Vagus nerve stimulation serves as an approach to manage drug-resistant epilepsy. Focused ultrasound stands out as a unique tool, offering a non-invasive modality for VNS. With its excellent depth of penetration and sub-millimeter focusing capabilities in soft tissue, ultrasound allows for precise targeting of the vagus nerve without the need for surgical intervention. This technology relies on piezoelectric transducers that convert electrical energy into ultrasonic waves. However, the high costs and technical difficulties associated with the production of these arrays have led to limited commercialization of piezoelectric transducer arrays. This thesis investigates the design, fabrication, and optimization of a small, low-cost phased-array piezoelectric ultrasonic transducer. The transducer is specially designed for non-invasive UVNS applications in the form of a small patch for the neck. The research is dedicated to the fabrication of the transducer array, designing a transducer capable of both transmitter (TX) and receiver (RX) functions, which in the future can be used for simultaneous image-guided neural regulation. Two prototypes were fabricated: one is a 256-element 2MHz rectangular transducer array integrated into an 8-layer stacked rigid printed circuit board (PCB), and the other is a dual-frequency array integrated into a 4-layer flexible PCB substrate, explicitly designed for simultaneous imaging and neural modulation. The study utilized two key materials, the well-known PZT and the lesser-known but promising <001> oriented PMN-0.3PT piezoelectric single crystal. Through extensive optimization, air-filled PZT transducer arrays were realized, and the cutting parameters for PMN-PT were significantly improved. A unique aspect of the fabrication was the use of flip-chip technology to directly integrate the air-filled 2D array onto the PCB, a method seldom detailed in existing research. While exhaustive testing on phase-delayed beam-forming and imaging capabilities could not be conducted due to equipment limitations, preliminary evaluations of the capacity to generate plane waves were made. The properties of the bulk PZT and PMN-PT transducers were characterized. It was observed that the PMN-PT transducer generated significantly lower ultrasonic pressure compared to the PZT transducer, which aligns with expectations due to the fragile nature of PMN-PT. The first prototype of the PZT array transducer was successfully fabricated and assessed, achieving a pressure of 176 kPa at its 10 mm natural focal point. Subsequently, the internal array second of the prototype was fabricated and evaluated, registering a pressure of 1.14 MPa at the 1.2 mm natural focus point. The results demonstrate the feasibility of building complex piezoelectric arrays using optimized fabrication methods. This lays the foundation for future prototypes to test beam-forming capabilities and for fabrication of the complete equipment afterwards.

In the emerging research field of bioelectronic medicine, it has been indicated that neuromodulation of the Vagus Nerve (VN) has the potential to treat various conditions such as epilepsy, depression, and autoimmune diseases. In order to reduce side effects, as well as to increase the effectiveness of the delivered therapy, sub-fascicle stimulation specificity is required. In the electrical domain, increasing spatial selectivity can only be achieved using invasive and potentially damaging approaches like compressive forces or nerve penetration. To avoid these invasive methods, while obtaining a high spatial selectivity, a 2 mm diameter extraneural cuff-shaped proof-of-concept design with integrated Lead Zirconate Titanate (PZT) piezoelectric ultrasound transducers is proposed. For the development of the proposed concept, wafer-level microfabrication techniques are employed. Moreover, acoustic measurements are performed on the device, in order to characterize the ultrasonic beam profiles of the integrated PZT-based piezoelectric ultrasound transducers. A focal spot size of 200 μm by 200 μm is measured for the proposed cuff. Moreover, the curvature of the device leads to constructive interference of the ultrasound waves originating from multiple piezoelectric ultrasound transducers, which in turn leads to an increase of 45% in focal pressure compared to the focal pressure of a single piezoelectric ultrasound transducer. Integrating piezoelectric ultrasound transducers in an extraneural cuff-shaped design has the potential to achieve high-precision ultrasound neuromodulation of the Vagus Nerve without requiring intraneural implantation.

