With WCE, the patient swallows a miniature capsule with camera, data processing unit, RF transmitter and batteries. The capsule captures and transmits images wirelessly from inside the human gastrointestinal (GI) tract. The external data logger worn by the patient stores the images and is later on transferred to a computer for presentation and image analysis. In this research, we designed and built a Wi-Fi based, low cost, miniature, versatile wearable data logger. The data logger is used with Wi-Fi enabled smart devices, smart phones and data servers to store and present images captured by capsule. The proposed data logger is designed to work with wireless capsule endoscopy and other biosensors like- temperature and heart rate sensors. The data logger is small enough to carry and conduct daily activities, and the patient do not need to carry traditional bulky data recorder all the time during diagnosis. The doctors can remotely access data and analyze the images from capsule endoscopy using remote access feature of the data logger. Smartphones and tablets have extensive processing power with expandable memory. This research exploits those capabilities to use with wireless capsule endoscopy and medical data logging applications. The application- specific data recorders are replaced by the proposed Wi-Fi data logger and smartphone. The data processing application is distributed on smart devices like smartphone /tablets and data logger. Once data are stored in smart devices, the data can be accessed remotely, distributed to the cloud and shared within networks to enable telemedicine. The data logger can work in both standalone and network mode. In the normal mode of the device, data logger stores medical data locally into a micro Secure Digital card for future download using the universal serial bus to the computer. In network mode, the real-time data is streamed into a smartphone and tablet for further processing and storage. The proposed Wi-Fi based data logger is prototyped in the lab and tested with the capsule hardware developed in our laboratory. The supporting Android app is also developed to collect data from the data logger and present the processed data to the viewer. The PC based software is also developed to access the data recorder and capture and download data from the data logger in real-time remotely. Both in vivo and ex vivo trials using live pig have been conducted to validate the performance of the proposed device

Embedded computing systems design: architectural and application perspectives

Questo elaborato affronta varie problematiche legate alla progettazione e all'implementazione dei moderni sistemi embedded di computing, ponendo in rilevo, e talvolta in contrapposizione, le sfide che emergono all'avanzare della tecnologia ed i requisiti che invece emergono a livello applicativo, derivanti dalle necessità degli utenti finali e dai trend di mercato. La discussione sarà articolata tenendo conto di due punti di vista: la progettazione hardware e la loro applicazione a livello di sistema. A livello hardware saranno affrontati nel dettaglio i problemi di interconnettività on-chip. Aspetto che riguarda la parallelizzazione del calcolo, ma anche l'integrazione di funzionalità eterogenee. Sarà quindi discussa un'architettura d'interconnessione denominata Network-on-Chip (NoC). La soluzione proposta è in grado di supportare funzionalità avanzate di networking direttamente in hardware, consentendo tuttavia di raggiungere sempre un compromesso ottimale tra prestazioni in termini di traffico e requisiti di implementazioni a seconda dell'applicazione specifica. Nella discussione di questa tematica, verrà posto l'accento sul problema della configurabilità dei blocchi che compongono una NoC. Quello della configurabilità, è un problema sempre più sentito nella progettazione dei sistemi complessi, nei quali si cerca di sviluppare delle funzionalità, anche molto evolute, ma che siano semplicemente riutilizzabili. A tale scopo sarà introdotta una nuova metodologia, denominata Metacoding che consiste nell'astrarre i problemi di configurabilità attraverso linguaggi di programmazione di alto livello. Sulla base del metacoding verrà anche proposto un flusso di design automatico in grado di semplificare la progettazione e la configurazione di una NoC da parte del designer di rete. Come anticipato, la discussione si sposterà poi a livello di sistema, per affrontare la progettazione di tali sistemi dal punto di vista applicativo, focalizzando l'attenzione in particolare sulle applicazioni di monitoraggio remoto. A tal riguardo saranno studiati nel dettaglio tutti gli aspetti che riguardano la progettazione di un sistema per il monitoraggio di pazienti affetti da scompenso cardiaco cronico. Si partirà dalla definizione dei requisiti, che, come spesso accade a questo livello, derivano principalmente dai bisogni dell'utente finale, nel nostro caso medici e pazienti. Verranno discusse le problematiche di acquisizione, elaborazione e gestione delle misure. Il sistema proposto introduce vari aspetti innovativi tra i quali il concetto di protocollo operativo e l'elevata interoperabilità offerta. In ultima analisi, verranno riportati i risultati relativi alla sperimentazione del sistema implementato. Infine, il tema del monitoraggio remoto sarà concluso con lo studio delle reti di distribuzione elettrica intelligenti: le Smart Grid, cercando di fare uno studio dello stato dell'arte del settore, proponendo un'architettura di Home Area Network (HAN) e suggerendone una possibile implementazione attraverso Commercial Off the Shelf (COTS)

