30 research outputs found

    Ultra-low Power Circuits for Internet of Things (IOT)

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    Miniaturized sensor nodes offer an unprecedented opportunity for the semiconductor industry which led to a rapid development of the application space: the Internet of Things (IoT). IoT is a global infrastructure that interconnects physical and virtual things which have the potential to dramatically improve people's daily lives. One of key aspect that makes IoT special is that the internet is expanding into places that has been ever reachable as device form factor continue to decreases. Extremely small sensors can be placed on plants, animals, humans, and geologic features, and connected to the Internet. Several challenges, however, exist that could possibly slow the development of IoT. In this thesis, several circuit techniques as well as system level optimizations to meet the challenging power/energy requirement for the IoT design space are described. First, a fully-integrated temperature sensor for battery-operated, ultra-low power microsystems is presented. Sensor operation is based on temperature independent/dependent current sources that are used with oscillators and counters to generate a digital temperature code. Second, an ultra-low power oscillator designed for wake-up timers in compact wireless sensors is presented. The proposed topology separates the continuous comparator from the oscillation path and activates it only for short period when it is required. As a result, both low power tracking and generation of precise wake-up signal is made possible. Third, an 8-bit sub-ranging SAR ADC for biomedical applications is discussed that takes an advantage of signal characteristics. ADC uses a moving window and stores the previous MSBs voltage value on a series capacitor to achieve energy saving compared to a conventional approach while maintaining its accuracy. Finally, an ultra-low power acoustic sensing and object recognition microsystem that uses frequency domain feature extraction and classification is presented. By introducing ultra-low 8-bit SAR-ADC with 50fF input capacitance, power consumption of the frontend amplifier has been reduced to single digit nW-level. Also, serialized discrete Fourier transform (DFT) feature extraction is proposed in a digital back-end, replacing a high-power/area-consuming conventional FFT.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137157/1/seojeong_1.pd

    Analog and Mixed Signal Design towards a Miniaturized Sleep Apnea Monitoring Device

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    Sleep apnea is a sleep-induced breathing disorder with symptoms of momentary and often repetitive cessations in breathing rhythm or sustained reductions in breathing amplitude. The phenomenon is known to occur with varying degrees of severity in literally millions of people around the world and cause a range of chronicle health issues. In spite of its high prevalence and serious consequences, nearly 80% of people with sleep apnea condition remain undiagnosed. The current standard diagnosis technique, termed polysomnography or PSG, requires the patient to schedule and undergo a complex full-night sleep study in a specially-equipped sleep lab. Due to both high cost and substantial inconvenience, millions of apnea patients are still undiagnosed and thus untreated. This research work aims at a simple, reliable, and miniaturized solution for in-home sleep apnea diagnosis purposes. The proposed solution bears high-level integration and minimal interference with sleeping patients, allowing them to monitor their apnea conditions at the comfort of their homes. Based on a MEMS sensor and an effective apnea detection algorithm, a low-cost single-channel apnea screening solution is proposed. A custom designed IC chip implements the apnea detection algorithm using time-domain signal processing techniques. The chip performs autonomous apnea detection and scoring based on the patient’s airflow signals detected by the MEMS sensor. Variable sensitivity is enabled to accommodate different breathing signal amplitudes. The IC chip was fabricated in standard 0.5-μm CMOS technology. A prototype device was designed and assembled including a MEMS sensor, the apnea detection IC chip, a PSoC platform, and wireless transceiver for data transmission. The prototype device demonstrates a valuable screening solution with great potential to reach the broader public with undiagnosed apnea conditions. In a battery-operated miniaturized medical device, an energy-efficient analog-to-digital converter is an integral part linking the analog world of biomedical signals and the digital domain with powerful signal processing capabilities. This dissertation includes the detailed design of a successive approximation register (SAR) ADC for ultra-low power applications. The ADC adopts an asynchronous 2b/step scheme that halves both conversion time and DAC/digital circuit’s switching activities to reduce static and dynamic energy consumption. A low-power sleep mode is engaged at the end of all conversion steps during each clock period. The technical contributions of this ADC design include an innovative 2b/step reference scheme based on a hybrid R-2R/C-3C DAC, an interpolation-assisted time-domain 2b comparison scheme, and a TDC with dual-edge-comparison mechanism. The prototype ADC was fabricated in 0.18μm CMOS process with an active area of 0.103 mm^(2), and achieves an ENoB of 9.2 bits and an FoM of 6.7 fJ/conversion-step at 100-kS/s

