This thesis presents the design and implementation of a sensor module used in a Remote Medical Monitoring System(RMMS). This RMMS aims to be unobtrusive and record the Activities of Daily Living(ADL). The proposed sensor module is built around an ESP32-S3 (Lilygo TQ-T Pro) and integrates all the sensors on custom PCBs. It includes interchangeable environment sensors(BME280 or ENS160 + AHT21), mmWave radar sensors(C1001 or HMMD) and a light sensor, with capabilities of powering an external ONVIF camera depending on the sensor module variant. This was done with embedded software written in Micropython using an asynchronous(uasyncio) main loop, automatic sensor detection, and secure data transmission using MQTT over mutual TLS. It also integrates a hardware-driven (de-)registration program developed in a companion project. The system was validated through measuring the connectivity and timing delays of the system. The resulting MQTT round trip time of the sensor module is less than 100 milliseconds and the throughput is more than 700 bytes per second. The overall delay between sensing and receiving it over the LAN is less than one second. The casing tests showed that the thickness of the outer shell influenced the measurement results for the radar sensors. However limitations are present for the sensor module, due to unreliable "ghost" readings from the C1001 mmWave radar sensor. Overall a modular and deployable sensor module was created that can be integrated in a RMMS with validated performance of the communication and runtime delays.

This thesis presents the design and implementation of a protocol that (de-)registers devices part of a Remote Medical Monitoring System (RMMS). RMMSs are designed to relieve some of the strain on health care by monitoring a patient’s well-being without human intervention.The registration protocol makes use of either a device’s onboard Light Emitting Diode (LED) or the position of a static point in its video feed to link a digital device profile to its physical asset. It registers devices in waves,with every wave registering as many devices as can be seen by a central registration camera. The protocol is semi-automatic, requiring some user inputs and verifications. It has been evaluated on its capabilities to handle malicious devices and its registration throughput. The designed protocol can register devices faster than a fully manual system, reaching speeds of less than 5 seconds per device. Malicious devices are successfully removed and have no impact on legitimate devices. Overall, the protocol provides more efficient and scalable registration for RMMS deployments.

This thesis investigates the integration of Transmission Electron Microscopy (TEM), Microelectromechanical Systems (MEMS)-based heaters, and Photonic Crystals (PhCs) for advanced materials characterization at the nanoscale. TEM is paired with MEMS-based microheaters to enable in-situ temperature control during atomic-resolution imaging, facilitating the study of temperature-dependent material properties. The work focuses on the fabrication of MEMS-based microheaters and the development of thin electron-transparent membranes using backside electron-beam lithography, allowing precise control over the heating process and enabling new capabilities in TEM experiments. Additionally, MEMS-based nanoreactors are designed for high-pressure in-situ TEM studies, providing insights into gas-material interactions and catalytic processes under realistic environmental conditions.

The thermal tuning of PhC cavities using elastomeric infills is also explored, demonstrating the potential for temperature-responsive optical devices. Finally, the integration of cathodoluminescence (CL) spectroscopy with TEM for the study of nitrogen-vacancy (NV) centres in diamond photonic crystals is presented, with a focus on overcoming challenges in fibre-diamond coupling and optimizing experimental conditions for NV detection.

This work advances the field of materials science, offering innovative solutions for high-resolution imaging, photonic device development, and their applications.

