Development Of Carbon Based Neural Interface For Neural Stimulation/recording And Neurotransmitter Detection

Electrical stimulation and recording of neural cells have been widely used in basic neuroscience studies, neural prostheses, and clinical therapies. Stable neural interfaces that effectively communicate with the nervous system via electrodes are of great significance. Recently, flexible neural interfaces that combine carbon nanotubes (CNTs) and soft polymer substrates have generated tremendous interests. CNT based microelectrode arrays (MEAs) have shown enhanced electrochemical properties compared to commonly used electrode materials such as tungsten, platinum or titanium nitride. On the other hand, the soft polymer substrate can overcome the mechanical mismatch between the traditional rigid electrodes (or silicon shank) and the soft tissues for chronic use. However, most fabrication techniques suffer from low CNT yield, bad adhesion, and limited controllability. In addition, the electrodes were covered by randomly distributed CNTs in most cases. In this study, a novel fabrication method combining XeF2 etching and parylene deposition was presented to integrate the high quality vertical CNTs grown at high temperature with the heat sensitive parylene substrate in a highly controllable manner. Lower stimulation threshold voltage and higher signal to noise ratio have been demonstrated using vertical CNTs bundles compared to a Pt electrode and other randomly distributed CNT films. Adhesion has also been greatly improved. The work has also been extended to develop cuff shaped electrode for peripheral nerve stimulation. Fast scan cyclic voltammetry is an electrochemical detection technique suitable for in-vivo neurotransmitter detection because of the miniaturization, fast time response, good sensitivity and selectivity. Traditional single carbon fiber microelectrode has been limited to single detection for in-vivo application. Alternatively, pyrolyzed photoresist film (PPF) is a good candidate for this application as they are readily compatible with the microfabrication process for precise fabrication of microelectrode arrays. By the oxygen plasma treatment of photoresist prior to pyrolysis, we obtained carbon fiber arrays. Good sensitivity in dopamine detection by this carbon fiber arrays and improved adhesion have been demonstrated

Advances in Bioengineering

The technological approach and the high level of innovation make bioengineering extremely dynamic and this forces researchers to continuous updating. It involves the publication of the results of the latest scientific research. This book covers a wide range of aspects and issues related to advances in bioengineering research with a particular focus on innovative technologies and applications. The book consists of 13 scientific contributions divided in four sections: Materials Science; Biosensors. Electronics and Telemetry; Light Therapy; Computing and Analysis Techniques

Intra-Cortical Microelectrode Arrays for Neuro-Interfacing

Neuro-engineering is an emerging multi-disciplinary domain which investigates the electrophysiological activities of the nervous system. It provides procedures and techniques to explore, analyze and characterize the functions of the different components comprising the nervous system. Neuro-engineering is not limited to research applications; it is employed in developing unconventional therapeutic techniques for treating different neurological disorders and restoring lost sensory or motor functions. Microelectrodes are principal elements in functional electric stimulation (FES) systems used in electrophysiological procedures. They are used in establishing an interface with the individual neurons or in clusters to record activities and communications, as well as modulate neuron behaviour through stimulation. Microelectrode technologies progressed through several modifications and innovations to improve their functionality and usability. However, conventional electrode technologies are open to further development, and advancement in microelectrodes technology will progressively meliorate the neuro-interfacing and electrotherapeutic techniques. This research introduced design methodology and fabrication processes for intra-cortical microelectrodes capable of befitting a wide range of design requirements and applications. The design process was employed in developing and implementing an ensemble of intra-cortical microelectrodes customized for different neuro-interfacing applications. The proposed designs presented several innovations and novelties. The research addressed practical considerations including assembly and interconnection to external circuitry. The research was concluded by exhibiting the Waterloo Array which is a high channel count flexible 3-D neuro-interfacing array. Finally, the dissertation was concluded by demonstrating the characterization, in vitro and acute in vivo testing results of the Waterloo Array. The implemented electrodes were tested and benchmarked against commercial equivalents and the results manifested improvement in the electrode performance compared to conventional electrodes. Electrode testing and evaluation were conducted in the Krembil Neuroscience Centre Research Lab (Toronto Western Hospital), and the Neurosciences & Mental Health Research Institute (the Sick Kids hospital). The research results and outcomes are currently being employed in developing chronic intra-cortical and electrocorticography (ECoG) electrode arrays for the epilepsy research and rodents nervous system investigations. The introduced electrode technologies will be used to develop customized designs for the clinical research labs collaborating with CIRFE Lab.1 yea

