Development of real-time cellular impedance analysis system

The cell impedance analysis technique is a label-free, non-invasive method, which simplifies sample preparation and allows applications requiring unmodified cell retrieval. However, traditional impedance measurement methods suffer from various problems (speed, bandwidth, accuracy) for extracting the cellular impedance information. This thesis proposes an improved system for extracting precise cellular impedance in real-time, with a wide bandwidth and satisfactory accuracy. The system hardware consists of five main parts: a microelectrode array (MEA), a stimulation circuit, a sensing circuit, a multi-function card and a computer. The development of system hardware is explored. Accordingly, a novel bioimpedance measurement method coined digital auto balancing bridge method, which is improved from the traditional analogue auto balancing bridge circuitry, is realized for real-time cellular impedance measurement. Two different digital bridge balancing algorithms are proposed and realized, which are based on least mean squares (LMS) algorithm and fast block LMS (FBLMS) algorithm for single- and multi-frequency measurements respectively. Details on their implementation in FPGA are discussed. The test results prove that the LMS-based algorithm is suitable for accelerating the measurement speed in single-frequency situation, whilst the FBLMS-based algorithm has advantages in stable convergence in multi-frequency applications. A novel algorithm, called the All Phase Fast Fourier Transform (APFFT), is applied for post-processing of bioimpedance measurement results. Compared with the classical FFT algorithm, the APFFT significantly reduces spectral leakage caused by truncation error. Compared to the traditional FFT and Digital Quadrature Demodulation (DQD) methods, the APFFT shows excellent performance for extracting accurate phase and amplitude in the frequency spectrum. Additionally, testing and evaluation of the realized system has been performed. The results show that our system achieved a satisfactory accuracy within a wide bandwidth, a fast measurement speed and a good repeatability. Furthermore, our system is compared with a commercial impedance analyzer (Agilent 4294A) in biological experiments. The results reveal that our system achieved a comparable accuracy to the commercial instrument in the biological experiments. Finally, conclusions are given and the future work is proposed

CMOS Design of Reconfigurable SoC Systems for Impedance Sensor Devices

La rápida evolución en el campo de los sensores inteligentes, junto con los avances en las tecnologías de la computación y la comunicación, está revolucionando la forma en que recopilamos y analizamos datos del mundo físico para tomar decisiones, facilitando nuevas soluciones que desempeñan tareas que antes eran inconcebibles de lograr.La inclusión en un mismo dado de silicio de todos los elementos necesarios para un proceso de monitorización y actuación ha sido posible gracias a los avances en micro (y nano) electrónica. Al mismo tiempo, la evolución de las tecnologías de procesamiento y micromecanizado de superficies de silicio y otros materiales complementarios ha dado lugar al desarrollo de sensores integrados compatibles con CMOS, lo que permite la implementación de matrices de sensores de alta densidad. Así, la combinación de un sistema de adquisición basado en sensores on-Chip, junto con un microprocesador como núcleo digital donde se puede ejecutar la digitalización de señales, el procesamiento y la comunicación de datos proporciona características adicionales como reducción del coste, compacidad, portabilidad, alimentación por batería, facilidad de uso e intercambio inteligente de datos, aumentando su potencial número de aplicaciones.Esta tesis pretende profundizar en el diseño de un sistema portátil de medición de espectroscopía de impedancia de baja potencia operado por batería, basado en tecnologías microelectrónicas CMOS, que pueda integrarse con el sensor, proporcionando una implementación paralelizable sin incrementar significativamente el tamaño o el consumo, pero manteniendo las principales características de fiabilidad y sensibilidad de un instrumento de laboratorio. Esto requiere el diseño tanto de la etapa de gestión de la energía como de las diferentes celdas que conforman la interfaz, que habrán de satisfacer los requisitos de un alto rendimiento a la par que las exigentes restricciones de tamaño mínimo y bajo consumo requeridas en la monitorización portátil, características que son aún más críticas al considerar la tendencia actual hacia matrices de sensores.A nivel de celdas, se proponen diferentes circuitos en un proceso CMOS de 180 nm: un regulador de baja caída de voltaje como unidad de gestión de energía, que proporciona una alimentación de 1.8 V estable, de bajo ruido, precisa e independiente de la carga para todo el sistema; amplificadores de instrumentación con una aproximación completamente diferencial, que incluyen una etapa de entrada de voltaje/corriente configurable, ganancia programable y ancho de banda ajustable, tanto en la frecuencia de corte baja como alta; un multiplicador para conformar la demodulación dual, que está embebido en el amplificador para optimizar consumo y área; y filtros pasa baja totalmente integrados, que actúan como extractores de magnitud de DC, con frecuencias de corte ajustables desde sub-Hz hasta cientos de Hz.<br /

