Subjective) tinnitus is a phantom perception, where a sound is perceived by the subject that cannot be objectively perceived by other observers. an estimated 9.8% of people suffer from chronic tinnitus, moreover, for 1%-3.1% of people, it severely impacts their lives, leading to anxiety, depression, and insomnia, amongst other symptoms.
Tinnitus is strongly related to hearing loss, however, the ear is likely not the sole cause of tinnitus.

Currently, the generation and progression of tinnitus is thought to be a complex multifactorial process. Although research is ongoing and a consensus is not reached yet, the most recent theories consider the following mechanism for the development of tinnitus: (1) a lack of auditory input, triggers (2) over-expression in auditory neurons in the brainstem and auditory cortex, both part of the ascending pathway, where after (3) the tinnitus signal becomes wrongly labeled as important by the brain’s medial pathway and directed to the conscious parts of the brain where it is perceived, subsequently (4) the descending pathway is unsuccessful in suppressing the generation of tinnitus.

It is hypothesized that pairing acoustic stimulation using tinnitus-matched sound with transcutaneous electrical nerve stimulation of the vagus nerve can teach the brain to associate the distressing tinnitus sound with the de-stressing stimulation of the vagus nerve. Over time it is expected that the tinnitus sound will be labeled as unimportant by the medial pathway and is thus consequentially suppressed.

To investigate this hypothesis a bimodal stimulator is required that can combine acoustic stimulation and transcutaneous electrical vagus nerve stimulation. The device should be easy to use and safe. The specific focus of this thesis report was to design the electronic hardware for electrical stimulation and power management and implement various safety features.

From testing the stimulation output it could be concluded that the device is successfully able to produce the electrical pulse pattern and potentially any other electrical pattern. Following a risk assessment, and analyzing the safety of the device, it was concluded that the device can be used to test the efficacy of the proposed treatment, given that it is used in the prescribed circumstances and that the user is aware of the risks. Furthermore, it was shown that the device was able to stimulate the vagus nerve. Overall, the device was easy to use and was able to pair acoustic and electrical stimulation.

The recording of biosignals, such as atrial electrograms (AEG), electrocardiograms (ECG), and electroencephalograms (EEG), is progressing towards the adoption of more dense electrode arrays in order to improve spatial and temporal resolution. The proliferation of channels necessitates some form of channel sharing technique so that efficient low power and area recording can be achieved.
In this thesis, a code-division multiplexed analog front-end is designed due to its efficient use of bandwidth in comparison to time and frequency multiplexing. Orthogonal coding schemes such as Walsh-Hadamard sequences are best suited for minimising cross-talk. These codes are typically implemented using an LUT or processor which becomes a significant overhead when a large number of channels are to be multiplexed. However, by investigating the sequences closely, a novel method of generating these codes from a clock signal using digital logic was devised. The proposed algorithm to generate these sequences on-chip provides significant area savings for sequences of length greater than 8, which makes the design scalable for a large number of channels,. The reduction in area ranges from a factor of 10 for a code length of 8 up to a factor as large as 200 for a code length of 128.
As orthogonal sequences require a low bandwidth, a low bandwidth low-noise amplifier and ADC were used for amplification and digitisation of the signal. By using digitally inspired analog blocks, such as an inverter-based amplifier, lower power consumption could be achieved.
The entire design was implemented to share 7 channels. The code generator, low-noise amplifier and ADC consume a total of 78.4μW, which corresponds to 11.2μW per channel. This is a 3.3x improvement to the design in [5] where pseudo-random sequences were used as the coding scheme. However, the design consumes more power than a state-of-the-art design reported in [6] which uses 1.97μW per channel. While the design is currently not optimized with respect to power consumption in comparison to the design in [6], the novel code generation technique reported in this thesis makes the design scalable for larger number of channels. This is because the area constraint of the LUT is no more the limiting factor in terms of area.

This study aims to systematically design and implement a voltage regulation control loop (VRCL) for an unspecified power management unit (PMU) to maintain the desired load voltage for electronics worn by group-housed rodents. This is crucial for analyzing the spontaneous behaviour of group-housed rodents, focusing on social interactions and environmental exploration in a simulated natural environment.