This thesis presents a comprehensive study on enhancing the frame rate of CMOS image sensors through both circuit-level and system-level innovations. Motivated by the growing demands inmachine vision and artificial intelligence applications such as ADAS and industrial automation, this work addresses the limitations of conventional high-speed image sensor designs, which typically require increased ADC sampling rates or a higher number of ADCs—often leading to trade-offs in area, power consumption, and image quality.
The first contribution of this research lies in the analog front-end design, particularly in optimizing the ADC architecture. A column-parallel SAR ADC is developed, with both conventional and advanced two-step structures implemented to reduce noise, improve linearity, and minimize layout area. These ADCs are designed to operate efficiently at 250kS/s while maintaining low temporal noise. Techniques such as analog correlated double sampling (CDS), comparator offset calibration, and FPN suppression using optical black (OB) pixels are applied to ensure image quality despite the high-speed operation. The overall noise model is theoretically analyzed and validated, showing that with proper bandwidth and CDS timing, temporal noise remains within acceptable limits without requiring high-frequency operation.
Beyond the circuit-level improvements, a major innovation is the implementation of an adaptive reconfigurable system that switches between full-frame and region-ofinterest (ROI) modes. Recognizing that in many practical scenarios—such as tracking a moving object in a fixed background—only a small part of the image needs to be updated, the proposed system dynamically identifies and captures a small ROI (e.g., 10×10 pixels) around the object. By capturing multiple ROI images within a single full-frame cycle, the effective frame rate is dramatically improved without increasing ADC speed or interface bandwidth. The intelligent switch network, pixel array design, and address decoder architecture are all tailored to support seamlessmode switching, enabling up to 750,000fps in effective frame ratewhile operating under fixed ADC sampling constraints.
The image data path, from pixel readout to ADC conversion and digital transmission, is carefully coordinated. In zoom-in mode, 300 ADCs sample and convert ROI data across three separate sets per horizontal line, managed by FPGA-controlled timing. Image data is reassembled and analyzed in real-time within the FPGA to update the ROI position based on intensity variation. The image analyzer performs high-speed comparison using a sliding 10×10 mask and updates ROI coordinates frame-by-frame. This feedback loop ensures accurate object tracking while minimizing redundant data processing.
Measurement results confirm that the proposed design successfully achieves highspeed performance and high image quality with improved energy efficiency. The background offset calibration achieves VFPN levels as low as 0.37LSB, and the system avoids the power and timing penalties typically associated with high-speed ADC operation and high-throughput interfaces. The architecture demonstrates a scalable, application-specific approach to image sensor design, suitable for future intelligent sensing systems.
In summary, this thesis delivers a novel image sensor readout architecture that enhances frame rate without compromising image quality or power efficiency. It introduces a practical framework for high-speed operation through a dual approach: a compact, high-performance SAR ADC and a flexible reconfigurable system architecture. Together, these solutions forma robust platformfor next-generation machine vision applications that demand both speed and intelligence.

Continuous, low-burden intraocular pressure (IOP) monitoring is increasingly recognized as important for the early identification of glaucoma risk. As the standard implant in cataract surgery, the intraocular lens (IOL) offers long-term stability, a fixed position within the posterior capsular bag, and a relatively stable geometry, providing a reliable mechanical and biological platform for integrating miniaturized sensing and RF modules. At the same time, the optical zone and haptics of IOL impose strict constraints on size, thickness, and curvature, and demand high transparency and biocompatibility; together, these factors limit device shape, electrical length, and packaging options. Building on these characteristics, the idea is integrating a sensor and RF structure within the IOL, powered and read by an external reader without an internal battery. Considering maturity and feasibility, two engineering methods are investigated: an NFC coil operating at 13.56 MHz and a radiative antenna operating at 2.45 GHz. The methodology begins with equivalent-circuit and multiphysics using LT Spice and COMSOL, followed by electromagnetic simulations in Ansys HFSS under both free-space and ocular-model conditions. Key observations include the impedance position on the Smith chart, resonance frequency, coupling/radiation efficiency, and bandwidth. Based on simulation results and the literature review, the two approaches are compared with respect to structural complexity, compatibility, and manufacturing feasibility. The analysis provides quantitative guidance for subsequent prototype design and experimental validation.

With the rapid development of science and technology, the Internet of Things and big data have become important forces driving the progress of modern technology. The evolution of these technologies has spurred the widespread application of smart devices and services, bringing revolutionary changes to various industries. In this context, flexible sensors have become a key bridge between the physical and digital worlds because of their unique bendability and high adaptability. They not only provide real-time data collection and transmission, but also serve a crucial role in health monitoring and environmental detection due to their lightweight and flexible characteristics. As fabrication technologies continue to innovate, flexible sensors are evolving towards miniaturization, integration, and customization. Although flexible sensors based on a variety of micro- and nanostructures and innovative materials have made significant progress in recent years, challenges still exist in terms of sensor performance, integration capability, and fabrication efficiency. To address these challenges, we utilized ultraviolet (UV) laser direct writing technology to efficiently achieve the microstructure fabrication and material modification required for the sensing capabilities of flexible sensors by precisely controlling the time, space, and energy of the laser. Correspondingly, we developed innovative fabrication technologies based on UV laser direct writing for different types of flexible sensors, including pressure sensors, strain sensors, gas sensors, and temperature sensors. The application of these technologies not only improves the fabrication efficiency but also enhances the sensor performance to meet the demands for customization and miniaturization.

