Endoscopy is a medical procedure in which the inside of the body is looked into. Specifically, the gastrointestinal tract is of interest. This part of the body can be looked into with a swallowable wireless endoscopic pill. The pill contains different components such as different kinds of sensors, a microcontroller, a transmitter and the power supply. This thesis will discuss the power management of such a pill. The used parts are two CR1025 batteries at a voltage range of 4-6 V and capacity of 30 mAh, a TPS82150 switching converter at an efficiency of 85.8 % with an output voltage of 3.3 V, a TMP112B temperature sensor, a MS5534C pressure sensor and a CC2650 micro controller that consists of a main part (cpu), sensor controller part and a transmitter. The power used by the system was measured to be 2.74 mW per cycle. This resulted in a 57.69 hours runtime which leaves room for other sensors to be implemented and ensures a diagnosis of the whole gastrointestinal tract. All components have been put on a PCB and put into a 3D printed capsule of 123 mm in length and 33 mm in diameter.

This thesis treats designing and building a linear generator which is used to power the Battery Free Jogger Light. This harvester needs to be able to generate power from the movement of a jogger. This Battery Free Jogger Light is meant to be used by people while jogging in dark environments to improve their visibility and thus safety. The complete system consists of the energy harvester which is connected to a full-bridge rectifier. This full-bridge rectifier consists of two LEDs and two schottkydiodes. The bridge is connected to a voltage regulator which provides a constant voltage to a super-capacitor while the jogger is moving. After having the super-capacitor charged to a sufficient voltage level, the super-capacitor is able to power three other LEDs using a clocked-decade counter until the voltage level of the super-capacitor becomes to low. A MATLAB model is created to be able to optimise the parameters of the model to comply with the needs of the rest of the system. To this point the model is able to calculate the voltages which are induced in the harvester. Using the model, a prototype was designed and built which was able to deliver plenty of power to the circuitry of the device. A final prototype of the harvester is designed and built, the harvester is tested in combination with the rest of the system and the complete system is proven to be working.

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.

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.

This document describes the design process and implementation of the lighting and casing of a battery free jogger light. This light is meant to increase the safety of joggers in dark environments. The most effective way of increasing the jogger's conspicuity will be researched by considering different light sources and driver circuits to efficiently power the light source in a blinking manner. A casing will be designed to encapsulate the components. Light emitting diodes were chosen as a light source due to their energy efficiency, colour optimisation and small size. Two LEDs are part of a rectifier, while three other LEDs are powered by a driver circuit that uses a clocked decade counter 4017 IC that receives its clock signal from a NAND based oscillator circuit. The casing is designed with 3D modelling software and a prototype is 3D printed. The intended light intensity was not reached, but the brightness in dark environments was deemed suitable for the project's goals. The casing has bigger dimensions than intended; however these can be optimised for mass production.

Implantable Medical Devices (IMDs) could fulfill many different functions in the human body. Batteries have always been the main power source of these devices. Batteries have some drawbacks, the biggest one being the replacement of IMDs with fully discharged batteries. In this thesis a wireless power transfer system, with a receiving power conversion system with a maximum volume of 10 mm3, is proposed for IMDs implanted at more than 10 cm deep. Ultrasonic wireless power transfer to IMDs could enable scaling down the devices to dimensions less than 1 cm. Compared with the electromagnetic far-field and near-field wireless power transfer methods, the power throughput to the IMD is much higher. Piezo-electric elements could be used to perform the acoustic to electric energy conversion. With the Butterworth-Van Dyke modeling technique, the ultrasonic wireless power transfer link could be characterized. Maximum acoustic intensity at the receiving piezo-electric element is assumed because of the high efficiency and the possible methods to focus the waves from the transmitter at a certain point in the human body. An electrical storage element is assumed because of fluctuations both in received and used power. As the piezo-electric receiver outputs sinusoidal voltage and current waveforms, and the electrical storage element requires DC voltage, the signal requires significant processing for maximum power transfer. A perfect complex conjugate match between the piezo-electric receiver and the power conversion circuit is required for maximum power transfer as well. Two different methods which are used in prior art to achieve maximum power transfer are presented in this thesis, and one new method is developed. The standard method, which is used often in literature, does not include any special processing by means of impedance transformations and is therefore only efficient around one power level operating point. The varying frequency method varies the frequency so as to vary the piezo resistance and match it to the power conversion systems resistance. The piezo inductance varies with the varying piezo resistance, and is canceled out by tunable capacitor banks. A DC boost converter is required for high efficiency to the electric storage element. This method has many drawbacks, among which the continuous communication back to the transmitter to close the loop, which is consuming power and adding delay. The newly proposed method is the AC boost method. The AC voltage of the piezo-electric receiver is transformed into a pulse width modulated square wave voltage, so all power could go through the rectifier and into the storage element. A continuous resistive match is made between the AC boost converter and the piezo-electric element, ensuring maximum power transfer. This new method is validated by performing electric circuit simulations. Circuits are designed for the simulations that are comparable because of using the same piezo-electric element, rectifier, and storage element. The simulations show that it is the most efficient method for a wide load power range of 10 µW to 5 mW. The standard method is as efficient but only at a small range at high power level. The varying frequency method is much more complex and has, therefore, lower power efficiency at high power levels whereas at low power levels it has the same power efficiency.