The study explores a potential high-level design of a power link, selecting resonant inductive coupling for wireless power transfer (WPT), enabling continuous power supply over larger areas (for instance, 5 by 5 meters). A literature review reveals a research gap in integrating encircling and underneath configurations for sufficient uniform power distribution. A block diagram of the WPT system is provided, outlining the transmitter and headstage receiver components. Subsequently, a hybrid layout is suggested and significant challenges like optimizing driving current and minimizing angular and vertical misalignments are addressed.

Next, a control loop is systematically designed and implemented. Potential loads and a PMU are
selected, followed by the development and verification of an ideal power converter and its derived
and proposed plant model. Control specifications derived from this model suggest the tuning of the
controller parameters using a tailored model-based control system approach. MATLAB simulations
confirm that the control specifications are met. A non-ideal power converter is then integrated with the control loop, including ideal gate drivers, a voltage-controlled oscillator, a bandgap reference, and a PI controller. Simulation results show that the control loop meets the specifications. Despite limitations in robustness, particularly regarding load and input voltage transient response, the study also highlights the need for verification of the power converter model for load capacitors in the pF-nF range, and identifies discrepancies in overshoot behaviour. Future work includes an analysis of the system’s robustness during controller tuning and the incorporation of a transient controller. The combination of the suggested plant model and model-based tuning approach offer an alternative option for the power converter’s control loop design.

Cervical Vagus Nerve Stimulation (CVNS) has shown efficacy in treating depression, therapy-resistant epilepsy, and is being explored for conditions such as obesity and migraine. The side effects of whole nerve stimulation, which is currently the only approved method, can be minimized using spatially selective stimulation. This thesis introduces Temporal Current Steering (TCS), a novel stimulation technique aimed at enhancing spatial selectivity for CVNS. TCS introduces a temporal variation to standard current steering, creating an electric field that varies both temporally and spatially. With this study, enhanced spatial selectivity was confirmed through simulations of extracellular stimulation of neurons with time-dependent waveforms on two electrodes located on a single plane. Particle swarm optimization was employed over 2000 iterations and 98 runs to identify a waveform with the highest spatial selectivity. The optimal solution achieved a 30% improvement over a single electrode placed directly in line with the target and a 31% improvement over the standard direct current steering technique, simulated in the same model. The findings of this thesis suggest that TCS can increase spatial selectivity in invasive stimulation, although further simulations are needed for non-invasive applications with greater electrode-to-neuron distances.

Subjective tinnitus is a sensation of sound without an external source. There is no clear understanding of the cause and pathology of tinnitus.

Literature suggests a combination of deafferentation of the tonotopic map , the Bayesian brain model, and the triple mode network, creating one combined hypothesis for tinnitus pathology. Based on the combined hypothesis, transcutaneous vagus nerve stimulation paired with tinnitus-matched sound stimulation should train the brain to reduce the tinnitus sound's importance, thereby eliminating it from conscious awareness.

To investigate this hypothesis in clinical studies, a device that combines transcutaneous electrical nerve stimulation on the tragus with tinnitus-matched sounds in the ears is needed. The device should be easy to use and electrically safe.

A device has been designed with a user interface that interacts with a microcontroller, following the requirements. The microcontroller controls the audio stimulation shield and the custom-made stimulation circuit designed by Jonathan Kneepkens.

Electrical stimulation of the tragus provides the right effect. It activates the parasympathetic nervous system. The device's efficacy as a treatment must await clinical trials with patient-specific tinnitus-matched acoustical stimulation.