In the rapidly developed market of smartphones, drones, robots and automobiles, 3D sensing based on NIR light detection becomes a standard feature. For example, functions like car parking assistance and pre-crash detection in the automobile’s domain; the facial recognition and field of depth detection in smartphone cameras. As a result, the combination for visible and NIR light detection becomes a wise choice for the future applications. Instead of merging two different types of image sensor pixels together, a new image sensor pixel design is developed in this thesis.
In the thesis, a novel CMOS image sensor (CIS) pixel architecture capable of operating across both the visible and near-infrared (NIR) spectral ranges is presented. The proposed design integrates an n-type four-transistor (4T) pinned photodiode (PPD) stacked back-to-back with a p-type 4T PPD structure. Considering the wavelength-dependent photon absorption properties of silicon, the shallower n-type PD is optimized for collecting electrons generated by visible light, whereas the deeper p-type PD is configured to collect holes induced by NIR illumination. The pixel structure was designed and simulated using Sentaurus TCAD and fabricated using a standard 0.18 μm CIS process on an n-type silicon substrate. The resulting pixel forms a multi-junction photodetector (MJPD) featuring a vertically stacked p+-nwell-pwell-nsub configuration—representing a significant difference comparing to the standard 4T PPD architectures. To understand the electrical behavior of the MJPD structure, a three-series-capacitor model is proposed and analyzed in detail. The theoretical analysis demonstrates good agreement with both TCAD simulation and measurement results.

In modern High-Performance Computing (HPC) systems based on Field Programmable Gate Arrays (FPGA) accelerators, First-In, First-Out queues (FIFOs) are crucial for data buffering and balancing, particularly in demanding applications requiring high-throughput data streaming. Some prominent examples are: large scale signal processing, machine learning, and online network processing. Typically, these FIFOs are implemented using the available on-chip blocks RAM (BRAM) blocks organized as a circular structure, leveraging the reconfigurable nature of FPGAs to manage data efficiently. However, as applications have to process larger and larger data capacities, the associated area and power consumption of these BRAM based implementations consume significantly large portion of the on-chip resources, posing challenges for both performance and efficiency.

This thesis explores an alternative approach for large and efficient reconfigurable on-chip FIFOs by designing a dedicated ASIC block containing linear shift register structure. Unlike circular FIFOs, which rely on complex control units such as address pointers and decoders, the linear FIFOs simplify the implementation by directly shifting the data through the registers. This approach eliminates the need for the additional intricate control logic typically associated with FPGA circular buffers, making it a potentially more efficient solution for a large class of streaming applications.

The first phase of this work focuses on implementing various FIFO designs on a Xilinx Virtex-7 series FPGA, utilizing different on-chip memory resources: registers, lookup tables (LUTs), and BRAM blocks. These implementations are investigated across different bit widths, in the range of hundreds of bits, and FIFO depths of several thousand stages. The second phase compares these FPGA implementations with an ASIC-based linear FIFO of similar size, synthesized using the TSMC 40 nm standard cell library. The results demonstrate that while the ASIC-based linear FIFO offers over twice the performance of the FPGA-based designs, it requires six to seven times more area. This is attributed to the fact that register-based storage cells are approximately ten times larger than SRAM cells, highlighting the inherent trade-off between performance and area in such designs.

To address the above area overhead, this project further investigates the use of two ring-counters to replace the address decoders typically found in SRAM-based FIFO designs. As data storage requirements increase, the complexity of address decoders also grows. By simplifying the control logic with ring-counters, the design achieved area reductions of 50\% to 76\% for FIFO depths of 1 Kbits and 2 Kbits across various bit widths. These findings underscore the significant potential of this approach to optimize both area and performance in memory-intensive FPGA applications.