Patients that suffer from heart failure can benefit from wearable monitoring devices that continuouslymonitor the condition of the heart. One of the foremost symptoms of exacerbation of the heart is fluidcongestion in the lungs. One of the method to measure a change in biological tissue, such as thebuild­up of fluids in the lungs and chest, is bioimpedance measurements. By injecting an alternatingcurrent into the tissue, a voltage develops across the tissue that is proportional to the impedance ofthe biological tissue, the bioimpedance. Conventional bioimpedance measurement techniques are notsuitable for continuous monitoring of the patients as they are power consuming and hinder patient intheir daily living.This thesis proposes an alternative approach that is based on a pulse width modulation (PWM) inorder to convert the measured analog signals to time signals. To determine the measured bioimped­ance, the magnitude and phase should be derived. The proposed design employs one channel toconvert the measured voltage across the bioimpedance to a PWM signal. As this PWM signal con­tains the amplitude information of the measured voltage, the magnitude of the bioimpedance can bederived. Furthermore, a second reference channel is employed where a known resistive reference isconverted to another PWM signal. By comparing the two PWM signals, the phase of the bioimpedancecan be determined. The proposed system requires only a comparator and triangular wave in order toconvert the measured analog signals, compared to the complex implementation of the conventionallyused analog­to­digital converter.In order to validate the design, the circuit is simulated and implemented on a printed circuit board (PCB). The PCB operates correctly on 3.3V and, additionally, an voltage­controlled current sourceis implemented and connected externally to the PCB to provide an excitation current of 100μA and10kHz to the circuit. The circuit should be capable of measuring the voltage across a device under test(퐷푈푇) that consist of resistive and capacitive components. This is because the bioimpedance can bemodelled by the Fricke­Morse model, which consist of a resistor in parallel with a capacitor and resistorin series. The implemented PCB can measure 퐷푈푇 magnitudes up to 1kΩ and is determine the phaseshift between the two PWM signals.This work shows an important contribution towards a wearable continuous bioimpedance measure­ments system to monitor patient that suffer from heart failure. It has been shown that the presenteddesign can measure the magnitude and phase that are required to determine the measured bioimped­ance, and also reduce complexity of the measurements instrumentation.

Biosensing has been developed rapidly for a number of biomedical applications, including neural monitoring, protein detection, bacteria detection and blood glucose monitoring. Among the branches of bio-sensing, capacitive sensing is a promising technique and utilized widely, since it is rapid, simple, label free and inexpensive. Compared with traditional capacitance sensing front end, capacitance to frequency (CFC) based frontend can be utilized to measure the capacitance change based on the frequency shift in the output. LC voltage-controlled oscillator (VCO) based CFC benefits from low power, low cost, high sensitivity, embedded wireless capability and miniaturized characterization, and it can be based on passive or active approaches. The limitation of cutting edge LC VCO based system is they are single channel. This thesis presents the design of a 3-by-3 400-MHz LC VCO based microsensor array for measuring bacteria concentration and related bio-analyte which behave capacitively in that frequency range. This would allow for high-resolution wireless capacitive sensing in a power-efficient way. The wireless capacitive microsensor array has been designed in a standard 0.18 um CMOS process. The sensor array is comprised of 3-by-3 pixels, and it is implemented by customized interdigitated capacitors. Each pixel has two customized 10.5 um * 10.5 um capacitors with 100fF capacitance value. A class-B VCO is implemented with 300fF buried metal-oxide metal (MOM) capacitor and 300nH off-chip inductor. The class-B oscillator converts the capacitance change in the sensor array into frequency shift and transmits the signal through wireless inductance link. The central frequency varies within ±3.3 MHz, with less than 1.4% RMS phase noise in process corners. By post-layout extraction, the circuit has 417 kHz/fF responsivity, 99.8% R^2 value and 1.5% RMS phase noise. Each pixel occupies and area of 30 um * 25 um area. In total, the whole front-end core circuit takes 140 um* 160 um chip area. This project contributes to further development of the multichannel LC VCO based sensing system, which could be utilized as a multi-channel low-power capacitance sensing technique in a long-term vision with combined detection and wireless transmission in the same front-end.