Medical technology has seen great progress over the last centuries, developing increasingly more specialised therapy to benefit human health. The rise of the pharmaceutical industry and the research it drives are contributors to this success. However, in humanity's attempt to tackle more and more complex health issues, the conventional methods used require adaptation. This is also true in the case of neurological disorders and diseases, which stem from the body's nervous system. While the nervous system possesses high responsiveness to chemical devices, these same devices can often not target specific locations at the required time. Therefore, solely depending on chemical delivery stagnates progress in overcoming the ailments' negative effects on both health and quality of life. It is here that an argument is made for therapeutic delivery through another modality. Manufacturing such technology creates complex engineering challenges and demands close cooperation between engineers and clinicians. In this thesis, fundamental research is done to aid the investigation of efficient acoustic delivery with focused ultrasound. It is part of an ongoing effort to make therapy for neurological disorders and diseases less invasive and more effective. The modality of ultrasonic waves promises great potential in this respect, being able to image and modulate neural activity. The work presented here shows the development of a research platform to effectively study the biophysical mechanisms that are responsible for ultrasonic neuromodulation. Using microfabrication techniques and 3D printing the basic elements of the platform could be manufactured. During electrodeposition, silver layers were grown to construct the Ag/AgCl electrode and insight was gained into the process. Electrophysiological measurements show the platform's capability to measure bilayer lipid membranes, which were manually prepared and suspended.

This report presents a proof-of-concept for a sensor measuring the ionic concentrations in sweat using cyclic voltammetry. Development is focused on feasibility of the sensor. Theoretical evaluations of voltammetry as a working principle and its physical and electrochemical foundations are guiding principles of the design. The sensor is then implemented using commercial components. Experiments show that the sensor has good sensitivity and linearity for single ions in the physiological range. For the measurement of multiple ions the voltammogram is characterized in-depth. A matrix of different ionic fluids with multiple ions is prepared and two independent parameters for the concentration of two ions (sodium and potassium) are found, proving the concept of the sensor for more complex solutions. The usability of the sensor is verified using a sweat sample. Different influencing factors are researched and their impact characterized. Varying electrode materials are evaluated considering durability and sensitivity. Conclusions are drawn and an outlook for future research on this type of sensor is given. The concept of the sensor is proven to work within certain limitations.

Vagus nerve stimulation (VNS) has been proven to be an effective treatment for patients suffering from drug­-resistant epilepsy. Current vagus nerve stimulators are either implantable devices or bulky, handheld devices. The implant consists of a pulse generator beneath the skin of the chest, connected to electrodes that are wired to the cervical vagus nerve. While capable of delivering localized electrical impulses, the implantation is highly invasive. Handheld devices do not ask for a risky surgery, but their imprecise targeting of the neck reduces efficiency and provokes additional side effects. Ultrasound has been widely used in clinical applications ranging from focused ultrasound (FUS) tissue ablation to medical imaging. Much research is being carried out on the use of FUS neuromodulation as a low-­cost, non-invasive alternative to electrical VNS. The combination of using ultrasound for neuromodulation as well as imaging allows for image-­guided FUS where automated tracking of the nerve location improves the targeting of the vagus nerve. In this thesis, the design of an ultrasound vagus nerve stimulator with combined imaging capabilities is presented. The novel architecture combines FUS for vagus nerve neuromodulation and plane wave imaging (PWI) with optimized sparse receive sub­arrays to obtain the location of the nerve within the neck. A 2D array of piezoelectric transducers with λ/2-pitch poses a strict constraint on the pixel area. The goal of the system design is to minimize the area consumption of the on­-pixel electronics by making use of already present circuit blocks. A shared delay­-locked loop generates the required continuous phases for FUS neuromodation, while a row-­column pulse control block generates a single pulse from the available phases for use in PWI. This way the on-­pixel transmit hardware is reduced to a multiplexer and high­-voltage driver. The receiver consists of an analog front­-end and analog-­to­-digital converter and is shared among a sub-­array of receive elements. Different degrees of random sparsity are explored for the optimal implementation of the receive sub-­arrays within the full array. Synthetic aperture imaging allows the multiplexing of multiple receive elements to the shared front-­end and reduces the time spent on imaging using dynamic beamforming on a single data set. The full system­-level architecture of a complementary metal­-oxide­-semiconductor (CMOS) interface is proposed and the receiver front-end has been designed and simulated.