Tissue vitality monitoring is a crucial process to preserve patients’ health during post-surgical recovery or to ensure full adaptation and healing of transplanted organs. Among the many local factors for vitality assessment, tissue oxygenation gives an insight into entire tissue recovery and is directly linked to cell metabolism. To be able to assess oxygenation at the cellular level, NADH fluorescence sensing is used due to its contribution to the cellular respiratory cycle and high sensitivity to oxygen concentration. The current devices for NADH fluorescence sensing are limited to external measurements, where they are suitable for hospital use. This raises the need for a device that is implantable and bioresorbable so that it can stay in the body after the surgery and does not require secondary surgery for removal that puts the patient at risk. The goal of this master’s thesis is to introduce the design of a bioresorbable optical filter and photodetector for the measurements of oxygen through the detection of NADH fluorescence. The design consists of an absorption layer, a Fabry-Perot filter, and a wavelength-specific photodetector; where the overall response is designed to have high sensitivity to the emission wavelength of NADH (470nm) and low sensitivity to the excitation of NADH (350nm). ZnO nanoparticles are chosen to be the absorption layer due to their high absorption properties to 350nm and biodegradability, where the optical response is then tested through spectroscopy measurements. For the Fabry-Perot filter, a design with SiO2 and SiNx layers has been created with simulation and tested with optical measurements. The complete design consists of 15 layers and has a total thickness of approximately 1μm. Lastly; for the photodetector, Spectra simulations have been conducted for the determination of the optimal design properties. The choices are then adapted to a mask design for the fabrication, in which the back side etching of the silicon wafer is required for biodegradability and optical performance. The fabrication of the photodetector has not been completed due to the time frame of the project. The measurements on the combination of ZnO and Fabry-Perot filter show that the transmission of 470nm is 2.5-4 times larger than the transmission of 350nm, which is expected to increase to at least an order of magnitude when combined with the photodetector. For future experiments, it is recommended to conduct more tests on the filters and ZnO to ensure repeatability and consistency.

During most cardiac surgeries, a Cardiopulmonary bypass (CPD) is used. This is a machine which takes over the respiration and circulation functions of the heart during surgery. However, the blood supply to the heart and thus the supply of oxygen and nutrients, will be cut off when this occurs. This is also known as myocardial ischemia, which can lead to damage to the heart tissue and could even be fatal. Therefore, it is of paramount importance to detect ischemia before it causes irreversible damage.

There are several parameters that can indicate ischemia, including pH, oxygen and lactate. This work focuses on measuring the pH level of the heart tissue, since this could be measured noninvasively and is relatively simple. In order to get a clear picture of the consequences of ischemia throughout the heart, the pH level should be measured at different locations. To achieve this an optical fluorescence sensor is designed. This sensor consists of a sensor layer, two LEDs and an optical fibre connected to a spectrometer.

The fluorescent indicator dye used in the sensor layer is 8-Hydroxypyrene-1,3,6-trisulfonic acid
trisodium salt (HPTS). This fluorescent dye has two excitation peaks, one at 405nm and one at 470nm and two emission peaks one at 440nm and one at 515nm. These different excitation and emission bands enable ratiometric sensing which improves accuracy and sensitivity. This is due to the fact that the intensity of the fluorescent emission at 515nm is directly proportional with the pH level, where the intensity of the fluorescent emission at 440nm is inversely proportional to the pH level. By taking the ratios of these measured intensities the pH can be determined.

The indicator dye is immobilized in a hydrogel which is thereafter deposited on a thin glass slide. This slide is placed above two LEDs which are matched with the excitation peaks of HPTS. Adjacent to the LEDs an optical fibre is placed to capture the fluorescent emission and direct it to the spectrometer which is connected to a computer. The designed sensor system shows a 5 fold increase in ratio of intensities over a pH range of 6.2-8.2, with a significant improvement in response time compared to other HPTS and hydrogel based pH sensors reported in literature.