De animais a máquinas : humanos tecnicamente melhores nos imaginários de futuro da convergência tecnológica

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Sociais, Departamento de Sociologia, 2020.O tema desta investigação é discutir os imaginários sociais de ciência e tecnologia que emergem a partir da área da neuroengenharia, em sua relação com a Convergência Tecnológica de quatro disciplinas: Nanotecnologia, Biotecnologia, tecnologias da Informação e tecnologias Cognitivas - neurociências- (CT-NBIC). Estas áreas desenvolvem-se e são articuladas por meio de discursos que ressaltam o aprimoramento das capacidades físicas e cognitivas dos seres humanos, com o intuito de construir uma sociedade melhor por meio do progresso científico e tecnológico, nos limites das agendas de pesquisa e desenvolvimento (P&D). Objetivos: Os objetivos nesse cenário, são discutir as implicações éticas, econômicas, políticas e sociais deste modelo de sistema sociotécnico. Nos referimos, tanto as aplicações tecnológicas, quanto as consequências das mesmas na formação dos imaginários sociais, que tipo de relações se estabelecem e como são criadas dentro desse contexto. Conclusão: Concluímos na busca por refletir criticamente sobre as propostas de aprimoramento humano mediado pela tecnologia, que surgem enquanto parte da agenda da Convergência Tecnológica NBIC. No entanto, as propostas de melhoramento humano vão muito além de uma agenda de investigação. Há todo um quadro de referências filosóficas e políticas que defendem o aprimoramento da espécie, vertentes estas que se aliam a movimentos trans-humanistas e pós- humanistas, posições que são ao mesmo tempo éticas, políticas e econômicas. A partir de nossa análise, entendemos que ciência, tecnologia e política estão articuladas, em coprodução, em relação às expectativas de futuros que são esperados ou desejados. Ainda assim, acreditamos que há um espaço de diálogo possível, a partir do qual buscamos abrir propostas para o debate público sobre questões de ciência e tecnologia relacionadas ao aprimoramento da espécie humana.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The subject of this research is to discuss the social imaginaries of science and technology that emerge from the area of neuroengineering in relation with the Technological Convergence of four disciplines: Nanotechnology, Biotechnology, Information technologies and Cognitive technologies -neurosciences- (CT-NBIC). These areas are developed and articulated through discourses that emphasize the enhancement of human physical and cognitive capacities, the intuition it is to build a better society, through the scientific and technological progress, at the limits of the research and development (R&D) agendas. Objectives: The objective in this scenery, is to discuss the ethic, economic, politic and social implications of this model of sociotechnical system. We refer about the technological applications and the consequences of them in the formation of social imaginaries as well as the kind of social relations that are created and established in this context. Conclusion: We conclude looking for critical reflections about the proposals of human enhancement mediated by the technology. That appear as a part of the NBIC technologies agenda. Even so, the proposals of human enhancement go beyond boundaries that an investigation agenda. There is a frame of philosophical and political references that defend the enhancement of the human beings. These currents that ally to the transhumanism and posthumanism movements, positions that are ethic, politic and economic at the same time. From our analysis, we understand that science, technology and politics are articulated, are in co-production, regarding the expected and desired futures. Even so, we believe that there is a space of possible dialog, from which we look to open proposals for the public discussion on questions of science and technology related to enhancement of human beings

