Efficient digital self-calibration of video-rate pipeline ADCs using white gaussian noise

Proceedings of IEEE, ISCAS 2003, Vol.I, pp. 877-880A digital-domain self-calibration technique for video-rate pipeline A/D converters based on a white Gaussian noise input signal is presented. The implementation of the proposed algorithm requires simple digital circuitv. An application design example of the self-calibration of a IZb. 40 MUS CMOSpipeline ADC is shown to illustrate that the overall linearity of the ADC can be highly improved using this technique

Digital-domain self-calibration technique for video-rate pipeline A/D converters using Gaussian white noise

Electronics Letters Vol.38, nº 19A digital-domain selfsalibmtion technique for video-rate pipeline AID converters based an a Gaussian white noise input signal is presented. The pmposed algorithm is simple and efficient. A design example is shown 10 illustrate that the overall linemiry of a pipeline ADC can be highly improved using this technique

New simple digital self-calibration technique for pipeline ADCs using the internal thermal noise

IEEE International Symposium on Circuits and Systems, pp. 232 – 235, Seattle, EUAThis paper describes a new digital-domain selfcalibration technique for high-speed pipeline A/D converters using the internal thermal noise as input stimulus. This lowamplitude noise is amplified and recycled by the ADC itself and, due to the successive foldings, it is naturally converted into uniform noise. This noise is then used to calculate the required calibrating-codes. As an example, the calibration of a 13-bit pipeline ADC shows that the overall linearity can be significantly improved using this technique

Low-voltage low-power CMOS analogue circuits for Gaussian and uniform noise generation

IEEE International Symposium on Circuits and Systems, MAY 25-28, 2003, Bangkok, Thailand. (ISI Web of Science)A CMOS analogue circuit for Gaussian noise generution as well as a novel circuitfor transforming Gaussian noise into uniform noise, hoth.designed/or operating with a supply voltoge o/ I . S K arepresented. Both circuits are optimizedfor U 0 . 3 5st~an - dord CMOS technology using an equation-based design methodology based on generic algorithms. Electrical simulations demonstrate that high noise amplinrdes together with reasonable hondwidths can be achieved with relatively low power dissipation. Potential applications include self-calihrution and on-chip self-testing of video-rate analogue-to-digital converter

Bidirectional Neural Interface Circuits with On-Chip Stimulation Artifact Reduction Schemes

Bidirectional neural interfaces are tools designed to “communicate” with the brain via recording and modulation of neuronal activity. The bidirectional interface systems have been adopted for many applications. Neuroscientists employ them to map neuronal circuits through precise stimulation and recording. Medical doctors deploy them as adaptable medical devices which control therapeutic stimulation parameters based on monitoring real-time neural activity. Brain-machine-interface (BMI) researchers use neural interfaces to bypass the nervous system and directly control neuroprosthetics or brain-computer-interface (BCI) spellers. In bidirectional interfaces, the implantable transducers as well as the corresponding electronic circuits and systems face several challenges. A high channel count, low power consumption, and reduced system size are desirable for potential chronic deployment and wider applicability. Moreover, a neural interface designed for robust closed-loop operation requires the mitigation of stimulation artifacts which corrupt the recorded signals. This dissertation introduces several techniques targeting low power consumption, small size, and reduction of stimulation artifacts. These techniques are implemented for extracellular electrophysiological recording and two stimulation modalities: direct current stimulation for closed-loop control of seizure detection/quench and optical stimulation for optogenetic studies. While the two modalities differ in their mechanisms, hardware implementation, and applications, they share many crucial system-level challenges. The first method aims at solving the critical issue of stimulation artifacts saturating the preamplifier in the recording front-end. To prevent saturation, a novel mixed-signal stimulation artifact cancellation circuit is devised to subtract the artifact before amplification and maintain the standard input range of a power-hungry preamplifier. Additional novel techniques have been also implemented to lower the noise and power consumption. A common average referencing (CAR) front-end circuit eliminates the cross-channel common mode noise by averaging and subtracting it in analog domain. A range-adapting SAR ADC saves additional power by eliminating unnecessary conversion cycles when the input signal is small. Measurements of an integrated circuit (IC) prototype demonstrate the attenuation of stimulation artifacts by up to 42 dB and cross-channel noise suppression by up to 39.8 dB. The power consumption per channel is maintained at 330 nW, while the area per channel is only 0.17 mm2. The second system implements a compact headstage for closed-loop optogenetic stimulation and electrophysiological recording. This design targets a miniaturized form factor, high channel count, and high-precision stimulation control suitable for rodent in-vivo optogenetic studies. Monolithically integrated optoelectrodes (which include 12 µLEDs for optical stimulation and 12 electrical recording sites) are combined with an off-the-shelf recording IC and a custom-designed high-precision LED driver. 32 recording and 12 stimulation channels can be individually accessed and controlled on a small headstage with dimensions of 2.16 x 2.38 x 0.35 cm and mass of 1.9 g. A third system prototype improves the optogenetic headstage prototype by furthering system integration and improving power efficiency facilitating wireless operation. The custom application-specific integrated circuit (ASIC) combines recording and stimulation channels with a power management unit, allowing the system to be powered by an ultra-light Li-ion battery. Additionally, the µLED drivers include a high-resolution arbitrary waveform generation mode for shaping of µLED current pulses to preemptively reduce artifacts. A prototype IC occupies 7.66 mm2, consumes 3.04 mW under typical operating conditions, and the optical pulse shaping scheme can attenuate stimulation artifacts by up to 3x with a Gaussian-rise pulse rise time under 1 ms.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147674/1/mendrela_1.pd