Neurological disorders profoundly affect quality of life, impairing essential functions like memory, cognition, and movement. Traditional treatments are often limited due to the complexity of the brain, the invasiveness of procedures, or the poor precision of the treatment. Ultrasound (US) neuromodulation offers a promising and minimally invasive alternative, using ultrasound waves to modulate neural activity in deep brain regions with high spatial resolution. Despite its potential, a technological gap limits preclinical ultrasound neuromodulation studies, as current ultrasound devices are too bulky and imprecise for flexible and continuous neuromodulation in freely moving rodents. Moreover, precise targeting is essential for effective neuromodulation, necessitating fine control over the focal spot location. This thesis aims to discover new system-level and circuit-level approaches to designing a miniaturized, power-efficient, and high-spatial-resolution 2D phased array transmitter application-specific integrated circuit (ASIC). These approaches are guided by the vision of implementing a miniaturized ultrasound transducer device for precise ultrasound neuromodulation in freely moving rodents, ultimately laying the foundation for future clinical applications in neurological disorder treatment.
The thesis begins with a literature review to determine the acoustic parameters required for effective ultrasound neuromodulation. Then, a comprehensive system-level study using the k-Wave Matlab toolbox is conducted, examining factors critical to the design of a 2D phased array transducer. This study highlights how parameters such as driving voltage, phase quantization resolution, frequency, and array length significantly impact the performance of the 2D phased array ultrasound transducer by influencing key acoustic and electrical attributes. Optimizing these parameters is essential to achieving high focal gain and spatial resolution while minimizing power consumption. The study finds that a three-bit phase resolution is optimal for accurate ultrasound beam steering. Additionally, while increasing array length improves spatial resolution and phased array gain, it also increases the overall size of the ultrasound transducer, constrained by the small brain sizes of rodents in preclinical studies. This study demonstrates that higher frequencies enhance spatial resolution and phased array gain. However, due to kerf limitations in the dicing manufacturing process of piezoelectric transducers, increasing frequency reduces the effective area of the transducers. Moreover, the pitch size should be reduced with increasing frequency in order to avoid the appearance of the grating lobes in the beam profile, forming a tradeoff between the frequency and the available area for the beamforming channels. Since higher frequencies are desired, particularly for applications in which higher spatial resolution is needed, high-voltage beamforming channels have been developed to investigate the highest frequency that allows for implementing a high-voltage beamforming channel. In this regard, two beamforming channels have been implemented and validated in TSMC 180-nm BCD technology, allowing for driving the ultrasound transducers with 12-MHz 36-V pulses. On the other hand, the power consumption of the beamforming channels has a crucial impact on the overall power efficiency of the ASIC. Therefore, a power-efficient HV pulser is developed, leading to 40.9% power consumption reduction with respect to the conventional HV pulser.
Utilizing the proposed beamforming channels, a prototype 2D phased array transmitter ASIC is developed to validate the findings of the initial system-level study. The transmitter ASIC includes a 12*12 array of beamforming channels that generate 12-MHz pulses with 20-V amplitude. The phasing circuitry in the ASIC generates the required delay for each beamforming channel, hence allowing the ASIC to steer the ultrasound beam. The measurement results proved the functionality of the phased-array transmitter ASIC in terms of phase quantization, showing a maximum DNL of 0.35 LSB. Furthermore, the ASIC allows for controlling the driving voltage and the burst duration, as needed for US neuromodulation applications. Based on the prototype 2D phased array transmitter ASIC, a US-guided US transmitter ASIC is developed for preclinical US neuromodulation experiments in freely moving rats. Considering the size of the rat's brain, the size of the ASIC is limited to 5*5 mm2. Given the prior discussion, the frequency was set to 12 MHz to achieve higher spatial resolution and phased array gain. Taking into account the proposed 20-V beamforming channel, the size of the 2D array was set to 66*66. According to the author's knowledge, this is the first transmitter ASIC that allows for preclinical US neuromodulation experiments on freely moving animals. Moreover, a temperature sensor was added to the ASIC to monitor the temperature rise in the ASIC. In order to monitor the location of the focal spot during the US neuromodulation, synthetic aperture US imaging capabilities are added to the ASIC to track the tissue displacement caused by the US neuromodulation push. In this regard, the ASIC includes eight groups of receiver channels that will be connected to 96 piezoelectric transducers using an analog multiplexer. To prevent side lobes in the beam profile, a system-level study was conducted to determine the optimal placement of receiver channels within the 2D array. The study revealed that a random distribution of receiver elements among the 2D transmitter elements is the most effective arrangement for minimizing side lobe appearance. To the best of the author's knowledge, this is the first ultrasound neuromodulation ASIC with integrated imaging capabilities. The measurement results proved the functionality of the ASIC in generating 20-V 12-MHz pulses with a programmable burst duration. The simulation results have shown that the receiver channels are capable of recording the echoes required for US imaging to monitor the location of the focal spot.
In summary, this thesis describes innovations in system-level and circuit-level integrated circuit design for developing an ultrasound ASIC that can be integrated with a 2D array of piezoelectric transducers, forming a miniaturized phased array US transducer that allows 3D US beam steering and focusing with the highest combination of spatial resolution and penetration depth in the context of pre-clinical studies. The ASIC includes the receiver channels that can be used for US imaging, allowing for monitoring real-time monitoring of the location of the focal spot during the US neuromodulation. This US ASIC leads to the emergence of miniaturized US transducers compatible with preclinical behavioral experiments in rodents, paving the way for the development of therapies to treat neurological disorders in humans. @en