A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

Bioimpedance sensors: a tutorial

Electrical bioimpedance entails the measurement of the electrical properties of tissues as a function of frequency. It is thus a spectroscopic technique. It has been applied in a plethora of biomedical applications for diagnostic and monitoring purposes. In this tutorial, the basics of electrical bioimpedance sensor design will be discussed. The electrode/electrolyte interface is thoroughly described, as well as methods for its modelling with equivalent circuits and computational tools. The design optimization and modelling of bipolar and tetrapolar bioimpedance sensors is presented in detail, based on the sensitivity theorem. Analytical and numerical modelling approaches for electric field simulations based on conformal mapping, point electrode approximations and the finite element method (FEM) are also elaborated. Finally, current trends on bioimpedance sensors are discussed followed by an overview of instrumentation methods for bioimpedance measurements, covering aspects of voltage signal excitations, current sources, voltage measurement front-end topologies and methods for computing the electrical impedance

Contact and remote breathing rate monitoring techniques: a review

ABSTRACT: Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients’ comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared

Advances in Integrated Circuits and Systems for Wearable Biomedical Electrical Impedance Tomography

Electrical impedance tomography (EIT) is an impedance mapping technique that can be used to image the inner impedance distribution of the subject under test. It is non-invasive, inexpensive and radiation-free, while at the same time it can facilitate long-term and real-time dynamic monitoring. Thus, EIT lends itself particularly well to the development of a bio-signal monitoring/imaging system in the form of wearable technology. This work focuses on EIT system hardware advancement using complementary metal oxide semiconductor (CMOS) technology. It presents the design and testing of application specific integrated circuit (ASIC) and their successful use in two bio-medical applications, namely, neonatal lung function monitoring and human-machine interface (HMI) for prosthetic hand control. Each year fifteen million babies are born prematurely, and up to 30% suffer from lung disease. Although respiratory support, especially mechanical ventilation, can improve their survival, it also can cause injury to their vulnerable lungs resulting in severe and chronic pulmonary morbidity lasting into adulthood, thus an integrated wearable EIT system for neonatal lung function monitoring is urgently needed. In this work, two wearable belt systems are presented. The first belt features a miniaturized active electrode module built around an analog front-end ASIC which is fabricated with 0.35-µm high-voltage process technology with ±9 V power supplies and occupies a total die area of 3.9 mm². The ASIC offers a high power active current driver capable of up to 6 mAp-p output, and wideband active buffer for EIT recording as well as contact impedance monitoring. The belt has a bandwidth of 500 kHz, and an image frame rate of 107 frame/s. To further improve the system, the active electrode module is integrated into one ASIC. It contains a fully differential current driver, a current feedback instrumentation amplifier (IA), a digital controller and multiplexors with a total die area of 9.6 mm². Compared to the conventional active electrode architecture employed in the first EIT belt, the second belt features a new architecture. It allows programmable flexible electrode current drive and voltage sense patterns under simple digital control. It has intimate connections to the electrodes for the current drive and to the IA for direct differential voltage measurement providing superior common-mode rejection ratio (CMRR) up to 74 dB, and with active gain, the noise level can be reduced by a factor of √3 using the adjacent scan. The second belt has a wider operating bandwidth of 1 MHz and multi-frequency operation. The image frame rate is 122 frame/s, the fastest wearable EIT reported to date. It measures impedance with 98% accuracy and has less than 0.5 Ω and 1° variation across all channels. In addition the ASIC facilitates several other functionalities to provide supplementary clinical information at the bedside. With the advancement of technology and the ever-increasing fusion of computer and machine into daily life, a seamless HMI system that can recognize hand gestures and motions and allow the control of robotic machines or prostheses to perform dexterous tasks, is a target of research. Originally developed as an imaging technique, EIT can be used with a machine learning technique to track bones and muscles movement towards understanding the human user’s intentions and ultimately controlling prosthetic hand applications. For this application, an analog front-end ASIC is designed using 0.35-µm standard process technology with ±1.65 V power supplies. It comprises a current driver capable of differential drive and a low noise (9μVrms) IA with a CMRR of 80 dB. The function modules occupy an area of 0.07 mm². Using the ASIC, a complete HMI system based on the EIT principle for hand prosthesis control has been presented, and the user’s forearm inner bio-impedance redistribution is assessed. Using artificial neural networks, bio-impedance redistribution can be learned so as to recognise the user’s intention in real-time for prosthesis operation. In this work, eleven hand motions are designed for prosthesis operation. Experiments with five subjects show that the system can achieve an overall recognition accuracy of 95.8%

