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

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

HIGH-PERFORMANCE PERIODIC ANTENNAS WITH HIGH ASPECT RATIO VERTICAL FEATURES AND LARGE INTERCELL CAPACITANCES FOR MICROWAVE APPLICATIONS

Modern communications systems are evolving rapidly to address the demand for data exchange, a fact which imposes stringent requirements on the design process of their RF and antenna front-ends. The most crucial pressure on the antenna front-end is the need for miniaturized design solutions while maintaining the desired radiation performance. To satisfy this need, this thesis presents innovative types of periodic antennas, including electromagnetic bandgap (EBG) antennas, which are distinguished in two respects. First, the periodic cells contain thick metal traces, contrary to the conventional thin-trace cells. Second, such thick traces contain very narrow gaps with very tall sidewalls, referred to as high aspect ratio (HAR) gaps. When such cells are used in the structure of the proposed periodic antennas, the high capacitance of HAR gaps decreases the resonance frequency, mitigates conduction loss, and thus, yields considerably small high efficiency antennas. For instance, one of the sample antenna designs with only two EBG cells offers a very small XYZ volume of 0.25λ×0.28λ×0.037λ with efficiency of 83%. Also, a circularly polarized HAR EBG antenna is presented which has a footprint as small as 0.26λ×0.29λ and efficiency as high as 94%. The main analysis method developed in this thesis is a combination of numerical and mathematical analyses and is referred to as HFSS/Bloch method. The numerical part of this method is conducted using a High Frequency Structure Simulator (HFSS), and the mathematical part is based on the classic Bloch theory. The HFSS/Bloch method acts as the mainstay of the thesis and all designs are built upon the insight provided by this method. A circuit model using transmission line (TL) theory is also developed for some of the unit cells and antennas. The HFSS/Bloch perspective results in a HAR EBG TL with radiation properties, a fragment of which (2 to 6 cells) is introduced as a novel antenna, the self-excited EBG resonator antenna (SE-EBG-RA). Open (OC) and short circuited (SC) versions of this antenna are studied and the inherently smaller size of the SC version is demonstrated. Moreover, the possibility of employing the SE-EBG-RA as the element of a series-fed array structure is investigated and some sample high-efficiency, flat array antennas are rendered. A microstrip antenna is also developed, the structure of which is composed of 3×3 unit cells and shows fast-wave behaviors. Most antenna designs are resonant in nature; however, in one case, a low-profile efficient leaky-wave antenna with scanning radiation pattern is proposed. Several antenna prototypes are fabricated and tested to validate the analyses and designs. As the structures are based on tall metal traces, two relevant fabrication methods are considered, including CNC machining and deep X-ray lithography (DXRL). Hands-on experiments provide an outlook of possible future DXRL fabricated SE-EBG-RAs

Micromachined three-dimensional electrode arrays for in-vitro and in-vivo electrogenic cellular networks

This dissertation presents an investigation of micromachined three-dimensional microelectrode arrays (3-D MEAs) targeted toward in-vitro and in-vivo biomedical applications. Current 3-D MEAs are predominantly silicon-based, fabricated in a planar fashion, and are assembled to achieve a true 3-D form: a technique that cannot be extended to micro-manufacturing. The integrated 3-D MEAs developed in this work are polymer-based and thus offer potential for large-scale, high volume manufacturing. Two different techniques are developed for microfabrication of these MEAs - laser micromachining of a conformally deposited polymer on a non-planar surface to create 3-D molds for metal electrodeposition; and metal transfer micromolding, where functional metal layers are transferred from one polymer to another during the process of micromolding thus eliminating the need for complex and non-repeatable 3-D lithography processes. In-vitro and in-vivo 3-D MEAs are microfabricated using these techniques and are packaged utilizing Printed Circuit Boards (PCB) or other low-cost manufacturing techniques. To demonstrate in-vitro applications, growth of 3-D co-cultures of neurons/astrocytes and tissue-slice electrophysiology with brain tissue of rat pups were implemented. To demonstrate in-vivo application, measurements of nerve conduction were implemented. Microelectrode impedance models, noise models and various process models were evaluated. The results confirmed biocompatibility of the polymers involved, acceptable impedance range and noise of the microelectrodes, and potential to improve upon an archaic clinical diagnostic application utilizing these 3-D MEAs.Ph.D.Committee Chair: Mark G. Allen; Committee Member: Elliot L. Chaikof; Committee Member: Ionnis (John) Papapolymerou; Committee Member: Maysam Ghovanloo; Committee Member: Oliver Bran