Class D amplifiers find widespread application in audio devices for driving load speakers, primarily due to their remarkable efficiency. Nonetheless, this enhanced efficiency often comes at the expense of reduced linearity. Hence, techniques for reducing Total Harmonic Distortion (THD) are important in the context of class D amplifiers.

The analysis of the distortion mechanisms is first presented. Specifically, emphasis is placed on the distortion generated within the power stage, encompassing aspects such as deadtime distortion and rising and falling time distortion. Both of them are found to be related to the input signal. Subsequently, the compensation technique is applied to the conventional class D amplifier to reproduce and cancel the error. The idea of the compensation approach involves modifying the amplitude of the triangular waveform based on the input signal. A 12 dB THD improvement is achieved in the concept verification section, which is conducted in LTspice.

The negative feedback serves as another technique to achieve THD reduction. A straightforward two-step design methodology is presented to avoid design iterations in the concept design phase. The phantom zero technique is applied when doing the frequency compensation of the feedback loop. The validation of the concept is performed through the use of SLICAP, while the circuit implementation and simulations are carried out within Cadence. Remarkably, this technique results in an impressive -111.8 dB THD reduction, achieved when the output power equals 1 W.

Electrical stimulation has emerged as a promising therapeutic modality for the treatment of various neurological disorders such as Parkinson's disease, chronic pain, epilepsy, and depression. In addition, recent studies have provided evidence supporting the effectiveness of electrical stimulation as a treatment option for patients with chronic migraine and cluster headaches who have been unresponsive to other therapies. Specifically, stimulation of the occipital and supraorbital nerves has shown promise in managing these refractory conditions. Current implantable medical devices (IMDs) are battery-powered, which increases the size of the implant and involves lengthy wires to connect with the electrodes. Wireless power transfer (WPT) techniques can be used to reduce the size and omit the battery from the implants. However, conventional power management methods use a rectifier, power converter, and neurostimulator to convert the AC power of the link to DC power and provide electrical stimulus, which lowers implant power efficiency.

This thesis presents a novel neurostimulator circuit that salvages and stores available energy from an inductive link. The circuit design includes an inductor for energy storage and utilizes a buck-boost converter-like topology to deliver the stored energy to the tissue. This topology exploits the capacitive membrane's characteristics and injects the charge into the tissue through ultra-high frequency pulsed stimulation without requiring additional circuits that may contribute to power losses. Operating at the resonance frequency of 6.58MHz, the circuit was designed and simulated to inject approximately 500nC at an 18mm distance from the transmitter. Furthermore, the proposed circuit design incorporates a charge-metering circuit adapted to ensure stimulation efficacy in response to coupling variations. To guarantee safety during stimulation, the residual voltage is carefully monitored and brought close to zero at the end of each stimulation cycle. To achieve this, a charge-balancing scheme has been implemented, which utilizes a comparator to monitor the residual voltage across the electrode.

