Wideband Fully-Programmable Dual-Mode CMOS Analogue Front-End for Electrical Impedance Spectroscopy

This paper presents a multi-channel dual-mode CMOS analogue front-end (AFE) for electrochemical and bioimpedance analysis. Current-mode and voltage-mode readouts, integrated on the same chip, can provide an adaptable platform to correlate single-cell biosensor studies with large-scale tissue or organ analysis for real-time cancer detection, imaging and characterization. The chip, implemented in a 180-nm CMOS technology, combines two current-readout (CR) channels and four voltage-readout (VR) channels suitable for both bipolar and tetrapolar electrical impedance spectroscopy (EIS) analysis. Each VR channel occupies an area of 0.48 mm 2 , is capable of an operational bandwidth of 8 MHz and a linear gain in the range between -6 dB and 42 dB. The gain of the CR channel can be set to 10 kΩ, 50 kΩ or 100 kΩ and is capable of 80-dB dynamic range, with a very linear response for input currents between 10 nA and 100 μ A. Each CR channel occupies an area of 0.21 mm 2 . The chip consumes between 530 μ A and 690 μ A per channel and operates from a 1.8-V supply. The chip was used to measure the impedance of capacitive interdigitated electrodes in saline solution. Measurements show close matching with results obtained using a commercial impedance analyser. The chip will be part of a fully flexible and configurable fully-integrated dual-mode EIS system for impedance sensors and bioimpedance analysis

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

A Low Power Low Noise Instrumentation Amplifier For ECG Recording Applications

The instrumentation amplifier (IA) is one of the crucial blocks in an electrocardiogram recording system. It is the first block in the analog front-end chain that processes the ECG signal from the human body and thus it defines some of the most important specifications of the ECG system like the noise and common mode rejection ratio (CMRR). The extremely low ECG signal bandwidth also makes it difficult to achieve a fully integrated system. In this thesis, a fully integrated IA topology is presented that achieves low noise levels and low power dissipation. The chopper stabilized technique is implemented together with an AC coupled amplifier to reduce the effect of flicker noise while eliminating the effect of the differential electrode offset (DEO). An ultra low power operational transconductance amplifier (OTA) is the only active power consuming block in the IA and so an overall low power consumption is achieved. A new implementation of a large resistor using the T-network is presented which makes it easy to achieve a fully integrated solution. The proposed IA operates on a 2V supply and consumes a total current of 1.4µA while achieving an integrated noise of 1.2µVrms within the bandwidth. The proposed IA will relax the power and noise requirements of the analog-to-digital converter (ADC) that immediately follows it in the signal chain and thus reduce the cost and increase the lifetime of the recording device. The proposed IA has been implemented in the ONSEMI 0.5µm CMOS technology

Low power low noise analog front-end IC design for biomedical sensor interface

Ph.DDOCTOR OF PHILOSOPH

Development of a Micro Recording Probe for Measurements of Neuronal Activity in Freely Moving Animals

To discover general principles of biological sensorimotor control, insects have become remarkably successful model systems. In contrast to highly complex mammals, the functional organization of the insect nervous system in combination with a well-defined behavioural repertoire turned out to provide ideal conditions for quantitative studies into the neural control of behaviour. In addition, the search for biologically inspired control algorithms has further accelerated research into the neuronal mechanisms underlying flight and gaze stabilization, especially in blowflies. However, recording the neuronal activity in freely behaving insects, in particular in comparatively small insects such as blowflies, still imposes a major technical challenge. To date, electrophysiological recordings in unrestrained flies have never been achieved. This thesis describes the design and testing of a micro recording probe to be used for monitoring extracellular electrical activity in the nervous system of freely moving blowflies. In principle, this probe could also be used to study the neuronal control of behaviour in any other animal species the size of which is bigger than that of a blowfly. The nature of neuronal signals and the objective to record neuronal activity from behaving blowflies puts massive constraints on the specifications of the probe. I designed a differential amplifier with high gain, high linearity, low noise, and low power consumption. To fit the probe in the blowfly‟s head capsule and in direct contact with the animal‟s brain, the amplifier is on an unpackaged die. The neuronal signals are in the order of a few 100s of μV in amplitude. To be able to digitize such small signals >1000 times amplification is desirable. The small signal amplitudes also necessitate minimization of circuit noise. Linearity is necessary to prevent distortion of signal shape. Since connecting wires would impede movement of the animal, the probe would need to be powered by batteries. Therefore, low power is needed for two reasons: (i) to increase battery life, and therefore recording time, and (ii) because heat caused by power expenditure may damage the blowfly‟s brain or change its behaviour. To reduce power consumption I used CMOS transistors biased in the subthreshold region and a 2.2 V low power supply. The amplifier was characterized after fabrication by means of measuring its frequency response, linearity, and noise. I also recorded signals from a blowfly's brain and compared the performance of my recording probe with the performance of a high specification commercial amplifier in the time and frequency domains

VCO-based ADCs Design Techniques for Communication Systems

This work presents a novel technique to implement voltage-controlled oscillator based continuous-time Delta-Sigma analog-to-digital converters (VCO-based CT-ΔΣ ADCs) in closed-loop configuration. Over the past years there has been an upward trend in the use of these type of converters for instrumentation, audio and communication applications. The reason is that they are mostly digital and thus benefit from advances in deep-submicron CMOS processes. VCO-based ADCs have been widely studied in a great deal of papers and it is known that one of its main drawbacks is the non-linearity it presents. To overcome this issue, to place the VCO within a closed-loop is usually done to attenuate its input magnitude level. However, to do so it is needed a digital-to-analog converter (DAC) as in a conventional CT-ΔΣ, therefore it is required for the DAC to be simple and it cannot present a high number of elements, being the latter a bottleneck for implementing VCOs with a high number of inverters. This works presents a technique that enables to use VCOs with severals inverters while keeping the same number of DAC elements as before. Based upon previous theoretical studies of the VCO-based ADCs which model it as a pulse frequency modulation encoder, this new technique is analyzed and linear models are developed in order to study its viability at system level. Moreover, how impairments related to a real implementation affect the use of this technique are also analyzed. The contributions proposed in this document are focused but not limited to communication applications.Máster Universitario en Ingeniería de Sistemas Electrónicos y Aplicaciones. Curso 2018/201