Fluid accumulation in the human body is, in many cases, a symptom of some underlying pathological condition. Most common examples include edema, ascites, pleural effusion, and internal bleeding. Currently available non-invasive methods to assess fluid accumulation in the body are mainly imaging-based (i.e. ultrasound, computed tomography). This means that monitoring is limited to spot-checks and is only performed when the presence of a particular condition is already suspected from prior clinical evaluation of the patient. There is high clinical interest in the development of a system allowing such monitoring to be performed automatically, continuously over a prolonged period of time, and independently of prior clinical evaluation. For instance, in the case of internal bleeding, hemorrhage indicators such as variation in heart rate and blood pressure are only observable after significant blood loss (up to more than 1 liter) has already taken place, therefore an early warning system can save lives, decrease hospital stay length and significantly reduce complication-related costs. In this thesis, a pioneer solution is proposed for development of such a monitoring system. The hypothesized solution is based on the observation of specific energy-describing features of the Ballistocardiogram (BCG) signal, a measure of the periodic displacements generated on the body as a result of ballistic forces produced by the heart during each cardiac cycle. Because of additional damping generated by the presence of internally accumulated fluid, the energy of this signal is expected to decrease compared to its baseline value. The BCG can be recorded unobtrusively with different sensing modalities on the surface of the body. In order to validate the research hypothesis and assess the feasibility of this novel technique, a custom experimental set-up exploiting several different BCG sensing options has been used to carry out a study on 15 human volunteers. Localized fluid accumulation along the GI tract was induced in a controlled, safe and simple fashion, by means of water intake by the participants, and the BCG signal was recorded before and after intake. Signal feature exploration and performance analysis has been used to develop an optimized feature able to accurately capture the decrease in signal energy due to fluid accumulation, as well as to identify the most suitable sensor type and monitoring body location for the present application. The developed energy-describing feature shows a significant decrease in energy value from baseline to after-intake condition with a p-value<0.001. Moreover, the selected feature was able to correctly identify presence of fluid accumulation with high sensitivity (90% in bed-based, and 100% in standing-position monitoring). Given the promising results of the present study, further research towards improvement and development of the proposed technique is highly encouraged.

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.

This thesis is about the simulation of the permanent magnet motors of the Nuna Solar Car in order to find their fundamental motor parameters. These parameters can then be used in a Field-Oriented control algorithm to be used in a new motorcontroller for the team. A finite element analysis is done on the two current motors of the Nuna solar car, a radial flux Mitsuba motor and an axial flux Marand motor, with the intend to find the fundamental motor parameters, the phase resistance, the inductance and the motor constant. The model is presented and the simulation results are discussed. Also some variations to the current design have been made to test the adaptability of the simulation. Also some work is done to simulate the entire drive system of the car.

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.

Stochastic resonance (SR) is a phenomenon in which the presence of noise increases the performance of the system. The phenomenon has first been discovered in a climate change model and is later observed in neuronal systems. In artificial, electronic, systems, stochastic resonance is observed in systems based on Schmitt-Triggers and comparators. The common property of all these systems is the threshold, which, when reached, causes a large transition in the system. The presence of noise in small signals can cause the system to reach the threshold or can increase the number of state transitions, increasing the quality of the output signal. Oversampling and integration are applied to reconstruct the original signal. Biomedical signals are typically affected relative high noise levels. The observations of stochastic resonance in nature, such as biological neural systems, combined with the observations of stochastic resonance in comparator-based circuits formed the inspiration and fundamental of this thesis research. The goal of this project is to investigate the potentials for using stochastic resonance in biomedical signal acquisition. In this thesis, an explorative study on the behavior, the performance, and the design of an analog-to-digital (ADC) converter fully based on stochastic resonance in a 1-bit quantizer is presented. The design and application focus on processing ECG measurements. A comprehensive analysis of the behavior, and an analytical method to determine the performance of 1-bit stochastic resonance analog-to-digital conversion in a comparator based circuit is presented. A novel technique using a negative hysteresis is found, showing a potential increase in SNDR up to 6.4 dB. Based on this analysis, a system level design is presented which implements a closed-loop operation of the stochastic resonance ADC. This design comprises a feedback loop to control the noise level, realizing the maximum performance over an input amplitude range from 1-10 mV, independent from noise present in the system. Furthermore, an offset compensation scheme is presented, which controls the threshold of the comparator, and a digital multi-rate filter is implemented to filter the high frequency noise, and to apply downsampling the highspeed bitstream. IC implementation of the comparator and the noise source is studied. A low-offset comparator, based on a strongARM latch, is proposed, with an offset calibration technique, reducing the offset to below 50 μV. The noise source creates a flat noise spectrum from 20 kHz to 4 MHz, using amplified thermal noise of a resistor combined with the amplifier noise. The proposed system can deliver a 27 dB SNDR in a signal bandwidth of 216 Hz, and an input amplitude range of 10×, using a sampling frequency of 2 MHz.