The proposed circuit was designed on a printed circuit board (PCB) to evaluate its feasibility. To evaluate its performance, a signal generator was used to simulate the input of the inductive link, and an electrode-tissue interface (ETI) model was used at the output. The circuit demonstrated its efficacy in measuring the charge and reducing the residual voltage within established safety limits while maintaining energy efficiency. More specifically, the charge metering measured a charge of 404nC for 450nC of injected charge, which is a 10.22% of error. Moreover, the circuit exhibited a linear response in controlling the injected charge. In the tested range, the charge balancing scheme yielded residual voltages ranging from -20mV to -16mV. The effectiveness of the charge balancing scheme was further confirmed through in-vitro measurements in a phosphate-buffered solution, with residual voltages measuring at -20mV, which falls within the safe range. Finally, the implemented circuit achieved a peak efficiency of 56%.

This document lays out the design and development of a specialized device aimed at monitoring the eye movements of premature babies, which creates an opportunity to create better sleep-monitoring systems.

Monitoring sleep has great significance, especially for premature babies, because it allows for the adaptation of care to accommodate for better and more sleep. Different sleep stages can be identified, but the identification does differ for adults compared to premature babies. Different characteristics including brain activity, heart rate, respiration, eye movement and face and body movements are linked to those sleep stages.

Eye movement is a characteristic that could be used more optimally for the creation of a sleep-monitoring system. Eye movement can be tracked using different methods, but electrooculography shows the greatest promise. For this specific method, different options exist concerning electrode placement and materials. The use of this system for premature babies during sleep also creates limitations related to the fragility of the skin of prematurely born babies. Furthermore, these babies normally lie in the Neonatal Intensive Care Unit, creating additional context-specific considerations.

Different research methods were used, resulting in a complete picture of the steps taken after premature birth occurs. These steps are portrayed in a scenario. The requirements and wishes drawn from these are used to develop ideas. During the development, a choice was made to create two parts for the device, namely the shell and the electronics module.

In the final design, the shell contains specialized electrode places, named snap-rings, as well as features that create adaptability and additional details to accommodate the use of multiple devices that are already being used on premature babies. The electronics module includes an electrode configuration that can be placed into the snap-rings in the shell. The electrode protrudes the snap-ring and is pushed onto the skin. The force needed to place the electrode is decreased by using a material with a low Young's modulus, ensuring contact between the electrode and the skin without causing damage to it. This novel configuration enables the use of dry electrodes, eliminating the need for gels and adhesives.

Some recommendations are given, which concern further the development of the device, the eventual certification and the embedding of the device within a system that monitors sleep.

Overall, a complete overview of the concept design of a device that can monitor eye movement of premature babies is given, which creates an opportunity for the improvement of sleep monitoring systems for these babies.

Acoustoelectric imaging is an emerging technology confirmed by in-vivo experiments that can help diagnose and evaluate peripheral nerve neuropathy. The ultrasound transmitter (TX) is required in such systems to selectively focus and apply acoustic pressure on the target volume. Within the ultrasound TX, the power amplifier (PA, commonly called pulser) can dominate up to 99\% of total TX power consumption. In this case, the pulser must be power-efficient and integrated with modern complementary metal-oxide semiconductor (CMOS) compatible transducers to enable miniaturized AE imaging systems. However, the small form factor is the natural limit for high-energy-efficiency pulser design.

The class-D switched-mode PA is the most common approach to drive ultrasonic transducers in recent research publications and commercialized products (e.g., TUSS
4470 by Texas Instruments$^\text{TM}$, STHVUP32 by STMicroelectronics$^\text{TM}$). Although the class-D PA manifests inherently simple and area-efficient features, it suffers from power loss on switching the plate parasitic capacitor $C_p$ of the transducer. Prior arts use excessive off-chip capacitors, inductors, and high-frequency switch-clocking signals generated by frequency synthesizers to switch the PA in different configurations to save power on $C_p$. However, these approaches increase the system form factor and introduce high-speed clock routing. Additionally, efforts to flip and short both terminals of the transducer for increased PA efficiency are not practical for CMOS-compatible transducer arrays. The trade-offs involved in optimizing switched-mode pulser efficiency extend beyond a simple consideration of $C_p$.

