17 research outputs found

    Noise Efficient Integrated Amplifier Designs for Biomedical Applications

    Get PDF
    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

    Integrated circuit design for implantable neural interfaces

    Get PDF
    Progress in microfabrication technology has opened the way for new possibilities in neuroscience and medicine. Chronic, biocompatible brain implants with recording and stimulation capabilities provided by embedded electronics have been successfully demonstrated. However, more ambitious applications call for improvements in every aspect of existing implementations. This thesis proposes two prototypes that advance the field in significant ways. The first prototype is a neural recording front-end with spectral selectivity capabilities that implements a design strategy that leads to the lowest reported power consumption as compared to the state of the art. The second one is a bidirectional front-end for closed-loop neuromodulation that accounts for self-interference and impedance mismatch thus enabling simultaneous recording and stimulation. The design process and experimental verification of both prototypes is presented herein

    Current efficient integrated architecture for common mode rejection sensitive neural recordings

    Get PDF
    In the last decade we have seen a significant growth of research and potential applications of electronic circuits that interact with the nervous system, in a wide range of applications, from basic neuroscience research to medical clinic, or from the entertainment industry to transport services. The real time acquisition and analysis of brain signals, either through wearable electroencephalography (EEG) or invasive or implantable recordings, in order to perform actions (brain machine interface) or to understand aspects of brain operation, has become scientifically and technologically feasible. This thesis aims to support neural recording applications with low noise, currentefficiency and high common-mode rejection ratio (CMRR) as main features of the recording system. One emblematic example of these applications in the neuroscience domain is the weakly electric fish neural activity recording, where the interference produced by the discharge of the fish electric organ is a key factor. Another example, from the implantable devices domain, is the nerve activity recorded with cuff electrodes, where the desired signal is interfered by electromyographic potentials generated by muscles near the cuff. In these cases, the amplitude of the interfering signals, which mainly appear in common mode, is several orders of magnitude higher than the amplitude of the signals of interest. Therefore, this thesis introduces a novel integrated neural preamplifier architecture targeting CMRR sensitive neural recording applications. The architecture is presented and analyzed in depth, deriving the preamplifier transfer function and the main design equations. We present a detailed analysis of a technique for blocking the input dc component and setting the high-pass frequency without using MOS pseudo-resistors. One of the main contributions of this work is the overall architecture coupled with an efficient and simple single-stage circuit for the preamplifier main transconductor. A fully-integrated neural preamplifier, which performs well in line with the state-ofthe-art of the field while providing enhanced CMRR performance, was fabricated in a 0.5 um CMOS process. Results from measurements show that the measured gain is 49.5 dB, bandwidth ranges from 13 Hz to 9.8 kHz, CMRR is very high (greater than 87 dB), and it is achieved jointly with a remarkable low noise (1.88 uVrms) and current-efficiency (NEF = noise efficiency factor = 2.1). A second version of the preamplifier with one external capacitor achieves a high-pass frequency of 0.1 Hz while keeping the performance of the fully-integrated version. In addition, we present in-vivo measurements made with the proposed architecture in a weakly electric fish (Gymnotus omarorum), showing the ability of the preamplifier to acquire neural signals from high amplitude common mode interference in an unshielded environment. This was the first in-vivo testing of a neural recording integrated circuit designed in Uruguay done in a local lab. Furthermore, signals recorded with our unshielded low-power battery-powered preamplifier perfectly match with those of a shielded commercially-available amplifier (ac-plugged, without power restrictions). To the best of our knowledge, the proposed preamplifier is the best option for applications that simultaneously need low noise, high CMRR and current-efficiency. Furthermore, in this thesis we applied the aforementioned architecture to bandpass biquad filters, specially but not only, to those with differential input. The new architecture provides a significant reduction in consumption (up to 30%) and/or makes it possible to block a higher level of dc at the input (up to the double, without using decoupling capacitors). Next, we applied the novel architecture to the design of the different stages of an integrated programmable analog front-end. Results from simulations shows that the gain is programmable between 57 dB and 99 dB, the low-pass frequency is programmable between 116 Hz and 5.2 kHz, the maximum power consumption is 11.2 uA and the maximum equivalent input-referred noise voltage is 1.87 uVrms. The comparison between our front-end and other works in the state-of-the-art shows that our front-end presents the best results in terms of CMRR and noise, has the greatest value of gain and equals the best NEF reported. Finally, some system-level topics were addressed during this thesis, including the design and implementation of three prototypes of end-to-end wireless biopotentials recording systems based on off-the-shelf components. Developing and applying circuits, systems and methods, for synchronized largescale monitoring of neural activity, sensory images, and behavior, would produce a dynamic picture of the brain function, which is essential for understanding the brain in action. In this context, we hope that the present thesis become our first step to further contribute to this area