Close collaboration between the Bioelectronics department at Delft University of Technology and the Neuroscience department at the Erasmus Medical Centre has resulted in a successful tethered design for a real-time epileptic seizure detection and suppression method for mice. The goal of the Neuromate project is to develop this method into a wireless setup containing group-housed freely moving and interacting mice for use in behavioural studies. The system will include continuous monitoring and stimulation at set points in time. The Neuromate project comprises three links, two of which have previously been established. The main goal of this study was to find and evaluate a technique to complement the current Neuromate project with a wireless downlink, channelling the communication from the researchers towards the mice. This new downlink should fit in the ongoing project and meet particular specifications. The most critical requirements are that it should be lightweight and small-scale and should allow simultaneous multi-user communication. Also crucial are the prevention of interference with the two other links, reliability and low power consumption. The three most promising techniques, power source keying, optical wireless transmission and terahertz torching are elaborated. Terahertz (THz) torching, covering the high thermal part of the THz band (10 to 100 THz), was chosen as the technique to be developed in this thesis. This decision was based on the fundamental limitations of power source keying and optical wireless transmission, which appear in the weighted criteria evaluation of the requirements. The challenges of THz torching are mainly practical, while fundamentally it provides the opportunity to form a reliable non-interfering wireless link. The feasibility of THz torching for our specific application was tested by creating a proof-of-principle and conducting five different experiments. The prototype includes two components. The first is a thermal source, which in the final design will be placed above the cage, and the second is a pyroelectric detector, which will later be positioned on top of the head module of each of the mice. During the experiments, communication with the recently developed THz torch was proven to be feasible. Experiment 1 resulted in an optimum data rate of 35.71 bps, allowing for the simultaneous stimulation of the mice. And the divergence of the source was sufficient to cover the entire cage, as it was found in experiment 3 that an angle of 50° was the maximum misalignment still allowing reliable transfer of the data. However, the prototype did fail to reach the required distance. In experiment 2 only 8 cm could reliably be bridged. The source was not strong enough to overcome the attenuation in the air. A more powerful source will allow an increased reachable distance, making sure the entire cage is covered. In this work, an innovative and promising proof-of-concept has been realized for the wireless downlink of the Neuromate project.

