A Low-Power Wireless Multichannel Microsystem for Reliable Neural Recording.

This thesis reports on the development of a reliable, single-chip, multichannel wireless biotelemetry microsystem intended for extracellular neural recording from awake, mobile, and small animal models. The inherently conflicting requirements of low power and reliability are addressed in the proposed microsystem at architectural and circuit levels. Through employing the preliminary microsystems in various in-vivo experiments, the system requirements for reliable neural recording are identified and addressed at architectural level through the analytical tool: signal path co-optimization. The 2.85mm×3.84mm, mixed-signal ASIC integrates a low-noise front-end, programmable digital controller, an RF modulator, and an RF power amplifier (PA) at the ISM band of 433MHz on a single-chip; and is fabricated using a 0.5µm double-poly triple-metal n-well standard CMOS process. The proposed microsystem, incorporating the ASIC, is a 9-channel (8-neural, 1-audio) user programmable reliable wireless neural telemetry microsystem with a weight of 2.2g (including two 1.5V batteries) and size of 2.2×1.1×0.5cm3. The electrical characteristics of this microsystem are extensively characterized via benchtop tests. The transmitter consumes 5mW and has a measured total input referred voltage noise of 4.74µVrms, 6.47µVrms, and 8.27µVrms at transmission distances of 3m, 10m, and 20m, respectively. The measured inter-channel crosstalk is less than 3.5% and battery life is about an hour. To compare the wireless neural telemetry systems, a figure of merit (FoM) is defined as the reciprocal of the power spent on broadcasting one channel over one meter distance. The proposed microsystem’s FoM is an order of magnitude larger compared to all other research and commercial systems. The proposed biotelemetry system has been successfully used in two in-vivo neural recording experiments: i) from a freely roaming South-American cockroach, and ii) from an awake and mobile rat.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91542/1/aborna_1.pd

A Design Methodology for Low Power CMOS Current Source

A current reference circuit is a basic building block in analog, digital and mixed-signal design systems. This work focuses on one type of integrated CMOS current reference circuit. This source only uses one type of MOSFET transistor and is suitable to produce very low currents in the order of nano Amperes. Despite being used in several works in the literature, there is no clear methodology to produce an optimal design for this source. With the absence of a design methodology, process variability becomes critical in affecting the performance of the current source. This variability issue is prominent in nanometer scaling of the technology. This work addresses that problem by developing a methodology to achieve a design with low area and low sensitivity to transistor mismatch. Presented are the sensitivity and mismatch analysis, methodology, design example and results in addi- tion to performance figures for a lesser sensitive circuit as compared with its traditional counterpart. Future scope of research has also been included in this thesis

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

Variability-aware design of CMOS nanopower reference circuits

Questo lavoro è inserito nell'ambito della progettazione di circuiti microelettronici analogici con l'uso di tecnologie scalate, per le quali ha sempre maggiore importanza il problema della sensibilità delle grandezze alle variazioni di processo. Viene affrontata la progettazione di generatori di quantità di riferimento molto precisi, basati sull’uso di dispositivi che sono disponibili anche in tecnologie CMOS standard e che sono “intrinsecamente” più robusti rispetto alle variazioni di processo. Questo ha permesso di ottenere una bassa sensibilità al processo insieme ad un consumo di potenza estremamente ridotto, con il principale svantaggio di una elevata occupazione di area. Tutti i risultati sono stati ottenuti in una tecnologia 0.18μm CMOS. In particolare, abbiamo progettato un riferimento di tensione, ottenendo una deviazione standard relativa della tensione di riferimento dello 0.18% e un consumo di potenza inferiore a 70 nW, sulla base di misure su un set di 20 campioni di un singolo batch. Sono anche disponibili risultati relativi alla variabilità inter batch, che mostrano una deviazione standard relativa cumulativa della tensione di riferimento dello 0.35%. Abbiamo quindi progettato un riferimento di corrente, ottenendo anche in questo caso una sensibilità al processo della corrente di riferimento dell’1.4% con un consumo di potenza inferiore a 300 nW (questi sono risultati sperimentali ottenuti dalle misure su 20 campioni di un singolo batch). I riferimenti di tensione e di corrente proposti sono stati quindi utilizzati per la progettazione di un oscillatore a rilassamento a bassa frequenza, che unisce una ridotta sensibilità al processo, inferiore al 2%, con un basso consumo di potenza, circa 300 nW, ottenuto sulla base di simulazioni circuitali. Infine, nella progettazione dei blocchi sopra menzionati, abbiamo applicato un metodo per la determinazione della stabilità dei punti di riposo, basato sull’uso dei CAD standard utilizzati per la progettazione microelettronica. Questo approccio ci ha permesso di determinare la stabilità dei punti di riposo desiderati, e ci ha anche permesso di stabilire che i circuiti di start up spesso non sono necessari