This study presents an AlN-based Lamb wave (A0 mode) liquid sensing device designed for biomedical applications. The Lamb wave device features a 1.5 μm composite membrane consisting of a 500 nm LPCVD SiN and a 1 μm of a c-axis oriented AlN film. Additionally, an innovative 45° rotated IDT design was explored to minimize edge reflections towards the output IDT. Liquid testing experiments, involving IPA, DI water, and D-PBS, were conducted to see if the devices were able to differentiate between these liquids. Results demonstrate that the fabricated Lamb wave devices exhibit sensitivity to mass loading and can distinguish between liquids based on phase, frequency, and gain characteristics. Devices with the rotated IDT design have shown a significant increase in resonance by 15 dB, as well as enhanced sensitivity compared to those with the normal design. Furthermore, devices with the rotated design demonstrated a higher Q factor of 680, indicating superior performance over the normal design (Q factor of 450). These findings suggest that a Lamb wave device with the 45° rotated IDT design holds considerable potential for applications that demand accurate liquid characterization and detection.

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.

In the past decades, the workload and the pressure on medical personnel has been growing to an unprecedented peak. This is partly due to the ageing population and the increasing capabilities to be independent at an older age, increasing the age people enter nursing homes. This paper focuses on a novel way to detect incidents that could occur in the daily life of the elderly. Unlike most systems already proposed by others, there will be no use of wearable positioning sensors and the system is implemented on an Single Board Computer (SBC). This thesis report is one of a set of two reports discussing the final implementation of the system.

The goal of this project was to develop a sensor system that detects Rapid Eye Movement Sleep Behaviour Disorder (RBD) episodes in an early stage and brings the patient to a lighter sleep stage at the episode onset. This project was completed in close collaboration with Momo Medical, a fast-growing start-up and developer of the BedSense - a device placed under mattresses that tracks the bed posture and restlessness of residents in nursing homes. To detect RBD episodes, the BedSense was used in combination with a sock that houses the biosensors EDA, PPG and an accelerometer. The sock also contains a vibrator module, that can bring the patient to a lighter sleep stage in case of an episode.

The outcomes of this project are promising, data has been recorded from both non-RBD test subjects and an RBD patient, and the vibration module has been tested.

The results of this project were integrated with another project seeking to develop an algorithm to detect RBD episodes in an early stage. This project used data from the Momo BedSense and from the sock that has been created in this project.

The objective of this project was to develop a real-time restlessness detection algorithm for Rapid Eye Movement Sleep Behavior Disorder (RBD). This project was completed in collaboration with Momo Medical, a fast-growing start-up, and developer of the BedSense device. Our project aimed to design a system capable of detecting RBD episodes and bringing patients to a lighter sleep stage. To accomplish this, proprietary data and existing data from an RBD patient were collected through the BedSense device. Additionally, data was extracted using a hardware system (developed by another subgroup) from a non-RBD test subject. The collected data was utilized to design and implement a restlessness detection algorithm. Given the limited data collected for this project, a classical detection algorithm was developed instead of machine learning techniques. The software system demonstrated impressive performance, achieving a balanced accuracy of 95.94%, an average sensitivity of 100%, and an average specificity of 91.88%.
The results of this project were integrated with another project seeking to develop a sensor system that brings an RBD patient to a lighter sleep stage. This project built a sock system with embedded sensors and a vibration module to achieve this. The proof of concept of the final integrated system demonstrated a non-invasive method of detecting and preventing episodes caused by RBD.

Prostate cancer is the most prevalent form of cancer among men, increasing in annual prevalence. Often, the disease progression is less intrusive than treatment. Sensitive and low-intrusive diagnosis methods exist but these are not specific. Causing the need for biopsy, an intrusive and high risk for complication procedure.

This thesis sets out to design, fabricate and test a low cost, maximum sensitivity for surface mass loading Love-mode surface acoustic wave (SAW) based sensor. The thesis goal and requirements build up to answer the research question: Can the biomarker CD9 in a liquid sample be detected by means of a Love-mode surface acoustic wave device?

SAW based sensors utilise the modulation of acoustic vibrations to detect an analyte. In this thesis, the change is caused by the immobilisation of a biomarker on a delay line between an input and output transducer. The method, more often referred to as gravimetric sensing, is based on the shift of the passband frequency by a change in surface mass density due to selective immobilisation of the biomarker. The change in passband frequency is detected by the change in phase at the fixed frequency. In this work, the fixed frequency within the passband is around 620MHz.