Neuropathic pain (NP) affects approximately seven to ten percent of the general population. Seventeen percent of NP patients scored their life as “worse than death”. A myriad of causes may underlie NP, such as stroke or spinal cord injury. Also, damage or disease of the peripheral nervous system (PNS) may result in NP. One of the main issues of NP caused by a peripheral nerve injury (PNI) is the development of a neuroma, which is a tumor-like mass at the proximal end of a severed nerve that can become very painful. Neuromas show unique neurophysiological characteristics. Cell membrane alternations lead to different ion channel distributions, which in turn result in subthreshold oscillations (SO) and ectopic discharges (ED). It is assumed that this behavior could lead to NP generation. Electrical neurostimulation (ENS) is used to treat patients, thereby applying pre-programmed stimulation patterns to the affected nerves. However, the pain-provoking signals which run through the nerves are not detected and analyzed before ENS is provided. Furthermore, it is questionable whether (the currently applied) pre-programmed ENS defuses these signals anyway. In addition, pre-programmed ENS is not effective at all moments of the pain experience caused by fluctuations in signal intensity. As the clinical results are discouraging, and in view of the high costs, the popularity of this technology is currently waning. Optimization of this potentially powerful technique is needed to improve the outcome and make this technology useful to implement in the treatment strategy of patients with intractable otherwise difficult to treat pain syndromes. Theoretically, optimization of stimulation technology is possible by actually neutralizing SO and ED, which should lead to mitigating the generation of NP. We propose an approach to neutralize SO and ED consisting of several steps. Firstly, the nerve activity is real-time monitored. Secondly, a decision mechanism (called a ‘controller’) is developed that constructs electrical neurostimulation (ENS) patterns to neutralize SO and ED. Finally, these patterns are actually applied to the nerve by an electrical stimulator...

In the Netherlands the preterm birth rate is around 7%. The problematic part is that these preterm infants make up for 72% of all deaths during or shortly after birth. To provide a way to aid these infants the following question was stated by the doctor: "turn on a light in the Neonatal Intensive Care Unit when the preterm infant’s development is not as expected". This question was interpreted as following: first of all, find an informative signal present for preterm infants which can provide knowledge on the state of development. Secondly, find a way to quantify this signal through measurement and provide a way to automate the detection. Based on literature the delta brush was selected as a promising waveform in the neonatal EEG, which can be used to follow the maturation of the brain. The spectral behavior of the EEG is used to identify the specific waveforms, but this analysis of the EEG is still mainly based on visual analysis, which is a subjective and time-consuming task. A way to quantify and automate this process was found in the Continuous Wavelet Transform (CWT). Using the Morlet mother wavelet, a time-frequency distribution of the EEG was calculated. The CWT’s redundant behavior was found to provide a finer sampling which could be used to reinforce specific waveform behavior. A third goal was to investigate the troubles that new innovations face in being accepted by the medical field. This was found to be related to the building of trust. The key elements for building trust in this work were identified as: interpretability of the results, transparency of the process, and ease of operation. These elements will be taken into account in the proposed solution. A set of high-density EEG measurements of preterm infants was acquired through collaboration with the the Academic Hospital Antwerp and the Erasmus Medical Center. This high-density consists of 19 electrode channels instead of the more commonly used 11 electrode channels. The measurement was done at 30 weeks postmenstrual age (PMA). These measurements were accompanied with annotation for the waveform of interest. An interactive application for visualization of the EEG data and wavelet coefficients was designed in MATLAB. This application can run standalone and can be used to visualize the detector’s results for the end user. Based on the inherent characteristics of the target waveform two detection features were chosen. The first feature is a measure of the ratio between peak in the high-frequency region (3.3-40 Hz) and the low-frequency region (0.1-3.3 Hz). The second feature is an energy calculation based on a windowed Squared Energy Operator (SEO). A triple-threshold multi-channel detector, based on these features, was initialized and performance was tested over the full threshold range. A Precision-Recall (PRC) curve was provided showing the total solution space for both feature thresholds. Based on the point closest to (100,100) in the training set PRC, a single threshold was selected for validation with the validation datasets. This has resulted in a detector with a sensitivity of 73.66% and a precision of 21.71%. This performance is expected to increase with cross-validation, due to lower quality EEG datasets in the validation set. The differences in performance can be explained by the uncertainties in the exact delta brush behavior and the incomplete annotation set, which causes possible detected delta brush activity to be labeled as false positives. In the end an informative waveform was found and a suitable quantification method has been proposed. A delta brush detector has been designed based on the inherent characteristics of the waveform. A standalone interactive application has been developed to visualize the EEG signal in combination with its time-frequency behavior. The application can also be used in combination with the detector to provide insight into the decision-making process and to visualize the detector’s output.