The development of neural prostheses, especially those directly targeting the brain, requires extensive research and modelling before clinical trials can be performed. Currently, the resolution of artificial vision is not sufficient for everyday tasks. By studying the expected spatial extent of stimulation, we aim to provide insights to researchers that can be used to improve the resolution of artificial vision. The goal of this MSc thesis was to visualise the shape and intensity of electric fields in the cortex as a response to intracortical microelectrode stimulation to observe the expected regions of neuronal activation considering electrode design parameters. To do this, parameters that can influence the generated electric field and the regions of activated tissue have been defined. Implementing these parameters in a Finite Element Model (FEM) allows the computation of the generated electric field in 3D of a stimulating electrode to observe the spatial extent of activated tissue. The spatial extent of activated tissue can be estimated using simplified methods such as the activating function (AF) or current density threshold. The result is a parameterised framework that creates a Visualisation of Neuronal Activation (VoNA) that can be used to assess activated tissue regions for varying scenarios by defining material properties and dimensions of the model, and allows for the adjustment of the stimulation configuration, electrode contact spacing, customisation of electrode size and modulation of stimulation current. It enables the user to tune the model settings towards their specific needs and explore the possibilities by visualising the results from different angles by defining subsets of the entire solution. In line with expectations, the presented models show that the model parameters can influence factors such as the generated electric field, the current density and electric potential, which are indicators of neuronal activation. The findings support the hypothesis that these parameters should be considered during electrode design to achieve accurate stimulation.

This thesis report, one of a set of two reports, describes a novel way to detect incidents that could occur in the daily life of the elderly. Unlike most systems already implemented in this field, this system does not use any wearable (positioning) sensors and works off an Single Board Computer (SBC).Independent of both of these systems is a system for reassurance to alleviate distress.

Development of a visual prosthesis has the potential to help millions of patients with visual impairment around the world. One approach of visual prostheses is intracortical stimulation, where electrodes penetrating the visual cortex are used to create small light dots in the patients visual field. Said therapy requires an implantable neurostimulator that is able to stimulate more than 1000 micro-electrodes for sufficient resolution. Conventional stimulation methods are not suitable for this purpose as they are inefficient in multi-channel stimulation or lack control of injected charge. In this thesis a novel stimulation method is presented based on dynamic duty cycle control of ultrahigh frequency (UHF) pulses. The duty cycle is charge-controlled using a monostable multivibrator control loop. With this novel topology, the injected charge of a stimulation pulse is controlled even when electrode impedance changes. The presented system uses spatio-temporal stimulation to share the stimulator circuit among multiple output channels. Another contribution of this work is the implementation of an active charge balancing method. This method monitors the residual voltage at the electrode-tissue interface in between UHF pulses and stops stimulation when this voltage is brought back close to zero. The charge balancing circuit consists of a single comparator connected to the stimulation path. Overall, the proposed stimulator circuit consists of two comparators, one capacitor, three logic gates, and switches. The circuit is easily scalable depending on the stimulation parameters, requiring only two switches per output electrode. For validation purposes, the circuit has been implemented on a printed circuit board (PCB). The PCB has 8 output pins and operates up to 15V. Using a linear model of the electrode tissue interface, charge injection accuracy of the circuit was measured. The charge injected during a single UHF pulse is scalable with C*V. The implemented PCB uses a capacitor value of C=400pF, while the voltage V is scaled from 62.5mV to 1.25V such that the stimulation intensity ranges from 25pC to 500pC perUHF pulse. Furthermore, the charge balancing method was verified with the linear tissue model. The proposed method successfully reduced the residual voltage to 3.1mV, well within the safety limit of50mV. Measurements on a micro-electrode array confirmed functionality of the circuit for non-linear loads. Finally, the work presents an important insight regarding the development of power efficient neurostimulators. It has been shown that it is important to consider not only power efficiency of the circuit but also the energy efficiency of the stimulation waveform to decrease the power consumption of the system.