Applications of acoustics in the measurement of coal slab thickness

The determination of the possibility of employing acoustic waves at ultrasonic frequencies for measurements of thicknesses of slabs of coal backed by shale is investigated. Fundamental information concerning the acoustical properties of coal, and the relationship between these properties and the structural and compositional parameters used to characterize coal samples was also sought. The testing device, which utilizes two matched transducers, is described

MPPT Solar Charge Contoller For Portable

The purpose of our senior project was to design and prototype an MPPT charge controller for small capacity PV panels under varying temperature and irradiance conditions to charge portable devices. In this paper we discuss our research, simulation, design, and testing to develop an MPPT solar charge controller. Furthermore, we presented our results and findings from testing our design. An MPPT solar charge controller is feasible and affordable if implemented on a PCB board. Due to MPPT’s affordability and increased efficiency under dynamic conditions, an MPPT solar charge controller for portable devices would be more effective than solar chargers currently sold without MPPT

Dynamic Pressure Sensing for the Flight Test Data System

This thesis describes the design, assembly, and test of the FTDS-K, a new device in the Boundary Layer Data System (BLDS) family of flight data acquisition systems. The FTDS-K provides high-frequency, high-gain data acquisition capability for up to two pressure sensors and an additional three low-frequency pressure sensors. Development of the FTDS-K was separated into a core module, specialized analog subsystem, and practical testing of the FTDS-K in a flow measurement mission. The core module combines an nRF52840-based microcontroller module, switching regulator, microSD card, real-time clock, temperature sensor, and trio of pressure sensors to provide the same capabilities as previous-generation BLDS-P devices. An expansion header is included in the core module to allow additional functionality to be added via daughter boards. An analog signal chain comprised of two-stage amplification and fourth-order active antialiasing filters was implemented as a daughter board to provide an AC-coupled end-to-end gain of 7,500 and a DC-coupled end-to-end gain of 50. This arrangement was tested in a wind tunnel to demonstrate that sensors with a full-scale range of 103 kPa can be used to reliably discriminate between laminar and turbulent flows based on pressure fluctuation differences on the order of tens of Pa. A combination of wind-off correction and band-filtering was used to reduce the effect of inherent and induced electrical noise, while two-sensor correlation was tested and shown to be effective at removing certain types of noise. Total power consumption for the FTDS-K in a representative mission is 208 mW, which translates to an operational endurance of 9 hours with 2 AAA LiFeS2 cells at -40°C

Design of a Low-Cost Passive UHF RFID tag in 0.18um CMOS technology

The work addresses the design of a passive UHF Radio-Frequency Identification (RFID) tag. In order to realize a product able to be competitive in the RFID expanding market, a cost reduction policy has been applied in the design: a general purpose digital technology has been employed, resorting to specific techniques in order to overcome the limitations due to the lack of process options. Such solutions are accurately described, and every block composing the transponder analog frontend is analyzed, highlighting advantages and disadvantages of the proposed architectures with respect to the ones present in literature. The circuits theory is validated through simulations and experimental data.Il lavoro di tesi è imperniato sul progetto di un tag passivo per l'Identificazione a Radio-Frequenza (RFID) operante nelle bande UHF. Per il progetto è stata applicata una politica di riduzione dei costi, così da proporre un prodotto in grado di essere competitivo nel fiorente mercato dell'RFID: è stata scelta una tecnologia digitale general-purpose, e specifiche tecniche di progettazione sono state utilizzate per superare le limitazioni dovute alla scarsità di opzioni di processo. Le soluzioni adottate sono descritte accuratamente, ed è riportata l'analisi di ogni singolo blocco componente il frontend analogico, evidenziando vantaggi e svantaggi delle architetture proposte rispetto a quelle presenti in letteratura. La validità della teoria alla base dei circuiti è stata verificata tramite simulazioni e dati sperimentali