Flexible adaptation of iterative learning control with applications to synthetic bone graft manufacturing

Additive manufacturing processes are powerful tools; they are capable of fabricating structures without expensive structure specific tooling -- therefore structure designs can efficiently change from run-to-run -- and they can integrate multiple distinct materials into a single structure. This work investigates one such additive manufacturing process, micro-Robotic Deposition ($\mu$RD), and its utility in fabricating advanced architecture synthetic bone grafts. These bone grafts, also known as synthetic bone scaffolds, are highly porous three-dimensional structures that provide a matrix to support the natural process of bone remodeling. Ideally, the synthetic scaffold will stimulate complete bone healing in a skeletal defect site and also resorb with time so that only natural tissue remains. The objective of this research is to develop methods to integrate different regions with different porous microstructures into a single scaffold; there is evidence that scaffolds with designed regions of specific microstructures can be used to elicit a strong and directed bone ingrowth response that improves bone ingrowth rate and quality. The key contribution of this work is the development of a control algorithm that precisely places different build materials in specified locations, thereby the fabrication of advanced architecture scaffolds is feasible. Under previous control methods, designs were relegated to be composed of a single material. The control algorithm developed in this work is an adaptation of Iterative Learning Control (ILC), a control method that is typically best suited for mass manufacturing applications. This adaptation reorients the ILC framework such that it is more amenable to additive manufacturing systems, such as $\mu$RD. Control efficacy is demonstrated by the fabrication of advanced architecture scaffolds. Scaffolds with contoured forms, multiple domains with distinct porous microstructures, and hollow cavities are feasible when the developed controller is used in conjunction with a novel manufacturing workflow in which scaffolds are filled within patterned molds that support overhanging features. An additional application demonstrates controller performance on the robot positioning problem; this work has implications for additive manufacturing in general

Intrinsic and Extrinsic Biomechanical Factors in a Co-adaptive ECoG-based Brain Computer Interface

Paralysis, due to spinal cord injury, amyotrophic lateral sclerosis (ALS), or stroke, is the result of severed communication between the brain and the motor periphery. Brain computer interfaces (BCIs) are neuroprosthetic devices that create novel communication pathways by measuring and transforming neural activity into operational commands. State of the art BCI systems measure brain activity using penetrating electrode arrays able to record from hundreds of individual cortical neurons simultaneously. Unfortunately, these systems are highly susceptible to signal degradation which limits their efficacy to 1-2 years. However, electrocorticography (ECoG) signals recorded from the surface of the brain deliver a more competitive balance between surgical risk, long-term stability, signal bandwidth, and signal-to-noise ratio when compared to both the aforementioned intracortical systems and the more common non-invasive electroencephalography (EEG) technologies. Historically, neural signals for controlling a computer cursor or robotic arm have been mapped to extrinsic, kinematic (i.e. position or velocity) variables. Although this strategy is adequate for use in simple environments, it may not be ideal for control of real-world prosthetic devices that are subject to external and unexpected forces. When reaching for an object, the trajectory of the hand through space can be defined in either extrinsic (e.g. Cartesian) or intrinsic (e.g. joint angles, muscle forces) frames of reference. During this movement, the brain has to perform a series of sensorimotor transformations that involve solving a complex, 2nd order differential equation (i.e. musculoskeletal biomechanics) in order to determine the appropriate muscle activations. Functional neuromuscular stimulation (FNS) is a desirable BCI application because it attempts to restore motor function to paralyzed limbs through electrical excitation of muscles. Rather than applying the conventional extrinsic kinematic control signals to such a system, it may be more appropriate to map neural activity to muscle activation directly and allow the brain to develop its own transfer function. This dissertation examines the application of intrinsic decoding schemes to control an upper limb using ECoG in non-human primates. ECoG electrode arrays were chronically implanted in rhesus monkeys over sensorimotor cortex. A novel multi-joint reaching task was developed to train the subjects to control a virtual arm simulating muscle and inertial forces. Utilizing a co-adaptive algorithm (where both the brain adapts via biofeedback and the decoding algorithm adapts to improve performance), new decoding models were initially built over the course of the first 3-5 minutes of each daily experimental session and then continually adapted throughout the day. Three subjects performed the task using neural control signals mapped to 1) joint angular velocity, 2) joint torque, and 3) muscle forces of the virtual arm. Performance exceeded 97%, 93%, and 89% accuracy for the three control paradigms respectively. Neural control features in the upper gamma frequency bands (70-115 and 130-175 Hz) were found to be directionally tuned in an ordered fashion, with preferred directions varying topographically in the mediolateral direction without distinction between motor and sensory areas. Long-term stability was demonstrated by all three monkeys, which maintained performance at 42, 55, and 57 months post-implantation. These results provide insights into the capabilities of sensorimotor cortex for control of non-linear multi-joint reaching dynamics and present a first step toward design of intrinsic, force-based BCI systems suitable for long-term FNS applications