Predicting when a neonate will fall victim to an infection or a disease allows prevention through early medicine administering. Such physiological conditions can be made visible using infrared thermography (IRT). This is a technique for measuring heat emitted in the infrared spectrum and transforming them into visible signals that can be recorded photographically. This thesis will contribute to the prediction of infection in (pre)term neonates by quantifying the interaction between IRT and a neonatal incubator without (and with) a neonate in it.  A system was designed that consisted of three modules: a measurement (incubator and IRT camera), back-end (embedded system and server), and front-end module. The scope of this thesis is limited to the measurement module and the embedded system of the back-end module. Minimum camera requirements were set up which required the camera to: be inexpensive (i.e. ≤ €1000,-), be mobile, be open-source (for Linux), have a minimum frames-per-second of 5, have a resolution of at least 160x160 pixels with a field of view (FOV) of 27°, sensitivity of < 0.1°C, and safe to the patient. Such a camera was found in the FLIR One Pro. For this thesis a different FLIR camera was used due to lack of budget, namely the FLIR A305sc, which was already available at the TU Delft. The A305sc is not open-source, which required a work-around. The Aravis Open Source Project allowed for communication with the camera. Internal camera parameters had to be determined to calculate temperature based on analogue-to-digital values. ExifTool was used on a file stored by the camera to extract these parameters. This calculated temperature was compared to the temperature as determined by FLIR’s software and led to a difference in the range of 1·106°C. An open-source application was written that can connect with this IRT camera that has a GenICam interface using Aravis. Additionally, this application implemented the temperature calculation based on the internal camera parameters. The hood of the incubator is opaque to infrared, which required the design of a measurement setup to circumvent this. Three different setups were discussed, with the final choice falling on placing the camera in front of an opened incubator porthole on a tripod, and sealing this porthole with high or low density ethyl polyethylene (HDPE/LDPE). Regular H/LDPE used for construction site was found to have a attenuated transmissivity as found in literature. To quantify the interaction between IRT and a neonatal incubator, the IRT measurements were to be compared against the current golden standard sensor, namely thermistors. These sensor values were to be read out from the incubator as this would also be used in the final product. Code was written which allows for automatic detection between the GE GiraffeTM Omnibed and the Dräger Caleo® incubator, automatic connecting, and manipulation of all sensors values to a standard string which allows for easy uploading to the InfluxDB database on the server. To be allowed to perform measurements on human subjects, approval had to be acquired by the human research ethics committee (HREC) of the TU Delft and the respective hospital. A “non-wet medisch wetenschappelijk onderzoek met mensen” (nWMO) request was submitted and approved, which resulted in 25 recorded sick and healthy neonates in incubators divided over two hospitals (the JKZ in The Hague, and the RDGG in Delft), with over 25 hours of recording material. Simultaneously, measurements were performed on an empty incubator to gain an understanding in the behaviour of an incubator when actors from outside interacted with the internal environment. Measurements that were performed included determining the reflected apparent temperature (RAT) for every possible opened porthole and for both incubator types. The RAT for the Caleo was found to be higher for every measurement for the GE. The accuracy of the IRT and hospital skin temperature sensors was compared against a calibrated Pt-100 sensor, which show that the Pt-100 sensor measures an equal value as the hospital skin temperature sensor, whereas The IRT camera measured .6°C higher. The effect of changing the distance on IRT values was measured, which shows that for a distance of 0.2m to 1.2m the accuracy of the IRT camera is within the specified accuracy. Finally, the effect of opening additional portholes on IRT was measured, the effect of the airboost setting on IRT, and the measurement of opening additional portholes was repeated with a different IRT camera. Overall the IRT camera measures a higher temperature than the hospital skin temperature sensors, but follows the skin temperature sensors’ pattern.    