A biosignal embedded system for physiological computing

Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications EngineeringO estudo e a utilização dos biosinais tem vindo a aumentar dentro da comunidade global de engenharia. Daí têm nascido novos campos de aplicações, para além das mais tradicionais em áreas da medicina. Enumerando alguns exemplos temos: monitorização da actividade humana em desporto, onde novos dispositivos (Hardware e Software) têm vindo a ser lançados pela indústria para auto-monitorização de performance; interação Homem-Máquina em jogos de computador/consola, possibilitando ao utilizador interagir com o jogo e vice-versa; em biometria, onde novos sistemas baseados em eletrocardiografia vêm adicionar novas propriedades de identificação às modalidades já existentes (reconhecimento facial, iris, impressão digital). Adicionalmente, as recentes correntes de “Open-Source” e “Do-It-Yourself” têm vindo a transformar o modo como a indústria e o ensino de engenharia são executados. Desta forma, surgem novas plataformas de desenvolvimento, tais como o Arduino e o Raspberry Pi, que têm revelado uma vibrante comunidade de seguidores, e têm inspirado diversos projectos na área de sistemas embebidos. Contudo, muitos dos projectos encontrados no estado da arte focam-se principalmente na computação física, onde interagem com simples sensores e actuadores, tais como LEDs e botões ou mesmo pequenos motores, tendo poucos requisitos em termos de aquisição de sinal, nomeadamente baixa tolerância ao ruído e baixas frequências de amostragem, não sendo compativeis com o estudo e aquisição de biosinais. Com este trabalho apresentamos o "BITalino", uma versátil e multimodal plataforma para aquisição de biosinais, de baixo-custo, que pode ser utilizada como ferramenta em actividades de sala de aula, que possibilita a interacção com outros dispositivos, e que potencia a prototipagem rápida de aplicações finais de utilizador na área da computação fisiológica. O principal objectivo é tornar a aquisição de biosinais fácil e acessível a todos, desde estudantes, investigadores, engenhocas, e pessoas com interesse em trabalhar na área dos biosinais. O BITalino é uma placa de hardware que integra um micro-controlador, um módulo de acondicionamento para a alimentação do sistema e controlo de carga da bateria, um módulo wireless para transmissão de dados utilizando a tecnologia Bluetooth, que possibilita a sua ligação a um computador, telemóvel, ou qualquer outro dispositivo que tenha um receptor Bluetooth. Integra também vários sensores muitos especializados na medição de sinais do corpo humano, nomeadamente, sensor para medir a actividade do coração, outro que permite medir a actividade muscular, outro para medir a actividade do sistema nervoso simpático e um outro que permite medir o movimento. Adicionalmente, integra também um sensor que permite medir a luz ambiente e também um simples LED que permite dar um feedback muito simples ao utilizador da placa. Além do baixo-custo, outra particularidade do sistema é o facto de estar desenhado como um Lego, em que todos os blocos descritos anteriormente podem ser destacados da placa principal,dando liberdade ao utilizador para combiná-los do modo que for mais interessante para a sua aplicação. Neste trabalho são focados os principais conceitos teóricos para a medida de biosinais, nomeadamente Eletrocardiografia, Eletromiografia, actividade Eletrodérmica e Acelerometria, assim como a caracterização detalhada de todo o hardware e firmware, nomeadamente cada módulo e respectivos testes de caracterização e avaliação de performance. Serão apresentados também alguns exemplos de aplicação construídos com base na plataforma desenvolvida, que demonstram o seu potencial, nomeadamente: um detector de ritmo cardíaco que utiliza sinais de eletrocardiografia para actuar num LED; um controlador de luz, que utiliza sinais de acelerometria para ligar ou desligar uma lâmpada; uma fechadura de porta que é controlada através de sinais de eletromiografia; um didático e interactivo detector de mentiras que se baseia nas variações emocionais captadas através dos sinais de actividade eletrodérmica e ritmo cardíaco; e uma flôr equipada com sensores adicionais que envia mensagens para o Twitter a informar o seu estado de saúde.Abstract: By definition, physical computing deals with the study and development of interactive systems that sense and react to the analog world. In an analogous way, physiological computing can be defined as the field, within physical computing, that deals with the study and development of systems that sense and react to the human body. While physical computing has seen significant advancements leveraged by the popular Arduino platform, no such equivalent can yet be found for physiological computing. In this work we present "BITalino", a novel, low-cost, versatile platform, targeted at multimodal biosignal acquisition that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications in the field of physiological computing. BITalino integrates a micro-controller, a module for power conditioning and battery management, a wireless communication module that uses Bluetooth technology, allowing it to be connected to a computer, mobile phone or any other device that includes a Bluetooth receiver. Targeting the acquisition of physiological signals, it also integrates many specialized sensors to measure signals from the human body, in particular sensors to measure the activity of the heart, muscles, the activity of the sympathetic nervous system and movement. Additionally, it also includes a sensor that measures ambient light as well as a simple LED that gives easy feedback to the user. Besides as low-cost, another feature of the system is the fact that it is designed as a Lego, in which all the blocks described above can be detached from the main board, providing the user freedom to combine them in the manner that is most interesting for their own applications. The emphases of this work is on the main theoretical concepts of the Biosignals measurement, including Electrocardiography, Electromyography, Electrodermal Activity and Accelerometry, as well as detailed characterization of all hardware and firmware modules, including each block and their characterization tests and performance evaluation. We also present several examples of ap- plications built using the developed platform to demonstrate its potential, namely: a Heartbeatdetector that uses Electrocardiographic (ECG) signals to trigger a LED; a light controlled by the wave of the hands, using Accelerometric (ACC) signals; a Muscle-controlled door lock, that uses Electromyographic (EMG) signals as a trigger; a didactic and interactive lie-detector setup that answers according to the emotional variations based on Electrodermal Activity (EDA) signals and Heart Rate (HR); and a twitting flower vase fitted with some additional non-BITalino sensors, that monitors the ambient light, soil moisture, relative humidity of air and temperature, to check the ”health” status of a flower