Brain-Computer Interfaces using Electrocorticography and Surface Stimulation

The brain connects to, modulates, and receives information from every organ in the body. As such, brain-computer interfaces (BCIs) have vast potential for diagnostics, medical therapies, and even augmentation or enhancement of normal functions. BCIs provide a means to explore the furthest corners of what it means to think, to feel, and to act—to experience the world and to be who you are. This work focuses on the development of a chronic bi-directional BCI for sensorimotor restoration through the use of separable frequency bands for recording motor intent and providing sensory feedback via electrocortical stimulation. Epidural cortical surface electrodes are used to both record electrocorticographic (ECoG) signals and provide stimulation without adverse effects associated with penetration through the protective dural barrier of brain. Chronic changes in electrode properties and signal characteristics are discussed, which inform optimal electrode designs and co-adaptive algorithms for decoding high-dimensional information. Additionally, a multi-layered approach to artifact suppression is presented, which includes a systems-level design of electronics, signal processing, and stimulus waveforms. The results of this work are relevant to a wider range of applications beyond ECoG and BCIs that involve closed-loop recording and stimulation throughout the body. By enabling simultaneous recording and stimulation through the techniques described here, responsive therapies can be developed that are tuned to individual patients and provide precision therapies at exactly the right place and time. This has the potential to improve targeted therapeutic outcomes while reducing undesirable side effects

Offset Electrodes for Enhanced Neural Recording in Microchannels

Microchannel electrodes have emerged in recent years as promising interfaces for recording signals in peripheral nerves. Unlike many technologies, microchannels maintain stable long-term connections and can record activity in individual or small groups of axons. Unfortunately, a traditional symmetrical mid-channel electrode configuration, designed to reduce noise artifacts, prevents microchannels from being used to distinguish between signals traveling in opposite directions. This is a profound limitation given that most nerves contain a mix of efferent and afferent axons and microchannels were initially conceived and later used as the basic building block in arrays designed to record bi-directional neural traffic in regenerated nerve fibers. Off-center, or “offset”, recording sites have been predicted to record larger signals than mid-channel locations. Unlike the mid-channel configuration, offset electrode asymmetry suggests it has the capacity to differentiate between efferent and afferent neural activity. Despite these apparent advantages, a theoretical basis for signal enhancement at offset locations has not been identified and, to our knowledge, no efforts to leverage offset electrodes for signal enhancement or discrimination in microchannels have been undertaken. This work provides a theoretical basis to explain signal enhancement at offset electrodes. The theory is used to explore offset electrode configurations that maximize signal amplitudes and enhance differences between signals traveling in opposite directions. Neural recordings are used to validate theoretical predictions and to explore novel reference configurations that seek to minimize noise artifacts. Key shape differences between signals recorded for action potentials traveling in opposite directions are characterized and exploited to further enhance signal discrimination at offset electrodes, as well as to reduce the rate of overlapping spikes in more complex neural recording scenarios, including compound action potentials. Overall, this work introduces the offset electrode configuration as a new paradigm for recording signals in peripheral nerves and provides a foundation for the development of future devices with enhanced performance and signal discrimination capabilities.Off-center, or “offset”, recording sites have been predicted to record larger signals than mid-channel locations. Unlike mid-channel electrodes, offset electrode asymmetry suggests they have the capacity to differentiate between efferent and afferent neural activity. Despite these apparent advantages, the theoretical underpinnings for signal enhancement at offset locations has not been identified and, to our knowledge, no efforts have been made to leverage offset electrodes for signal enhancement or discrimination in microchannels. This work provides a theoretical basis to explain signal enhancement at offset electrodes. The theory is used to explore and identify offset electrode configurations that maximize signal amplitudes and seek to enhance differences between signals traveling in opposite direction. Neural recordings in microchannels containing optimally-positioned offset electrodes are used to validate theoretical predictions and to explore novel reference configurations for minimizing noise artifacts. Shape differences between signals recorded at mid-channel and offset locations are characterized and exploited to further enhance signal discrimination at offset electrodes for single units and reduce the rate of overlapping spikes in more complex multi-unit spike trains as well as the compound action potential. Overall, this work demonstrates a new paradigm for neural recording in microchannels that provides a foundation for the development of future devices with enhanced performance and signal discrimination capabilities