Biosignals such as electoencephalogram (EEG), electrocorticogram (ECoG), atrial electrogram (AEG) etc. are being recorded from multiple channels simultaneously to improve the spatial resolution of the signals. Conventional multichannel synchronous Analog-to-Digital Converters (ADCs) are used to convert the analog continuous time signals into discrete digital values. Several biosignals have a sparsity in time domain as they have fast-rising peaks in between periods of low activity. Use of conventional synchronous ADCs for conversion of such signals is not an efficient approach as their operation is constant, irrespective of the activity of the input signals. Asynchronous ADCs such as level-crossing (LC) ADCs exploit the sparsity of biosignals and thus their operation is activity-dependent. However, multichannel configurations of LC ADCs do not yet exist. This problem is investigated in this work and a new ADC architecture is presented that can combine synchronous sampling with level-crossing quantisation method while converting input signals from several channels simultaneously. The synchronous LC ADC presented in this work achieves 3.37 times reduction in quantisation steps and 6 times reduction in number of output bits generated during conversion of AEG signals as compared to conventional synchronous ADCs. The problem in existing LC ADCs of data overhead in adaptive resolution technique is solved through a novel method named split resolution technique which is also presented in this work.

Many robotic systems rely on laser ranging sensors to navigate and map their environment. As robots are getting more advanced, smaller and cheaper, their sensors need to decrease in size and cost, while increasing their reliability and accuracy. Current laser-based sensors have difficulty to meet these properties. They are either large, expensive, contain moving parts or provide insufficient amounts of information. This thesis introduces an integrated approach for the development of an eye-safe, low-cost, solid-state, wide-angle line-laser distance sensor, tackling these challenges. A prototype is derived by constructing a generic, camera independent, triangulation model. The model, combined with a set of pre-defined requirements, is used to select hardware components and predict the sensor limits. A unified calibration step is proposed to estimate both camera intrinsics as well as misalignment errors with the same set of data. Additionally, a microsecond-accurate open loop synchronization system for laser activation and imager exposure is presented. Tests show that the prototyped sensor is able to measure distances up to 3 meters with an error of 4%. At 2 meter, the error is just under 2%. Additionally, the solid-state prototype has a field-of-view of 105 degrees, an angular resolution of 0.8 degrees, an update rate of 10Hz and an estimated cost of just below $35.

"The use of high-frequency stimulation for conduction block of the pudendal nerve has potentially high benefits for patients suffering from non-neurogenic urinary retention. Special care has to be put in the design of stimulation parameters to ensure safe operation and prevent electrode and tissue damage. While high-frequency conduction block has been studied and used for many years, only standard waveforms, such as charge balanced sinewaves and square waves, have been utilized. Several studies have anticipated that the use of non-standard, non-symmetrical and slightly charge unbalanced waveforms may provide electrochemically safer stimulation protocols. In this computational simulation study, the MRG model is combined with an electrode-tissue interface (ETI) model based on in vivo experimental data to create a computational model capable of assessing both the efficacy and electrochemical safety of any given stimulation waveform. This model is coupled to a differential evolution algorithm to find the optimal waveform parameters that ensure a successful conduction block and a minimized charge injection through irreversible faradaic reactions. The classical DE algorithm is adapted to include several improvements such as evolutionary adaptive parametrization, elitism, and variable pattern to increase its performance. Additionally, acknowledging the fact that the axonal model is the main bottleneck in computational terms, an improvement baptized as "model down-sampling" is presented. Model down-sampling consists on only executing the axonal model to determine the effectiveness of the block once every N generations. This modification manages to double the execution speed without compromising accuracy. The results show that non-standard waveforms with a slight charge imbalance keep the ETI voltage well within the narrow electrochemical safe window of -0.25V and 0.55V, thus avoiding any irreversible charge injection process. The obtained waveforms show a 39.8% improvement on the safety margin with respect to the best performing standard stimulation waveform. The obtained results prove that well designed non-standard waveforms can lead to electrochemically safer high-frequency stimulation."