This work proposes a new baseline power-efficiency analysis that comprehensively explains the switched-mode PA efficiency considering transducer characteristics. A switched-mode pulser based on the stepwise-charging technique, controlled by a stepwise sequencer based on a symmetrically-modulated delay cell, is implemented in 130 nm technology. The proposed architecture achieves an overall acoustic efficiency of 82.5\% in simulation while maintaining an average efficiency of 81\% in global PVT and mismatch corners. The PA achieves a 9.9\% acoustic-efficiency improvement compared to its baseline and significantly outperforms the work with a similar baseline by 6.9\%. The achieved efficiency is also comparable to the work featuring a 9.1\% higher baseline, while this work demonstrates a 20x saving in capacitance budget. The PA signal chain is estimated to have an area of 108 $\mu$m x 520 $\mu$m, which can be fit into a 115$\mu$m-pitch 1-D transducer channel without extra reference resources, offering promising prospects for compact multi-channel integrations.

This thesis presents a 48V-to-1V 10-level dual inductor hybrid converter (DIHC) containing 11 on-chip switches and an off-chip Gallium Nitride (GaN) switch. Thanks to the 10-level Dickson switched-capacitor (SC) circuit, most of the voltage stress will be taken over by off-chip capacitors, which reduces the voltage stress of each switch to 4.8 V and takes full advantage of the voltage pressure on the 5-V on-chip transistors. This proposed structure is implemented in a 0.18-μm BCD process to convert 48-V input to 1-V output with up to 18-A current load. The post-layout simulations show that a peak power efficiency of 90.6% can be achieved at 5.2-A loading and the power density is about 2093 W/in3 considering the power stage volume.
This thesis also proposes a 48V/3V multi-resonant DC-DC converter for data center applications, consisting of a 3Φ-SC stage and a 4-to-1 series-parallel stage. Thanks to the multi-phase resonant operation mode, the converter uses fewer components to achieve the same voltage conversion ratio as the conventional two-phase SC converters, and can further improve the efficiency by realising soft-charging. This topology is simulated in cadence spectre, and achieves a peak efficiency of 96.94%, and 95.0% full load efficiency at 30-A load.

This work proposes an energy harvesting DC-DC converter that is able to efficiently process a wide input power range from 25 mW up to 250 mW, to charge a storage device used in Internet-of-Things (IoT) applications. An interleaved boost-converter topology with two inductors is used to divide the high currents over the two branches, in order to reduce the conduction losses in the MOSFET power switches at high input power.

A Maximum Power Point Tracking (MPPT) strategy is employed to find the optimal matching between the harvesting sensor, which in this case is a solar cell, and the input of the converter. The Maximum Power Point (MPP) is found by measuring the output current of the converter, decreasing the duty cycle of the switching power MOSFETs, and again measuring the output current to check if it increases. This process is repeated until the output current no longer increases, which is where the MPP will be. The duty-cycle pulses that control the power switches are generated by comparing a reference voltage representing the duty cycle with two sawtooth waves with a phase difference of 180 degrees generated on-chip.

Usually, for converters that handle large currents, large power switches are required to keep the on-resistance of the switches minimal such that the conduction losses do not dominate. Since the converter also needs to be able to efficiently convert smaller powers, the size of the power switches is made configurable. This is necessary since otherwise the gate-charge losses will become dominant. The total size of the segmented power switches are controlled digitally by a logic unit that calculates the expected input current using 2-bit representations of the measured output current and the two most significant bits of the 5-bit representation for the duty cycle set by the MPPT.

Schematic simulation results show a conversion efficiency of up to 92%. The proposed system is designed and simulated using 180 nm TSMC CMOS technology. The chip covers a total silicon area of 2.20 mm2, with an active area of 1.12 mm2.

This report is part of the WiECG project. The goal of the WiECG project is to create a prototype device that makes it possible to perform a 12-lead ECG on patients without wires from a patient to the monitor. The solution consists of a transmitter and receiver of which one is close or on the patients body and the other is connected to a monitor.