Energy management techniques for ultra-small bio-medical implants

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 167-174).Trends in the medical industry have created a growing demand for implantable medical devices. In particular, the need to provide medical professionals a means to continuously monitor bio-markers over long time scales with increased precision is paramount to efficient healthcare. To make medical implants more attractive, there is a need to reduce their size and power consumption. Small medical implants would allow for less invasive procedures and greater comfort for patients. The two primary limitations to the size of small medical implants are the batteries that provide energy to circuit and sensor components, and the antennas that enable wireless communication to terminals outside of the body. In this work we present energy management and low-power techniques to help solve the engineering challenges posed by using ultracapacitors for energy storage. A major problem with using any capacitor as an energy source is the fact that its voltage drops rapidly with decreasing charge. This leaves the circuit to cope with a large supply variation and can lead to energy being left on the capacitor when its voltage gets too low to supply a sufficient supply voltage for operation. Rather than use a single ultracapacitor, we demonstrate higher energy utilization by splitting a single capacitor into an array of capacitors that are progressively reconfigured as energy is drawn out. An energy management IC fabricated in 180-nm CMOS implements a stacking procedure that allows for more than 98% of the initial energy stored in the ultracapacitors to be removed before the output voltage drops unsuitably low for circuit operation. The second part of this work develops techniques for wide-input-range energy management. The first chip implementing stacking suffered an efficiency penalty by using a switchedcapacitor voltage regulator with only a single conversion ratio. In a second implementation, we introduce a better solution that preserves efficiency performance by using a multiple conversion ratio switched-capacitor voltage regulator. At any given input voltage from an ultracapcitor array, the switched-capacitor voltage regulator is configured to maximize efficiency. Fabricated in a 180-nm CMOS process, the chip achieves a peak efficiency of 90% and the efficiency does not fall below 70% for input voltages between 1.25 and 3 V.by William R. Sanchez.Ph.D

Glucose-powered neuroelectronics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-164).A holy grail of bioelectronics is to engineer biologically implantable systems that can be embedded without disturbing their local environments, while harvesting from their surroundings all of the power they require. As implantable electronic devices become increasingly prevalent in scientific research and in the diagnosis, management, and treatment of human disease, there is correspondingly increasing demand for devices with unlimited functional lifetimes that integrate seamlessly with their hosts in these two ways. This thesis presents significant progress toward establishing the feasibility of one such system: A brain-machine interface powered by a bioimplantable fuel cell that harvests energy from extracellular glucose in the cerebrospinal fluid surrounding the brain. The first part of this thesis describes a set of biomimetic algorithms and low-power circuit architectures for decoding electrical signals from ensembles of neurons in the brain. The decoders are intended for use in the context of neural rehabilitation, to provide paralyzed or otherwise disabled patients with instantaneous, natural, thought-based control of robotic prosthetic limbs and other external devices. This thesis presents a detailed discussion of the decoding algorithms, descriptions of the low-power analog and digital circuit architectures used to implement the decoders, and results validating their performance when applied to decode real neural data. A major constraint on brain-implanted electronic devices is the requirement that they consume and dissipate very little power, so as not to damage surrounding brain tissue. The systems described here address that constraint, computing in the style of biological neural networks, and using arithmetic-free, purely logical primitives to establish universal computing architectures for neural decoding. The second part of this thesis describes the development of an implantable fuel cell powered by extracellular glucose at concentrations such as those found in the cerebrospinal fluid surrounding the brain. The theoretical foundations, details of design and fabrication, mechanical and electrochemical characterization, as well as in vitro performance data for the fuel cell are presented.by Benjamin Isaac Rapoport.Ph.D