Stochastic resonance (SR) is a phenomenon where the performance of a nonlinear system subjected to noise is better than it is without noise. This phenomenon can be found both in natural and artificial systems, especially in threshold-based systems such as comparators or a population of neurons. As noise always exists and interacts with the system, it is advantageous to design a system that purposefully uses SR to boost its performance. One possible use of SR is in the signal reconstruction. In this application, noise is added to the input signal and is processed by a comparator to produce a 1-bit output signal. This output can be averaged to recover the amplified input signal. In this thesis, three challenges regarding the use of SR in signal reconstruction are addressed. Firstly, to use SR not only to reconstruct the original signal, but also to implement mathematical operators, specifically a multiplier and an adder, that take two or more input signals. Secondly, to define the relevant metric(s) that can be used to measure the performance of the operators. Lastly, to build a system out of the proposed SR-based operators. The SR-based mathematical operators are implemented on the system level with a comparator as its fundamental building block. To analyze the behavior of the operators, formulas for noise and distortion power are derived. MATLAB simulation is then used to verify the theoretical analysis. Finally, these SR-based mathematical operators are used to build a Teager Energy Operator (TEO) for action potentials (APs) detection. An SR-based multiplier and adder can be implemented with the use of an XNOR logic gate and a binary half adder, respectively. The theoretical formulas are successful in predicting the noise and distortion behavior of the operators. In conclusion, it is possible to implement mathematical operators, specifically multipliers and adders, which use noise to boost their performance. The noise and distortion behavior of these operators can be predicted mathematically. Signal-to-noise ratio (SNR) and signal-to-noise-and-distortion ratio (SNDR) are used to measure the performance of the operators. Systems, specifically a TEO, can be built using the SR-based operators.

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.

Currently, EEG recordings are mostly made using scalp recording devices. These devices are typically difficult to put on and bulky, limiting their use to a lab environment. In-ear EEG recording is proposed as a more practical alternative to scalp EEG recording. In-ear EEG replaces the scalp electrode array with more discrete earpieces, recording the EEG signals from the ear canal instead of the scalp. Because of their increased convenience with respect to their scalp electrode array counterpart, the earpieces allow for everyday use, enabling the possibility of long-term EEG recording, outside of a lab environment. This work presents the design of a fully-integrated in-ear EEG device. The device has been designed to record EEG signals, process them locally, and transmit the processed data to a smartphone or personal computer. The device is made to be easily re-programmable, making it possible to change the device firmware depending on the intended application. This functionality has been integrated into a small form factor, to allow for the integration of the electronics into an earpiece. A low-power design has been created, to allow for long-term battery operation. Two prototypes have been made. The first prototype focuses on exploring different system configurations, with the small form factor less of a priority. The performance of the prototype is tested by comparing it to a commercially available scalp EEG recording device based on scalp EEG recordings. For this comparison, the auditory steady-state response (ASSR), steady-state visual evoked potential (SSVEP), and alpha-band modulation paradigms are used. The prototype has shown similar performance to the scalp EEG device in these experiments, with the scalp EEG device performing slightly better for the ASSR and alpha-band modulation paradigms, while the prototype showed the best performance for the SSVEP paradigm. The second prototype realises the best-performing system configuration that has been found with the first prototype into a form factor that fits into an earpiece. Ear EEG experiments are performed, with electrodes placed around the ears. The ASSR, SSVEP, and alpha-band modulation paradigms have again been used in these experiments. The measured performance on the ASSR and alpha-band modulation paradigms are slightly worse than that measured using the scalp EEG experiments. The SSVEP experiments showed significantly worse performance compared to the scalp EEG experiments. These results align with the expectations, as ear EEG has been documented to have performance close to scalp EEG for the ASSR and alpha-band modulation paradigms, while the SSVEP performance is typically worse for ear EEG than for scalp EEG.