    VLSI Circuits for Bidirectional Neural Interfaces

    Get PDF
    Medical devices that deliver electrical stimulation to neural tissue are important clinical tools that can augment or replace pharmacological therapies. The success of such devices has led to an explosion of interest in the field, termed neuromodulation, with a diverse set of disorders being targeted for device-based treatment. Nevertheless, a large degree of uncertainty surrounds how and why these devices are effective. This uncertainty limits the ability to optimize therapy and gives rise to deleterious side effects. An emerging approach to improve neuromodulation efficacy and to better understand its mechanisms is to record bioelectric activity during stimulation. Understanding how stimulation affects electrophysiology can provide insights into disease, and also provides a feedback signal to autonomously tune stimulation parameters to improve efficacy or decrease side-effects. The aims of this work were taken up to advance the state-of-the-art in neuro-interface technology to enable closed-loop neuromodulation therapies. Long term monitoring of neuronal activity in awake and behaving subjects can provide critical insights into brain dynamics that can inform system-level design of closed-loop neuromodulation systems. Thus, first we designed a system that wirelessly telemetered electrocorticography signals from awake-behaving rats. We hypothesized that such a system could be useful for detecting sporadic but clinically relevant electrophysiological events. In an 18-hour, overnight recording, seizure activity was detected in a pre-clinical rodent model of global ischemic brain injury. We subsequently turned to the design of neurostimulation circuits. Three critical features of neurostimulation devices are safety, programmability, and specificity. We conceived and implemented a neurostimulator architecture that utilizes a compact on-chip circuit for charge balancing (safety), digital-to-analog converter calibration (programmability) and current steering (specificity). Charge balancing accuracy was measured at better than 0.3%, the digital-to-analog converters achieved 8-bit resolution, and physiological effects of current steering stimulation were demonstrated in an anesthetized rat. Lastly, to implement a bidirectional neural interface, both the recording and stimulation circuits were fabricated on a single chip. In doing so, we implemented a low noise, ultra-low power recording front end with a high dynamic range. The recording circuits achieved a signal-to-noise ratio of 58 dB and a spurious-free dynamic range of better than 70 dB, while consuming 5.5 μW per channel. We demonstrated bidirectional operation of the chip by recording cardiac modulation induced through vagus nerve stimulation, and demonstrated closed-loop control of cardiac rhythm

    Development and modelling of a versatile active micro-electrode array for high density in-vivo and in-vitro neural signal investigation

    Get PDF
    The electrophysiological observation of neurological cells has allowed much knowledge to be gathered regarding how living organisms are believed to acquire and process sensation. Although much has been learned about neurons in isolation, there is much more to be discovered in how these neurons communicate within large networks. The challenges of measuring neurological networks at the scale, density and chronic level of non invasiveness required to observe neurological processing and decision making are manifold, however methods have been suggested that have allowed small scale networks to be observed using arrays of micro-fabricated electrodes. These arrays transduce ionic perturbations local to the cell membrane in the extracellular fluid into small electrical signals within the metal that may be measured. A device was designed for optimal electrical matching to the electrode interface and maximal signal preservation of the received extracellular neural signals. Design parameters were developed from electrophysiological computer simulations and experimentally obtained empirical models of the electrode-electrolyte interface. From this information, a novel interface based signal filtering method was developed that enabled high density amplifier interface circuitry to be realised. A novel prototype monolithic active electrode was developed using CMOS microfabrication technology. The device uses the top metallization of a selected process to form the electrode substrate and compact amplification circuitry fabricated directly beneath the electrode to amplify and separate the neural signal from the baseline offsets and noise of the electrode interface. The signal is then buffered for high speed sampling and switched signal routing. Prototype 16 and 256 active electrode array with custom support circuitry is presented at the layout stage for a 20 μm diameter 100 μm pitch electrode array. Each device consumes 26.4 μW of power and contributes 4.509 μV (rms) of noise to the received signal over a controlled bandwidth of 10 Hz - 5 kHz. The research has provided a fundamental insight into the challenges of high density neural network observation, both in the passive and the active manner. The thesis concludes that power consumption is the fundamental limiting factor of high density integrated MEA circuitry; low power dissipation being crucial for the existence of the surface adhered cells under measurement. With transistor sizing, noise and signal slewing each being inversely proportional to the dc supply current and the large power requirements of desirable ancillary circuitry such as analogue-to-digital converters, a situation of compromise is approached that must be carefully considered for specific application design

    Biosensor system with an integrated CMOS microelectrode array for high spatio-temporal electrochemical imaging, A