DEVELOPMENT OF INNOVATIVE MULTICOMPARTMENT MICROFLUIDIC PLATFORMS TO INVESTIGATE TRAUMATIC AXONAL INJURY

Compartmentalization of cell body from the axon of a neuron is an important aspect in studying the influence of microenvironments. Microenvironment is an integral part of neuronal studies involving traumatic axonal injuries (TAI). While TAI is one of the possible outcomes of various forms of traumatic insults to the central nervous system (CNS) and peripheral nervous system (PNS), many of the mechanistic details are still unknown, it can be agreed that the level of injury often dictates the functional deficit. This motivates the question, what is occurring at both the morphological and biomolecular scale in CNS and PNS axons during and throughout the recovery phase after injury? And, are there any treatment strategies that could be applied to improve the recovery and regeneration of the axons subject to TAI? Motivated by this, I propose to develop novel microfluidic platforms as a part of my master’s thesis to allow unprecedented, physiologically relevant focal and graded mechanical injury and observation to both CNS and PNS axons. My research for this thesis can be broadly classified into two fold. 1) I examined the regenerative effects of the members of the Glial cell line-derived neurotrophic factor (GDNF), a family of neurotrophic factors after axotomy. This work resulted in the discovery of the fact that GDNF is the most potent neurotrophic factor among the family of growth factors for axon regeneration in dorsal root ganglion (DRG) neurons after in vitro axotomy. It was also found that GDNF locally applied to cell body better promotes axonal regeneration in comparison to when applied locally to axons. 2) Development and refinement of existing axon injury microplatform (AIM) to closely mimic physiological conditions during traumatic injury in CNS neurons. This work was my attempt in improving already existing microfluidic compression platform. I successfully developed a displacement control injury device and demonstrated displacement control as a proof of principle. Further development of these microfluidic platforms will significantly contribute to the field of basic neuroscience, neurobiology, and biomedical engineering

Low power circuits and systems for wireless neural stimulation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 155-161).Electrical stimulation of tissues is an increasingly valuable tool for treating a variety of disorders, with applications including cardiac pacemakers, cochlear implants, visual prostheses, deep brain stimulators, spinal cord stimulators, and muscle stimulators. Brain implants for paralysis treatments are increasingly providing sensory feedback via neural stimulation. Within the field of neuroscience, the perturbation of neuronal circuits wirelessly in untethered, freely-behaving animals is of particular importance. In implantable systems, power consumption is often the limiting factor in determining battery or power coil size, cost, and level of tissue heating, with stimulation circuitry typically dominating the power budget of the entire implant. Thus, there is strong motivation to improve the energy efficiency of implantable electrical stimulators. In this thesis, I present two examples of low-power tissue stimulators. The first type is a wireless, low-power neural stimulation system for use in freely behaving animals. The system consists of an external transmitter and a miniature, implantable wireless receiver-and-stimulator utilizing a custom integrated chip built in a standard 0.5 ptm CMOS process. Low power design permits 12 days of continuous experimentation from a 5 mAh battery, extended by an automatic sleep mode that reduces standby power consumption by 2.5x. To test this device, bipolar stimulating electrodes were implanted into the songbird motor nucleus HVC of zebra finches. Single-neuron recordings revealed that wireless stimulation of HVC led to a strong increase of spiking activity in its downstream target, the robust nucleus of the arcopallium (RA). When this device was used to deliver biphasic pulses of current randomly during singing, singing activity was prematurely terminated in all birds tested. The second stimulator I present is a novel, energy-efficient electrode stimulator with feedback current regulation. This stimulator uses inductive storage and recycling of energy based on a dynamic power supply to drive an electrode in an adiabatic fashion such that energy consumption is minimized. Since there are no explicit current sources or current limiters, wasteful energy dissipation across such elements is naturally avoided. The stimulator also utilizes a shunt current-sensor to monitor and regulate the current through the electrode via feedback, thus enabling flexible and safe stimulation. The dynamic power supply allows efficient transfer of energy both to and from the electrode, and is based on a DC-DC converter topology that is used in a bidirectional fashion. In an exemplary electrode implementation, I show how the stimulator combines the efficiency of voltage control and the safety and accuracy of current control in a single low-power integrated-circuit built in a standard 0.35 pm CMOS process. I also perform a theoretical analysis of the energy efficiency that is in accord with experimental measurements. In its current proof-of-concept implementation, this stimulator achieves a 2x-3x reduction in energy consumption as compared to a conventional current-source-based stimulator operating from a fixed power supply.by Scott Kenneth Arfin.Ph.D