The Love-mode SAW is transceived by 8$\mu$m wavelength spaced interdigitated transducers on piezoelectric crystalline ST-cut quartz utilising Y propagating waves. The wave mode becomes Love-mode by capturing the wave energy using a slower shear horizontal wave speed 900nm polyimide waveguide layer.

The biomarker is the transmembrane protein CD9, present on extra cellular vesicles. These CD9 positive extracellular vesicles are well accessible as they are present in body fluids including urine. In this work, in vitro cell culture derived CD9 positive extracellular vesicles are used.

After an extensive study to the design of a Love-mode SAW based sensor and micro fabrication, using the high frequency probe station device characterisation method, it can be concluded Love-mode SAWs were excited. The devices show sensitivity for different liquids and are proven to be able to immobilise CD9 utilising covalent immobilised streptavidin and biotinylated monoclonal anti-CD9. The devices show a response to CD9 containing samples but are not proven to be sufficiently sensitive for CD9 in liquid sample detection.

It is recommended the sensor achieved sensitivity is first more systematically determined. Then a more robust measurement setup must be designed, less prone to cross sensitivity to environmental changes and experimental variations. Then a next generation sensor for better sensitivity to surface mass loading in liquid samples can be designed.

Capacitive, interdigital sensors in proximity of a PASiC thin film have been proposed as a cheap, robust alternative to existing ammonia sensing technologies. However, although prototype sensors have been manufactured, investigation into the working principles of this class of ammonia sensors is limited. This work aims to analyse the electrode and PASiC layer configuration to gain more insight into how design parameters influence the sensing capabilities of these devices.
To this end, finite element simulations and analytical simulations have been carried out to model the behaviour of the sensor configuration. The PASiC layer is modelled as a stack of layers with different permittivities, with the response to ammonia modelled as a change in the permittivity of the layers.
Using the simulation data, a lithography mask for a test-bench with varying electrode dimensions is designed to allow fabrication of devices for measuring the effects of different manufacturing parameters.
A series of prototypes created using this mask is then used to devise an etching setup to allow electrochemical etching of single chips to create the porous layer.
The results of the manufacturing process are analysed and discussed.

Power electronics are an important technology used to convert electricity from a source like a battery or high voltage DC bus to more usable forms of electricity. This has to be done efficiently, reliably and without failures which is critical in applications like electric cars or datacenters. Power MOSFETs with upcoming SiC and GaN devices are an important building block used in these converters. Hence these power MOSFET devices have to be improved continuously to get a lower on resistance (R_DSon), a better thermal dissipation and lower parasitic losses. In this thesis we will take a look at the embedding of power MOSFETs inside a PCB to obtain these improvements. This new technology needs to be evaluated in terms of reliability, failure-modes and thermal/electrical performance. By designing,
manufacturing and testing a PCB with embedded devices. During manufacturing silver sintering has been used for attaching the die to a copper coin. In the end the manufacturing has been done successfully.
Testing showed an 18% lower R_DSon and a twice as low junction to ambient thermal impedance indicating a better performance compared to regular packaging.

Over the years, care givers in nursing homes have seen their workload gradually increase. With no end of this trend in sight, the need for smart support systems increases. Especially systems which decrease the time spent on menial tasks are valued highly, because this frees more time for high quality and personal care.
To achieve this, Momo Medical is expanding on its nurse support system. This is a network of integrated smart solutions aiming at supporting care givers in nursing homes to provide better, faster and more personal care. The backbone of this nurse support system consists of the BedSenses, sensors which are placed under mattresses of each resident and can measure a variety of things.
This thesis describes the process of designing and creating a localization algorithm for this nurse support system. This algorithm can find residents by tracking the panic buttons they wear, so that in case of an emer- gency or whenever a care giver wants to know where a resident is located, they do not need to undertake a time consuming search in order to find them. These panic buttons send out an alive signal once every minute as well as a signal whenever the button is pressed. These signals are received by any nearby BedSenses. The algorithm looks at the signal strength with which each BedSense receives these signals and uses this to per- form localization.