Neuromodulation of the vagus nerve is used as a treatment for all kinds of ailments and even as a means of improving the wearer's physiology, however, this form of treatment is not popular due to its invasive nature, high chance of side effects, and short period between reimplementation surgery, as such an alternative is sought in the form of neuromodulation using ultrasound. In this thesis, 2 designs for wearable ultrasound neuromodulators for the vagus nerve are suggested, based on these designs a solution is made, solving the problem of detecting vagus nerve within a wearable environment. To detect the vagus nerve two methods are proposed: neural networks and template matching. Based on these methods and these proposed designs 5 unique works have been created, Vivo las vagus (VLV) an object detector using a neural network, a mobile implementation of both VLV as well as template matching, an FPGA implementation of template matching, and 2 FPGA implementations of VLV in which one uses a streaming dataflow architecture and the other a systolic array architecture. The best results are achieved with the streaming dataflow architecture implementation of VLV within an FPGA, resulting in an accuracy of 87.5 percent on the test set with the 10.88 FPS/watt, and inference of 0.174 seconds. This was achieved by using FINN, a community project for converting software neural networks into HDL representation for the FPGA. Combined with to the best of the author's knowledge, first-ever created loss function to automatically decrease the bit width of a quantized neural network layer without impacting the accuracy during training creating the first-ever fully automated end to end flow for creating a software neural network object detector and converting it towards an HDL representation, allowing biomedical engineers without knowledge of digital electronics or Neural networks to simply load in data and run the python files. To assess the accuracy an accuracy calculation function was created together with a dataset and test set with images taken from [1]. As the dataset has shown to be lacking severely in variety the accuracy assessment of all of the implementations can be considered moot. The VLV FINN implementation was compared to other FPGA implementations based on energy efficiency, showing that the work created within this thesis is one of the best in terms of power efficiency and the smallest in terms of resource usage footprint.

3D-multi-electrode arrays (3D-MEAs) are needed to overcome the limitations of 2D-multi-electrode arrays (2D-MEAs) and enable the electrical characterization of 3D neuronal cultures in in vitro brain models, advancing the understanding of neurological disorders and paving the way to personalized medicine. The aim of this thesis was to overcome some of the limitations of current 3D-MEA devices and develop structures approaching the stiffness of the brain microenvironment, by using materials softer than conventional Silicon.A polymeric 3D-MEA was designed and developed by means of an innovative combination of two-photon polymerization (2PP), a 3D printing technology with sub-micrometer resolution, and standard wafer-level microfabrication methods from the semiconductor industry. Two novel fabrication protocols were developed, the first being a combination of 2PP with high-aspect ratio photolithography, which, though feasible, proved to require an inconveniently laborious process flow. The second fabrication process employed instead 2PP to fabricate the polymeric structures, pattern the microelectrodes, and provide electrical insulation. The 2PP-based process flow was ultimately preferred due to its potential for fabrication of structures of higher aspect ratio and geometrical complexity for 3D-MEA, extending their measurement resolution. Furthermore, a wafer-level alignment routine was developed with an alignment repeatability of 2PP structures of ±5 µm, which enabled the multi-step 2PP fabrication process. A novel maskless photolithography via 2PP process was also developed to pattern thin films over slanted surfaces, utilizing photoresist and glycerol-based immersion optics. The resulting 3D-MEA consisted of 15 printed polymeric pyramids featuring a total of 60 gold microelectrodes. The electrical insulation of the traces was partially successful, and will require further process development.The results demonstrate the feasibility of merging, for the first time, the 2PP process with standard wafer-level microfabrication techniques, specifically for the fabrication of a 3D-MEA for in vitro studies of human induced pluripotent stem cell (hiPSC) neuronal cultures. The 2PP-based solutions provided in this thesis show a promising pathway for the development of more complex and biomimetic 3D-MEAs. More generally, the developed wafer-level alignment routine and maskless photolithography via 2PP process for high-aspect ratio structures contribute to advance the field of microfabrication, and may enable the development of other types of innovative microdevices.

Abstract—This paper investigates the performance of commonly used spike detection algorithms (Absolute Amplitude Thresholding and Non-linear Energy Operator) on compressed neural signals using a novel wired-OR lossy compression algorithm. Performing compression with the wired-OR architecture mainly removes the noisy baseline and preserves spikes in the neural signal. As a result, the spike detection sensitivity and accuracy improve or stay similar after compression. In addition, this paper proposes a new spike detection algorithm, the non-zero spike detector, that can be efficiently integrated into hardware with the wired-OR compression scheme. By using a firing rate-based approach to optimize the threshold in the non-zero spike detector, the proposed technique outperforms both Absolute Amplitude Thresholding and the Non-linear Energy Operator across different signal-to-noise ratios and firing rates. The wired-OR readout architecture, in combination with the non-zero spike detector, is a promising approach to achieve massive compression while preserving the neural signal and maintaining spike detection performance.