The functioning of the brain depends on the interplay between a large number of neurons. To understand the information processing in neuronal networks, we need tools to record the electrical activity of cells at high resolution. Microelectrode arrays (MEAs) are predominantly used to measure neuronal activity at high spatial and temporal resolution. With the advent of complementary metal-oxide-semiconductor (CMOS) based MEAs, it has been possible to design high-density MEAs with electrode sizes comparable to that of the individual neurons, allowing sub-cellular resolution. CMOS technology has also facilitated the on-chip signal conditioning needed to record the low-amplitude bio-signals with superior signal quality. In this thesis, a readout architecture for in-vitro MEAs has been proposed for a low-noise extracellular action potential (AP) readout. One of the challenges in MEA implementation is the design of thousands of low-noise readout channels for simultaneously recording the signals. There is a need to design low-noise ADCs with optimal power and area consumption. In this thesis, a unique low-noise oscillator based sigma-delta ADC has been designed for MEA applications. With the advantages of oversampling and time-encoding techniques, the in-band noise has been optimized, without increased hardware complexity. The simple implementation of this proposed ADC makes it efficient in terms of area and power consumption. The integrated circuit for this oscillator based sigma-delta ADC has been implemented in 0.18 um CMOS technology to demonstrate the feasibility of high-order oscillator-based ADCs for low-noise extracellular AP readout. It was possible to obtain a noise below 5 uVRMS (simulations) and power consumption under 3 uW using this ADC, which approximately occupies an area of 0.002 mm2. The action potential readout system implemented with this ADC has been taped-out for further analysis through measurements.

MRI machine has evolved tremendously over the years from its inception in order to render high-quality 3D images, best among its companion imaging systems. Of the whole system, RF receiver is the most crucial for its noise performance, which is expected to provide high SNR at all operating conditions. At Philips, MRI’s RF receiver is based on direct-digitization architecture which has replaced the bulky data-acquisition system with an integrated on-coil receiver. It allows a lot of signal processing to be done digitally which was earlier done in analog-domain, thus improving the SNR and dynamic range to more than 100 dB. However, this has increased the design restrictions of the remaining analog front-end. The high-frequency bandpass filter employed to select the signal band around the receiver’s resonance frequency has not only become highly selective (Q 400, 6th order) to narrow down the signal bandwidth and reject the rest with a high stopband attenuation but also incorporates a high passband gain (60 dB), unlikely to see otherwise. Operating at a high frequency of 100’s of MHz, with such a response, the filter can become drastically sensitive to the shift in its components with varying operating conditions. At Philips, the filter uses transconductor as one of its building blocks and filter frequency response is heavily dependent on the transconductance of the unit cell as they are employed in large number in the circuit. The transconductor cell, at Philips, shows 15% deviation with the process, supply and temperature variations. This leads to more than 10% variation in the passband gain of the filter. Operating at low supply voltage, such a deviation in MRI filter can deteriorate its output SNR and dynamic range by 10dB. In this thesis, a new inverter-based self-biased transconductance circuit has been proposed, which shows a deviation of ±2.5% in transconductance under the process, temperature and supply variations. It limits the passband gain of the filter to 60 dB±2% and bandwidth shows a deviation of less than 0.1%. However, the center frequency is matched precisely with the resonance frequency of the receiver by the external components of the filter. Given, this matching is the basis for the working principle of MRI receiver. With the proposed transconductance circuit, the filter shows an SNR of 112 dB, THD of -63 dB and consumes a power of 0.8 mW. The circuit has been implemented in 40 nm TSMC process and simulated for a temperature range of 0°C -85°C at the power supply of 1.1 V±10%, post-extraction.