Capsule endoscopy system with novel imaging algorithms

Wireless capsule endoscopy (WCE) is a state-of-the-art technology to receive images of human intestine for medical diagnostics. In WCE, the patient ingests a specially designed electronic capsule which has imaging and wireless transmission capabilities inside it. While the capsule travels through the gastrointestinal (GI) tract, it captures images and sends them wirelessly to an outside data logger unit. The data logger stores the image data and then they are transferred to a personal computer (PC) where the images are reconstructed and displayed for diagnosis. The key design challenge in WCE is to reduce the area and power consumption of the capsule while maintaining acceptable image reconstruction. In this research, the unique properties of WCE images are identified by analyzing hundreds of endoscopic images and video frames, and then these properties are used to develop novel and low complexity compression algorithms tailored for capsule endoscopy. The proposed image compressor consists of a new YEF color space converter, lossless prediction coder, customizable chrominance sub-sampler and an efficient Golomb-Rice encoder. The scheme has both lossy and lossless modes and is further customized to work with two lighting modes – conventional white light imaging (WLI) and emerging narrow band imaging (NBI). The average compression ratio achieved using the proposed lossy compression algorithm is 80.4% for WBI and 79.2% for NBI with high reconstruction quality index for both bands. Two surveys have been conducted which show that the reconstructed images have high acceptability among medical imaging doctors and gastroenterologists. The imaging algorithms have been realized in hardware description language (HDL) and their functionalities have been verified in field programmable gate array (FPGA) board. Later it was implemented in a 0.18 μm complementary metal oxide semiconductor (CMOS) technology and the chip was fabricated. Due to the low complexity of the core compressor, it consumes only 43 µW of power and 0.032 mm2 of area. The compressor is designed to work with commercial low-power image sensor that outputs image pixels in raster scan fashion, eliminating the need of significant input buffer memory. To demonstrate the advantage, a prototype of the complete WCE system including an FPGA based electronic capsule, a microcontroller based data logger unit and a Windows based image reconstruction software have been developed. The capsule contains the proposed low complexity image compressor and can generate both lossy and lossless compressed bit-stream. The capsule prototype also supports both white light imaging (WLI) and narrow band imaging (NBI) imaging modes and communicates with the data logger in full duplex fashion, which enables configuring the image size and imaging mode in real time during the examination. The developed data logger is portable and has a high data rate wireless connectivity including Bluetooth, graphical display for real time image viewing with state-of-the-art touch screen technology. The data are logged in micro SD cards and can be transferred to PC or Smartphone using card reader, USB interface, or Bluetooth wireless link. The workstation software can decompress and show the reconstructed images. The images can be navigated, marked, zoomed and can be played as video. Finally, ex-vivo testing of the WCE system has been done in pig's intestine to validate its performance

Myoelectric Signal Monitoring System

The Electromyography (EMG) is an important tool for gait analyzes and disorders diagnoses. Traditional methods involve equipment that can disturb the analyses, being gradually substituted by different approaches, like wearable and wireless systems. The cable replacement for autonomous systems demands for technologies capable of meeting the power constraints. This work presents the development of an EMG and kinematic data capture wireless module, designed taking into account power consumption issues. This module captures and converts the analog myoeletric signal to digital, synchronously with the capture of kinetic information. Both data are time multiplexed and sent to a PC via Bluetooth link. The work carried out comprised the development of the hardware, the firmware and a graphical interface running in an external PC. The hardware was developed using the PIC18F14K22, a low power family of microcontrollers. The link was established via Bluetooth, a protocol designed for low power communication. An application was also developed to recover and trace the signal to a Graphic User Interface (GUI), coordinating the message exchange with the firmware. Results were obtained which allowed validating the conceived system in static and with the subject performing short movements. Although it was not possible to perform the tests within more dynamic movements, it is shown that it is possible to capture, transmit and display the captured data as expected. Some suggestions to improve the system performance also were made