Ultra-Low Power Circuit Design for Miniaturized IoT Platform

This thesis examines the ultra-low power circuit techniques for mm-scale Internet of Things (IoT) platforms. The IoT devices are known for their small form factors and limited battery capacity and lifespan. So, ultra-low power consumption of always-on blocks is required for the IoT devices that adopt aggressive duty-cycling for high power efficiency and long lifespan. Several problems need to be addressed regarding IoT device designs, such as ultra-low power circuit design techniques for sleep mode and energy-efficient and fast data rate transmission for active mode communication. Therefore, this thesis highlights the ultra-low power always-on systems, focusing on energy efficient optical transmission in order to miniaturize the IoT systems. First, this thesis presents a battery-less sub-nW micro-controller for an always-operating system implemented with a newly proposed logic family. Second, it proposes an always-operating sub-nW light-to-digital converter to measure instant light intensity and cumulative light exposure, which employs the characteristics of this proposed logic family. Third, it presents an ultra-low standby power optical wake-up receiver with ambient light canceling using dual-mode operation. Finally, an energy-efficient low power optical transmitter for an implantable IoT device is suggested. Implications for future research are also provided.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145862/1/imhotep_1.pd

Model-based design for self-sustainable sensor nodes

Long-term and maintenance-free operation is a critical feature for large-scale deployed battery-operated sensor nodes. Energy harvesting (EH) is the most promising technology to overcome the energy bottleneck of today’s sensors and to enable the vision of perpetual operation. However, relying on fluctuating environmental energy requires an application-specific analysis of the energy statistics combined with an in-depth characterization of circuits and algorithms, making design and verification complex. This article presents a model-based design (MBD) approach for EH-enabled devices accounting for the dynamic behavior of components in the power generation, conversion, storage, and discharge paths. The extension of existing compact models combined with data-driven statistical modeling of harvesting circuits allows accurate offline analysis, verification, and validation. The presented approach facilitates application-specific optimization during the development phase and reliable long-term evaluation combined with environmental datasets. Experimental results demonstrate the accuracy and flexibility of this approach: the model verification of a solar-powered wireless sensor node shows a determination coefficient () of 0.992, resulting in an energy error of only -1.57 % between measurement and simulation. Compared to state-of-practice methods, the MBD approach attains a reduction of the estimated state-of-charge error of up to 10.2 % in a real-world scenario. MBD offers non-trivial insights on critical design choices: the analysis of the storage element selection reveals a 2–3 times too high self-discharge per capacity ratio for supercapacitors and a peak current constrain for lithium-ion polymer batteries

Hybrid of Solar Energy Harvesting using IoT and WSN Technology

Many experts consider WSNs to be one of the most important scientific topics. To fully utilize WSNs to increase the lifespan of sensors, however, is challenging due to the significant energy limits. Numerous methods for energy collecting, energy transfer, and energy conservation have been proposed.  The internet of things (IoT) manages a vast infrastructure of web-enabled smart devices. It does this by using data collected from its surroundings. Therefore, such devices are composed of scalable, light, and power-efficient storage nodes that, in order to operate practically, need electricity and batteries. The effectiveness and durability of IoT devices are undoubtedly greatly influenced by energy harvesting. The LEACH protocol is used along with the solar EH approach. The battery's charging and discharging curves as well as the nodes' energy state are depicted graphically. The converter receives switching pulses from the microcontroller, which also displays output current, solar panel voltage, and supercapacitor voltage. The simulation findings show that after using the solar EH approach, the battery and network lifetimes are increased

Wearable, low-power CMOS ISFETs and compensation circuits for on-body sweat analysis

Complementary metal-oxide-semiconductor (CMOS) technology has been a key driver behind the trend of reduced power consumption and increased integration of electronics in consumer devices and sensors. In the late 1990s, the integration of ion-sensitive field-effect transistors (ISFETs) into unmodified CMOS helped to create advancements in lab-on-chip technology through highly parallelised and low-cost designs. Using CMOS techniques to reduce power and size in chemical sensing applications has already aided the realisation of portable, battery-powered analysis platforms, however the possibility of integrating these sensors into wearable devices has until recently remained unexplored. This thesis investigates the use of CMOS ISFETs as wearable electrochemical sensors, specifically for on-body sweat analysis. The investigation begins by evaluating the ISFET sensor for wearable applications, identifying the key advantages and challenges that arise in this pursuit. A key requirement for wearable devices is a low power consumption, to enable a suitable operational life and small form factor. From this perspective, ISFETs are investigated for low power operation, to determine the limitations when trying to push down the consumption of individual sensors. Batteryless ISFET operation is explored through the design and implementation of a 0.35 \si{\micro\metre} CMOS ISFET sensing array, operating in weak-inversion and consuming 6 \si{\micro\watt}. Using this application-specific integrated circuit (ASIC), the first ISFET array powered by body heat is demonstrated and the feasibility of using near-field communication (NFC) for wireless powering and data transfer is shown. The thesis also presents circuits and systems for combatting three key non-ideal effects experienced by CMOS ISFETs, namely temperature variation, threshold voltage offset and drift. An improvement in temperature sensitivity by a factor of three compared to an uncompensated design is shown through measured results, while adding less than 70 \si{\nano\watt} to the design. A method of automatically biasing the sensors is presented and an approach to using spatial separation of sensors in arrays in applications with flowing fluids is proposed for distinguishing between signal and sensor drift. A wearable device using the ISFET-based system is designed and tested with both artificial and natural sweat, identifying the remaining challenges that exist with both the sensors themselves and accompanying components such as microfluidics and reference electrode. A new ASIC is designed based on the discoveries of this work and aimed at detecting multiple analytes on a single chip. %Removed In the latter half of the thesis, Finally, the future directions of wearable electrochemical sensors is discussed with a look towards embedded machine learning to aid the interpretation of complex fluid with time-domain sensor arrays. The contributions of this thesis aim to form a foundation for the use of ISFETs in wearable devices to enable non-invasive physiological monitoring.Open Acces