Class D amplifiers (CDA) have been used considerably in audio applications due to their high-efficiency behavior. Compared to standalone analog input CDAs, digital input CDAs are less sensitive to electromagnetic interference (EMI), which is preferred in automotive applications. For digital input CDAs, multi-bit current-steering DACs using tri-level units offer high dynamic range (DR) compared with other types of DAC. The main challenge in designing low total harmonic distortion plus noise (THD+N) and high DR IDAC lies in noise, mismatch, and ISI reduction. In this project, a new ISI resilient dynamic element matching technique is developed for mismatch shaping and ISI reduction in IDAC.

In vitro neuromodulation studies play a crucial role in understanding the underlying interaction mechanisms between cells and ultrasound, which is important in the development of new therapies for various neurological disorders. Acoustic focusing, the ability to focus ultrasound at a specific focal length with high spatial resolution, provides a precise and effective way to stimulate cell cultures. In this way, researchers are able to stimulate specific cells or regions within a cell culture, leading to a better understanding of cellular behaviour and responses to ultrasound stimulation. This thesis focuses on designing and developing a microfabricated acoustic Fresnel lens to focus ultrasound at a pre-determined focal length to fit into currently used Microelectrode Array (MEA) devices. Polydimethylsiloxane (PDMS) is used as lens material and microfabrication technologies are employed for the fabrication of a silicon mold. Experimental measurements have been conducted in an underwater configuration to evaluate the performance of the acoustic lens. The research highlights the potential of using acoustic Fresnel lenses on ultrasound transducers for in vitro neuromodulation. The results of the study demonstrate their capability to effectively focus ultrasound waves at the desired focal length. This advancement has significant implications for the field of in vitro neuromodulation, as it offers a cost-effective and promising method for achieving more accurate stimulation of cell cultures and for studying the impact of various acoustic parameters on cells.

Disruptive changes in the fields ofcryptography and quantum chemistry can be achieved through quantum computing,as specific computations can be sped up significantly. Thousands to millions ofqubits are required to perform these computations, illustrating the need forlarge quantum computers. These qubits must be cooled to cryogenic temperaturesin order to operate. Currently operations on few qubits can be done, these arecommonly controlled with room temperature equipment. However as the number ofqubits becomes larger, scalable and integrated electronics is required toreduce the interconnect. This has promoted research in cryogenic electronicsthat can be located close to the qubits. This thesis presents a low power,scalable cryogenic DC biasing solution for the biasing of spin qubits. Thepresented DC-DAC has been implemented in the Intel 22-nm finFET process. Unlikeconventional DACs, the designed DC-DAC periodically generates all possiblevoltages in the full scale output voltage range, and drives a multiplexer thatconnects a sample and hold capacitors when the right bias voltage for theelectrode has been generated. The DAC is able to achieve a high resolution of 16bits with low noise performance by using an offset-compensated switched capacitorintegrator. By offering a DC input to the integrator the full scale outputvoltage range can be generated, while using the offset-compensated switchedcapacitor integrator allows reduction of offset and 1/f noise which are expectedto degrade at cryogenic temperatures. The DC-DAC is designed to meet a largevoltage output range of 3 V, which breaks compliance with the nominal 1.8 Vcompliance of the thick oxide transistors in the process. While it is possibleto put larger voltages over the transistors, it is currently unknown how thiswill affect the reliability and behavior of the thick oxide transistors.Therefore, a two-stage amplifier has been implemented where the second stageuses a supply of 3.6 V. The voltage compliance in the second stage isguaranteed through cascode transistors that are dynamically biased byadditional DACs. As the addition of the second stage of the amplifier andcoarse DACs introduce another voltage domain, additional circuitry such aslogic level shifters, diode stacks and cascode transistors have been added toensure that voltage compliance is throughout the entire DAC. The DC-DACachieves a LSB step of 45.1휇푉,, avoltage output range of 3 푉,,integrated noise of 17 휇푉 rms and dissipates a total of 187휇푊, whilenot consuming more than 0.078 푚푚,2. Thehigh resolution, large voltage output range and low power of the DAC enableintegration of the DAC with the qubits, paving the way for scalable quantumcomputers.