This thesis describes the design and implementation process for the communication protocols. This concerns mainly the WiFi communication from transmitter to receiver and the I2C pairing protocol. The WiFi communication protocol was extended with retransmission and encryption to ensure the reliability and discreteness of the data, which was indicated to be of high priority by ambulance personnel. The channel needs to minimally support 9 samples of 16 bits with a frequency of 500 samples per second. The pairing protocol needs to enable the transmitter and receiver to pair in mere seconds.

A prototype is made which successfully pairs and transfers data from transmitter to receiver. This prototype still needs to be tested thoroughly.

The goal of the WiECG project is to create a prototype device that makes it possible to perform a 12-lead ECG measurement on patients without wires from the patient to a monitor. The solution consists of a transmitter and receiver, one of which is close or on the patients body and the other is connected to a monitor.

This thesis describes the design and implementation of a subsystem of the prototype device that performs digitization, digital processing and reconstruction of the measured 12-lead ECG signal. This concerns converting nine 0 to 3.3V analog signals to the digital domain by using Analog-to-Digital converters, real-time filtering of nine signals with multiple digital IIR filters and reconstructing nine digital signals to the analog domain using Digital-to-Analog converters. Furthermore, component selection, design decisions and the implementation process will be detailed in this document.

The subsystem proposed in this paper is able to successfully sample, efficiently filter and reconstruct nine signals in real time. Recommendations on improving the implementation to better adhere to the lower power requirements for a longer battery life are provided as future research prospects.

WiECG aims to create a prototype device which enable ambulance personnel to perform a 12-lead ECG without wires connecting the patient to the monitor. The proposed solution consists of a transmitter and a receiver device. The transmitter transmits the measured signals, the receiver sends the measured signals to the monitor, which shows the measured signals.
This thesis describes the design and implementation process for the hardware. This concerns the amplification and filtering of the signals produced by the heart of the patient as well as the reconstruction
and attenuation at the output of the receiver module. These processes should be done for 9 signals. Furthermore, component selection, design decisions and the process of implementing this analog signal processing on a printed circuit board is described including the interfaces with the modules used by the other subgroups of this thesis. The prototype built during this project was able to filter the 9 signals and send it from transmitter to receiver while only adding 1.572 V RMS noise to the output ECG signal.

Recent technological advancements have made it possible to study complex social behaviors in rodents using automated observations. The Neuromate project of the Erasmus Medical Center and Delft University of Technology aims to expand the research possibilities with this technology by enabling closed-loop neuro-stimulation and observation in group-housed mice. This thesis tackles a crucial aspect of the Neuromate project: the tracking of the mice.

This tracking is done using a 3D infrared (IR) camera in combination with 2D IR markers, located on the head of the mice. The tracking system is tested using dummy mice in two sets of test conditions. Each set consists of a baseline test and a test with a complication. The first set consists of a single mouse run as a baseline and a single mouse run with an obstruction as the complication. The second set consists of a run with two mice as a baseline and a run with two mice with a close encounter as the complication.

Results showed that the test setup was capable of successfully tracking the mice during all test conditions. The test with the close encounter showed the lowest rate of positive identifications (PI) per second of the 2D IR markers (12.86§0.89 PI/s). The single mouse baseline test showed the worst percentage of false positives (1.23% of all identifications). The test setup proves that by changing the camera setup to increase the spatial resolution, for example by using a higher resolution camera, the tracking method would be capable of fulfilling the requirements of the Neuromate.