Prolonged energy harvesting for ingestible devices

Ingestible electronics have revolutionized the standard of care for a variety of health conditions. Extending the capacity and safety of these devices, and reducing the costs of powering them, could enable broad deployment of prolonged-monitoring systems for patients. Although previous biocompatible power-harvesting systems for in vivo use have demonstrated short (minute-long) bursts of power from the stomach, little is known about the potential for powering electronics in the longer term and throughout the gastrointestinal tract. Here, we report the design and operation of an energy-harvesting galvanic cell for continuous in vivo temperature sensing and wireless communication. The device delivered an average power of 0.23 μW mm⁻² of electrode area for an average of 6.1 days of temperature measurements in the gastrointestinal tract of pigs. This power-harvesting cell could provide power to the next generation of ingestible electronic devices for prolonged periods of time inside the gastrointestinal tract.National Institutes of Health (U.S.) (Grant EB-000244

Ultra Low Power Circuits for Internet of Things and Deep Learning Accelerator Design with In-Memory Computing

Collecting data from environment and converting gathered data into information is the key idea of Internet of Things (IoT). Miniaturized sensing devices enable the idea for many applications including health monitoring, industrial sensing, and so on. Sensing devices typically have small form factor and thus, low battery capacity, but at the same time, require long life time for continuous monitoring and least frequent battery replacement. This thesis introduces three analog circuit design techniques featuring ultra-low power consumption for such requirements: (1) An ultra-low power resistor-less current reference circuit, (2) A 110nW resistive frequency locked on-chip oscillator as a timing reference, (3) A resonant current-mode wireless power receiver and battery charger for implantable systems. Raw data can be efficiently transformed into useful information using deep learning. However deep learning requires tremendous amount of computation by its nature, and thus, an energy efficient deep learning hardware is highly demanded to fully utilize this algorithm in various applications. This thesis also presents a pulse-width based computation concept which utilizes in-memory computing of SRAM.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144173/1/myungjun_1.pd

Wearable electrochemical biosensors in North America

Tremendous research and commercialization efforts around the world are focused on developing novel wearable electrochemical biosensors that can noninvasively and continuously screen for biochemical markers in body fluids for the prognosis, diagnosis and management of diseases, as well as the monitoring of fitness. Researchers in North America are leading the development of innovative wearable platforms that can comfortably comply to the human body and efficiently sample fluids such as sweat, interstitial fluids, tear and saliva for the electrochemical detection of biomarkers through various sensing approaches such as potentiometric ion selective electrodes and amperometric enzymatic sensors. We start this review with a historical timeline overviewing the major milestones in the development of wearable electrochemical sensors by North American institutions. We then describe how such research efforts have led to pioneering developments and are driving the advancement and commercialization of wearable electrochemical sensors: from minimally invasive continuous glucose monitors for chronic disease management to non-invasive sweat electrolyte sensors for dehydration monitoring in fitness applications. While many countries across the globe have contributed significantly to this rapidly emerging field, their contributions are beyond the scope of this review. Furthermore, we share our perspective on the promising future of wearable electrochemical sensors in applications spanning from remote and personalized healthcare to wellness

Development of a Sensor Readout Integrated Circuit Towards a Contact Lens for Wireless Intraocular Pressure Monitoring

This design covers the design of an integrated circuit (IC) in support of the active contact lens project at Cal Poly. The project aims to monitor intraocular eye pressure (IOP) to help diagnose and treat glaucoma, which is expected affect 6.3 million Americans by 2050. The IC is designed using IBM’s 130 nm 8RF process, is powered by an on-lens thin film 3.8 V rechargeable battery, and will be fabricated at no cost through MOSIS. The IC features a low-power linear regulator that powers a current-starved voltage-controlled oscillator (CSVCO) used for establishing a backscatter communication link. Additional circuitry is included to regulate power to and from the battery. An undervoltage lockout circuit protects the battery from deep discharge damage. When recharging, a rectifier and a voltage regulator provides overvoltage protection. These circuit blocks are biased primarily using a 696 mV subthreshold voltage reference that consumes 110.5 nA