Malignant Melanoma (MM) is the most aggressive type of skin-cancer. Current diagnostic tools for the detection of malignancies of the skin (MM cancer) include histological, optical, ultrasound, and impedance-based techniques. The inadequacies of the first three practices are overwhelmed by the Electrical Impedance Spectroscopy (EIS) method. EIS overcomes reported spatiotemporal tradeoffs as a label-free and optics-free analytical method. Yet, MM’s enhanced heterogeneity and metastatic potential still results in misdiagnosis, or late diagnosis leading to stages characterized by high mortality rates. Important biological information and processing ability on single-cell level is missing. Single-cell dynamics recorded with a high-throughput system, contain important biological information on the heterogeneous subpopulations which are responsible for the MM aggressiveness.This project aims to investigate experimentally the possibility and capabilities of such a bioassay development, create working protocols and generate a fundamental basis for analysis and interpretation of the big-data-sets which derive from Impedance monitoring from a high-throughput transducer.Experiments were performed, employing two diverse, human-derived, MM cancer cell-lines, and using a high-throughput HD-MEA system with a 1024-channel impedance readout unit developed at IMEC, in Belgium. The measurements were realized at 1kHz aiming to extract Rseal information. The main proposal presents an experimental protocol of mid-term and long-term experiments Temporal and spatial resolutions were enhanced (Control System Automation), allowing for implementation of an experimental set to test the assay’s capabilities and determine any necessary additions to make the assay more robust for research (i.e. Z-Map, templates and scripts for OriginLab and Matlab, statistical methods for validation of findings on the big-data sets, optimizations in the experimental process, etc).Experimental results proved the optics-free specification of the assay with the utilization of an Impedance colormap, which was validated by comparing it to confocal images after measurements. Electrode-size and normalization techniques were deemed crucial factors that affected the variance of the results for the largest and smallest electrode sizes. Confluence level (70% or 10%) of the cell on the chip was an added biasing factor. IM measurements at 1kHz for two MM cell-lines (MM087 & MM029) showed a good possibility for classification (long-term experiments), while the biological findings on the heterogeneity information (mid-term and long-term experiments) cannot be considered conclusive until a full-scale analysis is conducted on the data. A proposal for a new type of analysis on the Impedance data is presented; it is an example-based approach to extract the classification and heterogeneity information of normalized IM measurements, by obtaining and analyzing the trends of impedance variance over time, per electrode.The bioassay proposal that was developed and tested in this project shows potential for both classification and heterogeneity studies for MM cancer. Further experimentation and development of validation techniques is required.

A major cause for voiding dysfunction is the inability to relax the urethral sphincter. KiloHertz Frequency Alternating Current (KHFAC) stimulation can block signals that are travelling through the body; applying this type of stimulation at the pudendal nerve could inhibit the pulses that lead to contraction of the urethral sphincter, and restore voiding ability. In order to design a successful KHFAC block therapy for the pudendal nerve, it is necessary to understand what impact different stimulation parameters have on efficacy, safety and power-efficiency. This thesis will therefore test earlier researched KHFAC stimulation parameters against a new quality measure, study the impact of new waveform alterations, and study how bipolar electrode design can improve KHFAC therapy. By utilizing the theory behind the mechanism of the KHFAC nerve block, a new block-determination model was developed that is over thirty times faster than the classic model. The McIntyre-Richardson-Grill model was chosen as the implementation of the axon model, and the bipolar electrode was modelled as an electric dipole. The simulation experiments revealed that the charge per phase of the KHFAC signal at block threshold could be reduced, without increasing the amplitude of the signal, by introducing interphase delays to the waveforms and by creating asymmetric charge-balanced waveforms. Triangular waveforms were shown to also require less charge per phase than a regular square wave to block, albeit with a higher amplitude. A correctly aligned bipolar electrode set-up with an interpolar distance that was about the same as the electrode-to-axon distance was shown to result in reduced block thresholds. Overall, this thesis has shown how stimulation parameters can be chosen to develop an effective KHFAC block therapy for the pudendal nerve.

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.

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 𝜇V RMS noise to the output ECG signal.

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.