UWB Technology

Ultra Wide Band (UWB) technology has attracted increasing interest and there is a growing demand for UWB for several applications and scenarios. The unlicensed use of the UWB spectrum has been regulated by the Federal Communications Commission (FCC) since the early 2000s. The main concern in designing UWB circuits is to consider the assigned bandwidth and the low power permitted for transmission. This makes UWB circuit design a challenging mission in today's community. Various circuit designs and system implementations are published in this book to give the reader a glimpse of the state-of-the-art examples in this field. The book starts at the circuit level design of major UWB elements such as filters, antennas, and amplifiers; and ends with the complete system implementation using such modules

Micro-electro-opto-fluidic systems for biomedical drug screening and electromagnetic filtering and cloaking applications

Microfluidic is a multidisciplinary field that deals with the flow of liquid inside micro-meter size channels. In order to be considered as microfluidics, at least one dimension of the channel should be in the range of one micrometer or sub-millimeter. Microfluidic technology includes designing, manufacturing, formulating devices and processing the liquid. As numerous bio-science and engineering techniques have utilized microfluidics and highly integrated with this remarkable technology, the microfluidic platform technology has extended to several sub-techs: micro-scale analysis, soft-lithography fabrication, polymer science and processing, on-chip sensing and micro-scale fluid manipulation. Those sub-techs have been developed rapidly along with the booming microfluidics. The advance of those techniques has promoted microfluidic system diverse and widespread applications. Some examples that employ this technology include on-chip drug screening, micro-scale analysis, flexible electronics, biochemical assays. Many engineering field, such as optics, electronics, chemicals and electromagnetics, have been integrated with the microfluidic system to form a completed system for sensing, analyzing or realizing some specific applications. Through the fusion of those technologies with microfluidics, many emerging technologies are well initiated, such as optofluidics and electrofluidics. Despite of rapid advancement of each parent technology field, those intersected technologies are still in their infancy and many technological elements and even some fundamental concepts are just now being developed. Thus, it provides great opportunity to explore more about those emerging technologies. Some particular areas that mainly interest researchers including cost deduction, effective fabrication, highly integration, portability and applicability. Due to the wide and diversity nature of the microfluidic technology and numerous combinations from the integration with other fields, it is very difficult to choose a single aspect or particular subject to research. Hence, we would like to focus on the application orientated microfluidic techniques that integrated with other engineering areas, in particular optics and electronics. Correspondingly, I will present four microfluidic platforms that integrated with optics, electronics for different application purpose. First of all, fiber-optics was integrated into a microfluidic device to detect muscular force generation of microscopic nematodes. The integrated opto-fluidic device is capable of measuring the muscular force of nematode worms normal to the translational movement direction with high sensitivity, high data reliability, and simple device structure. The ability to quantify the muscular forces of small nematode worms will provide a new approach for screening mutants at single animal resolution. Secondly, electronic grids were integrated into a microfluidic chip to realize on-chip tracking of nematode locomotion. The micro-electro-fluidic approach is capable of real-time lens-less and image-sensor-less monitoring of the locomotion of microscopic nematodes. The technology showed promise for overcoming the constraint of the limited field of view of conventional optical microscopy, with relatively low cost, good spatial resolution, and high portability. Thirdly, electromagnetic spit ring resonator (SRR) structure was adopted as microfluidic channel filled with liquid metal to fabricate a tunable microfluidic microwave electronics called meta-atom. The presented meta-atom is capable of tuning its electromagnetic (EM) response characteristics over a broad frequency range via simple mechanical stretching. The meta-atom in this study presents a simple but effective building block for realizing mechanically tunable metamaterials. Finally, based on the meta-atom we previously developed, an array of electromagnetic SRR shaped microfluidic channels filled with liquid metal to form a flexible metamaterial-based microwave electronic “skin” or meta-skin. When stretched, the meta-skin performs as a tunable frequency selective surface with a wide resonance frequency tuning range. When wrapped around a curved dielectric material, the meta-skin functions as a flexible “cloaking” surface to significantly suppress scattering from the surface of the dielectric material along different directions. The microfluidic platform will find great applications when it integrates with other technologies. The development of such integration will greatly intersect different research areas and benefit all of the intersected technologies and fields, thus broadening the future applications