Impedance Spectroscopy

This book covers new advances in the field of impedance spectroscopy including fundamentals, methods and applications. It releases selected extended and peer reviewed scientific contributions from the International Workshop on Impedance Spectroscopy (IWIS 2017) focussing on detailed information about recent scientific research results in electrochemistry and battery research, bioimpedance measurement, sensors, system design, signal processing

A Low Total Harmonic Distortion Sinusoidal Oscillator Based on Digital Harmonic Cancellation Technique

Sinusoidal oscillator is intensively used in many applications, such as built-in-self-testing and ADC characterization. An innovative medical application for skin cancer detection employed a technology named bio-impedance spectroscopy, which also requires highly linear sinusoidal-wave as the reference clock. Moreover, the generated sinusoidal signals should be tunable within the frequency range from 10kHz to 10MHz, and quadrature outputs are demanded for coherent demodulation within the system. A design methodology of sinusoidal oscillator named digital-harmonic-cancellation (DHC) technique is presented. DHC technique is realized by summing up a set of square-wave signals with different phase shifts and different summing coefficient to cancel unwanted harmonics. With a general survey of literature, some sinusoidal oscillators based on DHC technique are reviewed and categorized. Also, the mathematical algorithm behind the technique is explained, and non-ideality effect is analyzed based on mathematical calculation. The prototype is fabricated in OnSemi 0.5um CMOS technology. The experimental results of this work show that it can achieve HD2 is -59.74dB and HD3 is -60dB at 0.9MHz, and the frequency is tunable over 0.1MHz to 0.9MHz. The chip consumes area of 0.76mm2, and power consumption at 0.9MHz is 2.98mW. Another design in IBM 0.18um technology is still in the phase of design. The preliminary simulation results show that the 0.18um design can realize total harmonic distortion of -72dB at 10MHz with the power consumption of 0.4mW. The new design is very competitive with state-of-art, which will be finished with layout, submitted for fabrication and measured later

Graphene and Related Materials for the Internet of Bio-Nano Things

Internet of Bio-Nano Things (IoBNT) is a transformative communication framework, characterized by heterogeneous networks comprising both biological entities and artificial micro/nano-scale devices, so-called Bio-Nano Things (BNTs), interfaced with conventional communication networks for enabling innovative biomedical and environmental applications. Realizing the potential of IoBNT requires the development of new and unconventional communication technologies, such as molecular communications, as well as the corresponding transceivers, bio-cyber interfacing technologies connecting the biochemical domain of IoBNT to the electromagnetic domain of conventional networks, and miniaturized energy harvesting and storage components for the continuous power supply to BNTs. Graphene and related materials (GRMs) exhibit exceptional electrical, optical, biochemical, and mechanical properties, rendering them ideal candidates for addressing the challenges posed by IoBNT. This perspective article highlights recent advancements in GRM-based device technologies that are promising for implementing the core components of IoBNT. By identifying the unique opportunities afforded by GRMs and aligning them with the practical challenges associated with IoBNT, particularly in the materials domain, our aim is to accelerate the transition of envisaged IoBNT applications from theoretical concepts to practical implementations, while also uncovering new application areas for GRMs