Versatile integrated circuit for the acquisition of biopotentials

Journal ArticleElectrically active cells in the body produce a wide variety of voltage signals that are useful for medical diagnosis and scientific investigation. These biopotentials span a wide range of amplitudes and frequencies. We have developed a versatile front-end integrated circuit that can be used to amplify many types of bioelectrical signals. The 0.6-μm CMOS chip contains 16 fully-differential amplifiers with gains of 46 dB, 2μVrms input-referred noise, and bandwidths programmable from 10Hz to 10kHz

Noise Efficient Integrated Amplifier Designs for Biomedical Applications

The recording of neural signals with small monolithically integrated amplifiers is of high interest in research as well as in commercial applications, where it is common to acquire 100 or more channels in parallel. This paper reviews the recent developments in low-noise biomedical amplifier design based on CMOS technology, including lateral bipolar devices. Seven major circuit topology categories are identified and analyzed on a per-channel basis in terms of their noise-efficiency factor (NEF), input-referred absolute noise, current consumption, and area. A historical trend towards lower NEF is observed whilst absolute noise power and current consumption exhibit a widespread over more than five orders of magnitude. The performance of lateral bipolar transistors as amplifier input devices is examined by transistor-level simulations and measurements from five different prototype designs fabricated in 180 nm and 350 nm CMOS technology. The lowest measured noise floor is 9.9 nV/√Hz with a 10 µA bias current, which results in a NEF of 1.2

An Ultra-Low-Power Front-End Neural Interface with Automatic Gain for Uncalibrated Monitoring

Accepted versio

A High CMRR Instrumentation Amplifier for Biopotential Signal Acquisition

Biopotential signals are important to physicians for diagnosing medical conditions in patients. Traditionally, biopotentials are acquired using contact electrodes together with instrumentation amplifiers (INAs). The biopotentials are generally weak and in the presence of stronger common mode signals. The INA thus needs to have very good Common Mode Rejection Ratio (CMRR) to amplify the weak biopotential while rejecting the stronger common mode interferers. Opamp based INAs with a resistor-capacitor feedback are suitable for acquiring biopotentials with low power and low noise performance. However, CMRR of such INA topologies is typically very poor. In the presented research, a technique is proposed for improving the CMRR of opamp based INAs in RC feedback configurations by dynamically matching input and feedback capacitor pairs. Two instrumentation amplifiers (one fully differential and the other fully balanced fully symmetric) are designed with the proposed dynamic element matching scheme. Post layout simulation results show that with 1 percent mismatch between the limiting capacitor pairs, CMRR is improved to above 150dB when the proposed dynamic element matching scheme is used. The INAs draw about 10uA of quiescent current from a 1.5 dual power supply source. The input referred noise of the INAs is less than 3uV/sqrt(Hz)

Modulaarinen kehitysalusta langattomille lääketieteellisille anturi-implanteille

Implanting medical sensor devices under skin improves the quality of the acquired measurement results, and can greatly increase the comfort for the patient in prolonged measurement. Design of such complex devices and related systems benefits from using a dedicated development platform that represents the functionalities and associated challenges. This work presents the design, implementation and verified performance of a modular platform that can be used in demonstration, development and testing of various functionalities of wireless medical sensor implants. The system is constructed using discrete components and consists of five inter connectable modules, each representing a specific function of the sensor implant system: bio potential measurement front-end module, wireless communication front-end module, clock and power management module, control logic module and external reader module. The implemented system has measurement front-end with an ENOB of 9 bits and configurable structure for the needs of various bio potentials. Wireless data transfer operates at 840-960 MHz with supported data rate up to 640 kbps. The system demonstrates dual carrier operation for separating the power and data transfers. Power can be harvested and clock extracted from 6.75 MHz or 865 MHz radio signals, both radio signals can be generated by the external reader. Control logic is provided with a high-end FPGA evaluation board. The completed platform can be used for developing and testing aspects for novel implanted devices, such as different radio communication schemes, radio antenna options, or controls and algorithms in digital logic.Lääketieteellisten anturien asettaminen ihon alle parantaa biopotentiaalimittauksien tulosten laatua ja pitkäaikaisten mittauksien mukavuutta potilaalle. Näiden monimutkaisten laitteiden suunnittelua voidaan tehostaa käyttämällä apuna sovelluskohtaista kehitysalustaa. Tässä työssä suunnitellaan ja toteutetaan modulaarinen, korkean suorituskyvyn kehitysalusta biopotentiaalia mittaavien langattomien anturi-implanttijärjestelmien eri toiminnallisuuksien esittelyyn, kehitykseen ja testaukseen. Diskreeteillä komponenteilla toteutettu järjestelmä koostuu viidestä moduulista: biopotentiaalien mittausmoduuli, langattoman tiedonvälityksen radiomoduuli, tehon ja kellosignaalin keräysmoduuli, ohjauslogiikkamoduuli, ja kehon ulkopuolinen lukijamoduuli. Kehitysalusta on muokattavissa eri biopotentiaalien mittauksien tarpeisiin. Mittausetupään tehollinen bittimäärä on 9 bittiä. Langatonta tiedonsiirtoa tuetaan 840 - 960 MHz taajuuskaistalla 640 kbps siirtonopeuksiin asti. Järjestelmällä voidaan demonstroida kahden kantoaallon yhtäaikaista käyttämistä, jolloin tehon- ja tiedonsiirto voidaan tarvittaessa erottaa toisistaan. Tehoa voidaan kerätä ja kellosignaaleja muodostaa 6,75 MHz ja 865 MHz taajuuksien radiosignaaleilta, jotka molemmat voidaan luoda hallitusti lukijamoduulilla. Ohjauslogiikka on toteutettu käyttäen ohjelmoitavaa porttimatriisipiiriä. Kehitysalustaa voidaan käyttää uusien implanttijärjestelmien suunnittelussa, esimerkiksi eri tiedonsiirtotapojen, antennirakenteiden, ohjauslogiikan ja digitaalisten algoritmien arvioinnissa

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

Advanced Interfaces for HMI in Hand Gesture Recognition

The present thesis investigates techniques and technologies for high quality Human Machine Interfaces (HMI) in biomedical applications. Starting from a literature review and considering market SoA in this field, the thesis explores advanced sensor interfaces, wearable computing and machine learning techniques for embedded resource-constrained systems. The research starts from the design and implementation of a real-time control system for a multifinger hand prosthesis based on pattern recognition algorithms. This system is capable to control an artificial hand using a natural gesture interface, considering the challenges related to the trade-off between responsiveness, accuracy and light computation. Furthermore, the thesis addresses the challenges related to the design of a scalable and versatile system for gesture recognition with the integration of a novel sensor interface for wearable medical and consumer application

Enhanced ICMR amplifier for high CMRR biopotential recordings

PostprintThis paper presents an integrated biopotential preamplifier architecture targeting applications that simultaneously require high common-mode rejection ratio (CMRR), low noise, high input common-mode range (ICMR), and current-efficiency (low Noise Efficiency Factor or NEF). A biopotential preamplifier, which performs well in line with the state-of-the-art of the field while providing enhanced ICMR and CMRR performance, was fabricated in a 0.5 μm CMOS process. Results from measurements show that the gain is 47 dB, the bandwidth ranges from 1 Hz to 7.7 kHz, the equivalent input noise is 1.8 μV rms , the CMRR is 100.5 dB, the ICMR is 1.7 V and the NEF is 3.2