A built-in self-test technique for high speed analog-to-digital converters

Fundação para a Ciência e a Tecnologia (FCT) - PhD grant (SFRH/BD/62568/2009

The IceCube Neutrino Observatory: Instrumentation and Online Systems

The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy neutrino detector built into the ice at the South Pole. Construction of IceCube, the largest neutrino detector built to date, was completed in 2011 and enabled the discovery of high-energy astrophysical neutrinos. We describe here the design, production, and calibration of the IceCube digital optical module (DOM), the cable systems, computing hardware, and our methodology for drilling and deployment. We also describe the online triggering and data filtering systems that select candidate neutrino and cosmic ray events for analysis. Due to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are operating and collecting data. IceCube routinely achieves a detector uptime of 99% by emphasizing software stability and monitoring. Detector operations have been stable since construction was completed, and the detector is expected to operate at least until the end of the next decade.Comment: 83 pages, 50 figures; updated with minor changes from journal review and proofin

Analysis of near-infrared dye-labeled Sanger sequencing fragments with gel electrophoresis using the time-resolved flourescence lifetime indentification methods

The research presented in this dissertation involves the identification of sequencing fragments with time-resolved methods. For this application, near-infrared heavy-atom tricarbocyanine dyes were developed in our laboratory, which can be excited with a single laser and emission collected using a single detection channel. The dyes have four spectroscopically unique, but relatively short lifetimes that can be altered by the intramolecular heavy-atom they contain. The work described here involves the optimization of dye-primer chemistry for preparing Sanger sequencing reactions for longer reads and the optimization of the separation matrix for capillary gel electrophoresis that produces favorable statistical analysis of the aforementioned dyes’ lifetimes. The performance of a two-lifetime experiment in which we modified an automated DNA sequencer to allow implementation of lifetime identification of DNA fragments labeled with near-IR fluorochromes and fractionation via slab-gel electrophoresis was investigated. A two-dye/two-lane sequencing experiment was carried out, in which two terminal bases, labeled with near-infrared dyes, were run in one lane and the other two bases in an adjacent lane. A lifetime evaluation of the resulting electropherogram on a pixel-by-pixel basis allowed the identification of the terminal nucleotide comprising a DNA band. The read accuracy was found to be better than a one-dye/four-lane approach using the software of the commercial instrument in spite of the fact that a spectroscopic call was implemented. An automated peak recognition and base calling algorithm was also implemented and evaluated on two-tract dye-primer and dye-terminator capillary electrophoresis runs. The base calling accuracy was greater than 97% for both

The prognostic value of advanced MR in gliomas

This work examines the prognostic value of advanced MR at selected time points during the early stages of treatment in glioma patients. In this thesis, serial imaging of glioma patients was conducted using diffusion tensor imaging (DTI), dynamic contrast enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI. A methodology for the processing and registration of multiparametric MRI was developed in order to simultaneously sample whole tumour measurements of multiple MR parameters with the same volume of interest.Differences between glioma grades were investigated using functional MR parameters and tested using Kruskal-Wallis tests. A 2-stage logistic regression model was developed to grade lesions from the preoperative MR, with the model retaining the apparent diffusion coefficient, radial diffusivity, anisotropic component of diffusion, vessel permeability and extravascular extracellular space parameters for glioma grading. A multi-echo single voxel spectroscopic sequence was independently investigated for the classification of gliomas into different grades.From preoperative MR, progression-free survival was predicted using the multiparametric MR data. Individual parameters were investigated using Kaplan-Meier survival analysis, before Cox regression modelling was used for a multiparametric analysis. Radial diffusivity, spin–lattice relaxation rate and blood volume fraction calculated from the DTI and DCE MRI were retained in the final model.MR parameter values were also investigated during the early stages of adjuvant treatment. Patients were scanned before and after chemoradiotherapy, with the change in MR parameters as well as the absolute values investigated for their prognostic information. Cox regression analysis was also performed for the adjuvant treatment imaging, with measures of the apparent diffusion coefficient, spin–lattice relaxation rate, vessel permeability and extravascular extracellular space, derived from the DTI and DCE datasets most predictive of progression-free survival.In conclusion, this thesis demonstrates multiparametric MR of gliomas during the early stages of treatment contains useful prognostic information relating to grade and progression-free survival interval

1-D imaging cytometry: statistical assays for immunotherapy drug screening

Modern cancer immunotherapy involves the conditioning of endogenous T cells to fight cancerous bodies that have managed to resist or avoid detection. Recently approved antibody drugs target the immune checkpoint pathway in T cells to prevent their tolerance to cancer antigens. There exists a compelling need, especially in the drug discovery world, to develop better assays for screening and to study the underlying mechanisms of these new antibody drugs. The core motivation of my work is to develop a primary cell assay for the immune checkpoint pathway using 1-D imaging cytometry. The assay is focused on high throughput and high content screening. It takes advantage of our novel 1-D imaging cytometer platform. The assay is designed to artificially induce anergy in primary human T cells and systemically study their drug response. An automated statistical method quantifies the functional phenotypes of both healthy and anergic T cells into a single descriptive readout. Reducing localization of biomarkers into a single ‘activity score’ readout has many advantages for drug screening and characterization. Additional assays were developed to study T cell activation dynamics and other signaling events during the immune checkpoint pathway. Our 1-D instrument leverages both the high throughput aspects of traditional flow cytometry and the high spatial content of 2-D imaging cytometers. The PMC data analysis emphasizes an unbiased approach to analyze flow cytometry data, which eliminates the subjective manual gating of current cytometric methods. This is crucial to developing more accurate and reliable assays with minimal supervision and need for expert operators. The high-throughput and high-content capabilities presented enable new types of assays previously not possible with human primary T cells. Adoption of physiological relevant primary cell assays has potential to revolutionize large-scale drug screening and future applications in personalized medicine