Endoscopic devices are used in the medical world to inspect the gastrointestinal tract. Because there are some complications with wired endoscopy, such as reaching the small intestine, there is a need for new methods to do endoscopy. Therefore an endoscopic pill is invented which can be used to do measurements in the gastrointestinal tract. This endoscopic pill is a small device with small sized electronic sensing elements. This thesis goes through the implementation process of sensors inside an endoscopic pill in order to be able to perform measurements inside the human body. The sensors used in the endoscopic pill are a temperature and a pressure sensor. Besides that, this thesis also goes through the design process of the 3D design of the capsule, which is later 3D printed. The goal of the project is to make a prototype which contains functioning sensors and which can be made swallowable during future work.

Psychiatric disorders are associated with major societal, personal issues and comprise 13% of the global burden of disease. They are heritable and present a complex pathophysiology, characterized by hundreds of genetic variants which are cumulated together and provoke a specific psychiatric disorder. Although a considerable progress has been made in the identification of genetics variants, the way a cellular phenotype is related to a gene expression caused by biological pathways remains unclear. Significant effort has been focused, over the last years, on psychiatric diseases modeling, to investigate the complex, polygenic neurobiological nature of these disorders. Human induced pluripotent stem cell (iPSC) technology has been widely used for in vitro disease modeling. Human iPSCs can be readily derived from patients and differentiated into any cell type including neurons. The functional characterization of neurons constitutes a challenging procedure and different electrophysiological techniques can be applied. A hallmark of a non-invasive technique, in which the neuronal network dynamics can be observed, is the Microelectrode Array (MEA) measurements. The functional characterization of neuronal activity contributes to the cellular phenotype investigation of neuronal cultures, derived from patients who are affected by psychiatric disorders. The cellular phenotypes could be used as readouts for high-throughput pharmacological screenings and enhance the development of new drugs. In the current thesis project, the combination of a long-term neural differentiation protocol with extracellular MEA measurements was implemented, to assess the spontaneous and synchronized network activity of human iPSC-derived neural cultures. This protocol generates both neurons and astrocytes from a common neural progenitor cell (NPC) into a control ratio (60:40). A commercial MEA system (Multiwell-MEA, Multi Channel Systems, GmbH, Germany) was used for extracellular recordings on the neural populations. Additionally, a spike sorting analysis was performed for spike waveform observation. Experimental results presented a robust network activity derived from neural populations cultivated in neuronal medium (BrainPhys), for a period of ten weeks in vitro. Neuronal activity was characterized in terms of cumulative firing rate (CFR) per cell culture and mean firing rate (MFR) per electrode. Results showed a peak CFR of 1700 spikes/minute/culture (±260 SEM) and a peak MFR of 215 spikes/minute/electrode (±22.5 SEM). Additionally, a bursting activity was constantly detected on a scale of 270 burst/10 minutes/culture (±31 SEM), during the period of ten weeks in vitro. A spike sorting analysis verified the successful monitoring of spikes’ waveforms derived from the same unit of neurons in a two-week period. 88% of the detected waveform patterns presented a normalized cross-correlation higher than 0.9, which reinforced the argument that the electrodes detected electrical activity derived from the same unit of neurons in a constant way. This project contributes to the creation of an optimized functional readout of human neural model in vitro, which, in a long-term vision, could be used as reference point for comparison between healthy and diseased cell lines derived from patients with psychiatric disorders.

Microelectrode arrays (MEAs) are extensively used for measuring neural activity in-vitro given their ability to monitor several neurons simultaneously unlike techniques such as patch clamp. However, MEAs still have limitations in acquiring high spatial resolution data due to limited number of channels that can be parallelly scanned, the need for bulky anti-aliasing filters, and limitations in signal-to-noise ratio (SNR) arising from thermal noise. Commercially available MEAs rely on resistive or self-capacitive sensing scheme, but this research proposes a new approach to increase the number of sensing locations while reducing the channels and to increase SNR. Fundamental design aspects of a MEA such as the shape and size of electrodes are revisited. By employing traditional lithographic fabrication techniques, these arrays with various geometries are fabricated and characterized. Neural cultures are seeded on these novel MEAs to record neural activity in the electrical domain and concurrently Ca+2 Imaging is performed to correlate and verify the activity of a neuron.