To be able to cope with the demands of next generation radar applications, a bandwidth of 400MHz is required. The SAR assisted CT ∆Σ ADC provides an energy efficient ADC, but needs improvements to cope with the bandwidth enlargement. This thesis examines the front end components and thus initially focuses on resolving the issues in the front end. Although bandwidth enlargement is possible, the APF limits the performance resulting in an inefficient two-stage architecture. For optimal system efficiency, the APF requirements must be relaxed, which is achieved by decreasing the amount of resolved bits in the coarse ADC. Due to this reduction in bits, more stages must be incorporated into the architecture. To facilitate this, power and error budgets are devised to visualize the effects of adding stages. Hereafter, the 2 bit coarse ADC is compared to a 3 bit coarse ADC. This results in a trade-off
between the applicable gain (APF complexity) and the noise requirements of the front end.
The five-stage (2-2-2-2-6 bit) architecture proves to be the most promising design to achieve the desired FoMs of 172dB. Finally, in an attempt to optimize power efficiency, the APF and LPF filter are revised. The open loop filter implementation is compared to a closed loop filter implementation. It shows
that the open loop implementation exhibits very good power efficiency, but lacks in its linearity.
The closed loop implementation achieves the requirements, but consumes a lot of power. To optimize power consumption, the first and second stage must be implemented with the closed loop filters, but the third and fourth stage must be implemented with the open loop filters.

Adaptive Deep Brain Stimulation (aDBS) offers the potential for personalized stimulation strategies for patients with Parkinson's Disease (PD). The closed loop characteristic of this system requires the incorporation of PD relevant biomarkers that determine the patient's need. In order to obtain high quality LFP (Local Field Potential) input signals, the ECG (electrocardiogram) noise should be suppressed. The aim of this project is to study the performance of various algorithmic ECG noise suppression methods. Out of the ADAPT-PD trial, we have taken 9 LFP channels with consistent ECG artefacts for exploring the performance of ECG noise suppression models. As a reference point for filtering performance, we have used survey data (DBS-OFF). Using an externally measured ECG as reference, we have implemented two Adaptive NLMS (Normalized Least Mean Squared) Noise Cancellation algorithms. For the first version, we have used stimulation ramping alone for synchronization of the data sets. The second version includes an extension that aims to improve only the data synchronization feature. Furthermore, we have explored the ECG noise suppression performance of a proposed template subtraction method, using 11 different variations of epoch length. For improved analysis, we have used three data sets, namely personal (#1), patient group (#9) and simulated (#5346) data, using the Perceive toolbox ECG filtering method as the benchmark. Simulated LFPs are based on survey data combined with 9 external ECGs in 11 levels of contamination (100-1100 %). We have conducted analysis in both the time and frequency domain (beta-range 13-30 Hz), in order to estimate the absolute difference from the reference survey. Outcomes in the frequency domain show that, for personal performance, template subtraction tweaking provides an improvement up to 37.6 % over the Perceive toolbox. Furthermore, the outcomes show that, for both the patient and simulation group, optimal performance is obtained using the Perceive Toolbox with 20.7 % accuracy for the patient group and 4.7 % for the simulations. It can be concluded that the survey LFPs can be used for personal calibration of ECG noise suppression. This contradicts the aim to find one universal LFP ECG noise suppression method. There is a need for a reliable data synchronization method between the Percept LFPs and other biometric data. Reliable synchronization would improve the usability of the external ECG as reference signal in adaptive filters. Furthermore, reliable synchronization would accelerate the discovery of linked physical symptoms for PD biomarkers.

Outstanding seizure detection algorithms using electroencephalogram (EEG) recordings have been developed over the past decade. These works mainly focus on best of class performance, which leads to computationally heavy solutions. This limits the applicability of these detection algorithms for hardware implementations such as field­programmable gate arrays (FPGAs). Which in turn limits its use in real­world applications such as warning systems or neural­stimulation systems. In this work, a convolutional neural network (CNN) is trained and its properties reduced to minimize its footprint on hardware. The network is trained based on 1423 EEG recording sessions of 637 different patients sourced from the TUSZ epilepsy database. The input EEG data is processed by removing artifacts, then applying a short­term Fourier transform (STFT) and normalizing and quantizing this to 1 byte values. The neural network is optimized by reducing the input space, this is done by reducing the number of channels, time, and frequencies used. The CNN itself is reduced by quantizing the neural network and reducing its size. Based on these results two ANNs are selected and implemented on an FPGA, one is optimized for accuracy and one for network size. The resulting networks have a sensitivity of 72.26% and 70.00% and an MCC­score of 0.711 and 0.591. The first FPGA implementations consume 0.296 W and 0.562 W at 50000 detections per second.