    Get PDF
    2019 Fall.Includes bibliographical references.The ability to view biological events in real time has contributed significantly to research in life sciences. While optical microscopy is important to observe anatomical and morphological changes, it is equally important to capture real-time two-dimensional (2D) chemical activities that drive the bio-sample behaviors. The existing chemical sensing methods (i.e. optical photoluminescence, magnetic resonance, and scanning electrochemical), are well-established and optimized for existing ex vivo or in vitro analyses. However, such methods also present various limitations in resolution, real-time performance, and costs. Electrochemical method has been advantageous to life sciences by supporting studies and discoveries in neurotransmitter signaling and metabolic activities in biological samples. In the meantime, the integration of Microelectrode Array (MEA) and Complementary-Metal-Oxide-Semiconductor (CMOS) technology to the electrochemical method provides biosensing capabilities with high spatial and temporal resolutions. This work discusses three related subtopics in this specific order: improvements to an electrochemical imaging system with 8,192 sensing points for neurotransmitter sensing; comprehensive design processes of an electrochemical imaging system with 16,064 sensing points based on the previous system; and the application of the system for imaging oxygen concentration gradients in metabolizing bovine oocytes. The first attempt of high spatial electrochemical imaging was based on an integrated CMOS microchip with 8,192 configurable Pt surface electrodes, on-chip potentiostat, on-chip control logic, and a microfluidic device designed to support ex vivo tissue experimentation. Using norepinephrine as a target analyte for proof of concept, the system is capable of differentiating concentrations of norepinephrine as low as 8µM and up to 1,024 µM with a linear response and a spatial resolution of 25.5×30.4μm. Electrochemical imaging was performed using murine adrenal tissue as a biological model and successfully showed caffeine-stimulated release of catecholamines from live slices of adrenal tissue with desired spatial and temporal resolutions. This system demonstrates the capability of an electrochemical imaging system capable of capturing changes in chemical gradients in live tissue slices. An enhanced system was designed and implemented in a CMOS microchip based on the previous generation. The enhanced CMOS microchip has an expanded sensing area of 3.6×3.6mm containing 16,064 Pt electrodes and the associated 16,064 integrated read channels. The novel three-electrode electrochemical sensor system designed at 27.5×27.5µm pitch enables spatially dense cellular level chemical gradient imaging. The noise level of the on-chip read channels allow amperometric linear detection of neurotransmitter (norepinephrine) concentrations from 4µM to 512µM with 4.7pA/µM sensitivity (R=0.98). Electrochemical response to dissolved oxygen concentration or oxygen partial pressure (pO2) was also characterized with deoxygenated deionized water containing 10µM to 165 µM pO2 with 8.21pA/µM sensitivity (R=0.89). The enhanced biosensor system also demonstrates selectivity to different target analytes using cyclic voltammetry to simultaneously detect NE and uric acid. In addition, a custom-designed indium tin oxide and Au glass electrode is integrated into the microfluidic support system to enable pH measurement, ensuring viability of bio-samples in ex vivo experiments. Electrochemical images confirm the spatiotemporal performance at four frames per second while maintaining the sensitivity to target analytes. The overall system is controlled and continuously monitored by a custom-designed user interface, which is optimized for real-time high spatiotemporal resolution chemical bioimaging. It is well known that physiological events related to oxygen concentration gradients provide valuable information to determine the state of metabolizing biological cells. Utilizing the CMOS microchip with 16,064 Pt MEA and an improved three-electrode system configuration, the system is capable of imaging low oxygen concentration with limit of detection of 18.3µM, 0.58mg/L, or 13.8mmHg. A modified microfluidic support system allows convenient bio-sample handling and delivery to the MEA surface for sensing. In vitro oxygen imaging experiments were performed using bovine cumulus-oocytes-complexes cells with custom software algorithms to analyze its flux density and oxygen consumption rate. The imaging results are processed and presented as 2D heatmaps, representing the dissolved oxygen concentration in the immediate proximity of the cell. The 2D images and analysis of oxygen consumption provide a unique insight into the spatial and temporal dynamics of cell metabolism

    Modulated Backscatter for Low-Power High-Bandwidth Communication

    Get PDF
    <p>This thesis re-examines the physical layer of a communication link in order to increase the energy efficiency of a remote device or sensor. Backscatter modulation allows a remote device to wirelessly telemeter information without operating a traditional transceiver. Instead, a backscatter device leverages a carrier transmitted by an access point or base station.</p><p>A low-power multi-state vector backscatter modulation technique is presented where quadrature amplitude modulation (QAM) signalling is generated without running a traditional transceiver. Backscatter QAM allows for significant power savings compared to traditional wireless communication schemes. For example, a device presented in this thesis that implements 16-QAM backscatter modulation is capable of streaming data at 96 Mbps with a radio communication efficiency of 15.5 pJ/bit. This is over 100x lower energy per bit than WiFi (IEEE 802.11).</p><p>This work could lead to a new class of high-bandwidth sensors or implantables with power consumption far lower than traditional radios.</p>Dissertatio
    corecore