CMOS SPAD-based image sensor for single photon counting and time of flight imaging

The facility to capture the arrival of a single photon, is the fundamental limit to the detection of quantised electromagnetic radiation. An image sensor capable of capturing a picture with this ultimate optical and temporal precision is the pinnacle of photo-sensing. The creation of high spatial resolution, single photon sensitive, and time-resolved image sensors in complementary metal oxide semiconductor (CMOS) technology offers numerous benefits in a wide field of applications. These CMOS devices will be suitable to replace high sensitivity charge-coupled device (CCD) technology (electron-multiplied or electron bombarded) with significantly lower cost and comparable performance in low light or high speed scenarios. For example, with temporal resolution in the order of nano and picoseconds, detailed three-dimensional (3D) pictures can be formed by measuring the time of flight (TOF) of a light pulse. High frame rate imaging of single photons can yield new capabilities in super-resolution microscopy. Also, the imaging of quantum effects such as the entanglement of photons may be realised. The goal of this research project is the development of such an image sensor by exploiting single photon avalanche diodes (SPAD) in advanced imaging-specific 130nm front side illuminated (FSI) CMOS technology. SPADs have three key combined advantages over other imaging technologies: single photon sensitivity, picosecond temporal resolution and the facility to be integrated in standard CMOS technology. Analogue techniques are employed to create an efficient and compact imager that is scalable to mega-pixel arrays. A SPAD-based image sensor is described with 320 by 240 pixels at a pitch of 8μm and an optical efficiency or fill-factor of 26.8%. Each pixel comprises a SPAD with a hybrid analogue counting and memory circuit that makes novel use of a low-power charge transfer amplifier. Global shutter single photon counting images are captured. These exhibit photon shot noise limited statistics with unprecedented low input-referred noise at an equivalent of 0.06 electrons. The CMOS image sensor (CIS) trends of shrinking pixels, increasing array sizes, decreasing read noise, fast readout and oversampled image formation are projected towards the formation of binary single photon imagers or quanta image sensors (QIS). In a binary digital image capture mode, the image sensor offers a look-ahead to the properties and performance of future QISs with 20,000 binary frames per second readout with a bit error rate of 1.7 x 10-3. The bit density, or cumulative binary intensity, against exposure performance of this image sensor is in the shape of the famous Hurter and Driffield densitometry curves of photographic film. Oversampled time-gated binary image capture is demonstrated, capturing 3D TOF images with 3.8cm precision in a 60cm range

Analog VLSI Circuits for Biosensors, Neural Signal Processing and Prosthetics

Stroke, spinal cord injury and neurodegenerative diseases such as ALS and Parkinson's debilitate their victims by suffocating, cleaving communication between, and/or poisoning entire populations of geographically correlated neurons. Although the damage associated with such injury or disease is typically irreversible, recent advances in implantable neural prosthetic devices offer hope for the restoration of lost sensory, cognitive and motor functions by remapping those functions onto healthy cortical regions. The research presented in this thesis is directed toward developing enabling technology for totally implantable neural prosthetics that could one day restore lost sensory, cognitive and motor function to the victims of debilitating neural injury or disease. There are three principal components to this work. First, novel integrated biosensors have been designed and implemented to transduce weak extra-cellular electrical potentials and optical signals from cells cultured directly on the surface of the sensor chips, as well as to manipulate cells on the surface of these chips. Second, a method of detecting and identifying stereotyped neural signals, or action potentials, has been mapped into silicon circuits which operate at very low power levels suitable for implantation. Third, as one small step towards the development of cognitive neural implants, a learning silicon synapse has been implemented and a neural network application demonstrated. The original contributions of this dissertation include: * A contact image sensor that adapts to background light intensity and can asynchronously detect statistically significant optical events in real-time; * Programmable electrode arrays for enhanced electrophysiological recording, for directing cellular growth, for site-specific in situ bio-functionalization, and for analyte and particulate collection; * Ultra-low power, programmable floating gate template matching circuits for the detection and classification of neural action potentials; * A two transistor synapse that exhibits spike timing dependent plasticity and can implement adaptive pattern classification and silicon learning