    Communication and energy delivery architectures for personal medical devices

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 219-232).Advances in sensor technologies and integrated electronics are revolutionizing how humans access and receive healthcare. However, many envisioned wearable or implantable systems are not deployable in practice due to high energy consumption and anatomically-limited size constraints, necessitating large form-factors for external devices, or eventual surgical re-implantation procedures for in-vivo applications. Since communication and energy-management sub-systems often dominate the power budgets of personal biomedical devices, this thesis explores alternative usecases, system architectures, and circuit solutions to reduce their energy burden. For wearable applications, a system-on-chip is designed that both communicates and delivers power over an eTextiles network. The transmitter and receiver front-ends are at least an order of magnitude more efficient than conventional body-area networks. For implantable applications, two separate systems are proposed that avoid reimplantation requirements. The first system extracts energy from the endocochlear potential, an electrochemical gradient found naturally within the inner-ear of mammals, in order to power a wireless sensor. Since extractable energy levels are limited, novel sensing, communication, and energy management solutions are proposed that leverage duty-cycling to achieve enabling power consumptions that are at least an order of magnitude lower than previous work. Clinical measurements show the first system demonstrated to sustain itself with a mammalian-generated electrochemical potential operating as the only source of energy into the system. The second system leverages the essentially unlimited number of re-charge cycles offered by ultracapacitors. To ease patient usability, a rapid wireless capacitor charging architecture is proposed that employs a multi-tapped secondary inductive coil to provide charging times that are significantly faster than conventional approaches.by Patrick Philip Mercier.Ph.D

    A Closed-Loop Bidirectional Brain-Machine Interface System For Freely Behaving Animals

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    A brain-machine interface (BMI) creates an artificial pathway between the brain and the external world. The research and applications of BMI have received enormous attention among the scientific community as well as the public in the past decade. However, most research of BMI relies on experiments with tethered or sedated animals, using rack-mount equipment, which significantly restricts the experimental methods and paradigms. Moreover, most research to date has focused on neural signal recording or decoding in an open-loop method. Although the use of a closed-loop, wireless BMI is critical to the success of an extensive range of neuroscience research, it is an approach yet to be widely used, with the electronics design being one of the major bottlenecks. The key goal of this research is to address the design challenges of a closed-loop, bidirectional BMI by providing innovative solutions from the neuron-electronics interface up to the system level. Circuit design innovations have been proposed in the neural recording front-end, the neural feature extraction module, and the neural stimulator. Practical design issues of the bidirectional neural interface, the closed-loop controller and the overall system integration have been carefully studied and discussed.To the best of our knowledge, this work presents the first reported portable system to provide all required hardware for a closed-loop sensorimotor neural interface, the first wireless sensory encoding experiment conducted in freely swimming animals, and the first bidirectional study of the hippocampal field potentials in freely behaving animals from sedation to sleep. This thesis gives a comprehensive survey of bidirectional BMI designs, reviews the key design trade-offs in neural recorders and stimulators, and summarizes neural features and mechanisms for a successful closed-loop operation. The circuit and system design details are presented with bench testing and animal experimental results. The methods, circuit techniques, system topology, and experimental paradigms proposed in this work can be used in a wide range of relevant neurophysiology research and neuroprosthetic development, especially in experiments using freely behaving animals

    Protocol Design and Performance Evaluation of Wake-up Radio enabled IoT Networks

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    Circuit design for embedded memory in low-power integrated circuits

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 141-152).This thesis explores the challenges for integrating embedded static random access memory (SRAM) and non-volatile memory-based on ferroelectric capacitor technology-into lowpower integrated circuits. First considered is the impact of process variation in deep-submicron technologies on SRAM, which must exhibit higher density and performance at increased levels of integration with every new semiconductor generation. Techniques to speed up the statistical analysis of physical memory designs by a factor of 100 to 10,000 relative to the conventional Monte Carlo Method are developed. The proposed methods build upon the Importance Sampling simulation algorithm and efficiently explore the sample space of transistor parameter fluctuation. Process variation in SRAM at low-voltage is further investigated experimentally with a 512kb 8T SRAM test chip in 45nm SOI CMOS technology. For active operation, an AC coupled sense amplifier and regenerative global bitline scheme are designed to operate at the limit of on current and off current separation on a single-ended SRAM bitline. The SRAM operates from 1.2 V down to 0.57 V with access times from 400ps to 3.4ns. For standby power, a data retention voltage sensor predicts the mismatch-limited minimum supply voltage without corrupting the contents of the memory. The leakage power of SRAM forces the chip designer to seek non-volatile memory in applications such as portable electronics that retain significant quantities of data over long durations. In this scenario, the energy cost of accessing data must be minimized. This thesis presents a ferroelectric random access memory (FRAM) prototype that addresses the challenges of sensing diminishingly small charge under conditions favorable to low access energy with a time-to-digital sensing scheme. The 1 Mb IT1C FRAM fabricated in 130 nm CMOS operates from 1.5 V to 1.0 V with corresponding access energy from 19.2 pJ to 9.8 pJ per bit. Finally, the computational state of sequential elements interspersed in CMOS logic, also restricts the ability to power gate. To enable simple and fast turn-on, ferroelectric capacitors are integrated into the design of a standard cell register, whose non-volatile operation is made compatible with the digital design flow. A test-case circuit containing ferroelectric registers exhibits non-volatile operation and consumes less than 1.3 pJ per bit of state information and less than 10 clock cycles to save or restore with no minimum standby power requirement in-between active periods.by Masood Qazi.Ph.D
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