Using Hidden Markov Models to Segment and Classify Wrist Motions Related to Eating Activities

Advances in body sensing and mobile health technology have created new opportunities for empowering people to take a more active role in managing their health. Measurements of dietary intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require considerable manual effort, leading to underreporting of consumption, non-compliance, and discontinued use over the long term. We are investigating the use of wrist-worn accelerometers and gyroscopes to automatically recognize eating gestures. In order to improve recognition accuracy, we studied the sequential ependency of actions during eating. In chapter 2 we first undertook the task of finding a set of wrist motion gestures which were small and descriptive enough to model the actions performed by an eater during consumption of a meal. We found a set of four actions: rest, utensiling, bite, and drink; any alternative gestures is referred as the other gesture. The stability of the definitions for gestures was evaluated using an inter-rater reliability test. Later, in chapter 3, 25 meals were hand labeled and used to study the existence of sequential dependence of the gestures. To study this, three types of classifiers were built: 1) a K-nearest neighbor classifier which uses no sequential context, 2) a hidden Markov model (HMM) which captures the sequential context of sub-gesture motions, and 3) HMMs that model inter-gesture sequential dependencies. We built first-order to sixth-order HMMs to evaluate the usefulness of increasing amounts of sequential dependence to aid recognition. The first two were our baseline algorithms. We found that the adding knowledge of the sequential dependence of gestures achieved an accuracy of 96.5%, which is an improvement of 20.7% and 12.2% over the KNN and sub-gesture HMM. Lastly, in chapter 4, we automatically segmented a continuous wrist motion signal and assessed its classification performance for each of the three classifiers. Again, the knowledge of sequential dependence enhances the recognition of gestures in unsegmented data, achieving 90% accuracy and improving 30.1% and 18.9% over the KNN and the sub-gesture HMM

Real-time signal detection and classification algorithms for body-centered systems

El principal motivo por el cual los sistemas de comunicación en el entrono corporal se desean con el objetivo de poder obtener y procesar señales biométricas para monitorizar e incluso tratar una condición médica sea ésta causada por una enfermedad o el rendimiento de un atleta. Dado que la base de estos sistemas está en la sensorización y el procesado, los algoritmos de procesado de señal son una parte fundamental de los mismos. Esta tesis se centra en los algoritmos de tratamiento de señales en tiempo real que se utilizan tanto para monitorizar los parámetros como para obtener la información que resulta relevante de las señales obtenidas. En la primera parte se introduce los tipos de señales y sensores en los sistemas en el entrono corporal. A continuación se desarrollan dos aplicaciones concretas de los sistemas en el entorno corporal así como los algoritmos que en las mismas se utilizan. La primera aplicación es el control de glucosa en sangre en pacientes con diabetes. En esta parte se desarrolla un método de detección mediante clasificación de patronones de medidas erróneas obtenidas con el monitor contínuo comercial "Minimed CGMS". La segunda aplicacióin consiste en la monitorizacióni de señales neuronales. Descubrimientos recientes en este campo han demostrado enormes posibilidades terapéuticas (por ejemplo, pacientes con parálisis total que son capaces de comunicarse con el entrono gracias a la monitorizacióin e interpretación de señales provenientes de sus neuronas) y también de entretenimiento. En este trabajo, se han desarrollado algoritmos de detección, clasificación y compresión de impulsos neuronales y dichos algoritmos han sido evaluados junto con técnicas de transmisión inalámbricas que posibiliten una monitorización sin cables. Por último, se dedica un capítulo a la transmisión inalámbrica de señales en los sistemas en el entorno corporal. En esta parte se estudia las condiciones del canal que presenta el entorno corporal para la transmisión de sTraver Sebastiá, L. (2012). Real-time signal detection and classification algorithms for body-centered systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16188Palanci