In recent years, trends in the medical industry have created a growing demand for a variety of implantable medical devices. At the same time, advances in integrated circuits techniques, particularly in CMOS, have opened possibilities for advanced implantable systems that are very small and consume minimal energy. Minimizing the volume of medical implants is important as it allows for less invasive procedures and greater comfort to patients. Minimizing energy consumption is imperative as batteries must last at least a decade without replacement. Two primary functions that consume energy in medical implants are sensor interfaces that collect information from biomedical signals, and radios that allow the implant to communicate with a base-station outside of the body. The general focus of this work was the development of circuits and systems that minimize the size and energy required to carry out these two functions. The first part of this work focuses on laying down the theoretical framework for an ultra-low power radio, including advances to the literature in the area of super-regeneration. The second part includes the design of a transceiver optimized for medical implants, and its implementation in a CMOS process. The final part describes the design of a sensor interface that leverages novel analog and digital techniques to reduce the system's size and improve its functionality. This final part was developed in conjunction with Marcus Yip.

This book describes the design of CMOS circuits for ultra-low power consumption including analog, radio frequency (RF), and digital signal processing circuits (DSP). The book addresses issues from circuit and system design to production design, and applies the ultra-low power circuits described to systems for digital hearing aids and capsule endoscope devices. Provides a valuable introduction to ultra-low power circuit design, aimed at practicing design engineers; Describes all key building blocks of ultra-low power circuits, from a systems perspective; Applies circuits and systems described to real product examples such as hearing aids and capsule endoscopes.

This book provides, for the first time, a broad and deep treatment of the fields of both ultra low power electronics and bioelectronics. It discusses fundamental principles and circuits for ultra low power electronic design and their applications in biomedical systems. It also discusses how ultra energy efficient cellular and neural systems in biology can inspire revolutionary low power architectures in mixed-signal and RF electronics. The book presents a unique, unifying view of ultra low power analog and digital electronics and emphasizes the use of the ultra energy efficient subthreshold regime of transistor operation in both. Chapters on batteries, energy harvesting, and the future of energy provide an understanding of fundamental relationships between energy use and energy generation at small scales and at large scales. A wealth of insights and examples from brain implants, cochlear implants, bio-molecular sensing, cardiac devices, and bio-inspired systems make the book useful and engaging for students and practicing engineers.

This book will describe ultra low-power, integrated circuits and systems designed for the emerging field of neural signal recording and processing, and wireless communication. Since neural interfaces are typically implanted, their operation is highly energy-constrained. This book introduces concepts and theory that allow circuit operation approaching the fundamental limits. Design examples and measurements of real systems are provided. The book will describe circuit designs for all of the critical components of a neural recording system, including: Amplifiers which utilize new techniques to improve the trade-off between good noise performance and low power consumption. Analog and mixed-signal circuits which implement signal processing tasks specific to the neural recording application: Detection of neural spikes Extraction of features that describe the spikes Clustering, a machine learning technique for sorting spikes Weak-inversion operation of analog-domain transistors, allowing processing circuits that reduce the requirements for analog-digital conversion and allow low system-level power consumption. Highly-integrated, sub-mW wireless transmitter designed for the Medical Implant Communications Service (MICS) and ISM bands.

Advances in circuits, sensors, and energy storage elements have opened up many new possibilities in the health industry. In the area of wearable devices, the miniaturization of electronics has spurred the rapid development of wearable vital signs, activity, and fitness monitors. Maximizing the time between battery recharge places stringent requirements on power consumption by the device. For implantable devices, the situation is exacerbated by the fact that energy storage capacity is limited by volume constraints, and frequent battery replacement via surgery is undesirable. In this case, the design of energy-efficient circuits and systems becomes even more crucial. This thesis explores the design of energy-efficient circuits and systems for two medical applications. The first half of the thesis focuses on the design and implementation of an ultra-low-power, mixed-signal front-end for a wearable ECG monitor in a 0.18pm CMOS process. A mixed-signal architecture together with analog circuit optimizations enable ultra-low-voltage operation at 0.6V which provides power savings through voltage scaling, and ensures compatibility with state-of-the-art DSPs. The fully-integrated front-end consumes just 2.9[mu]W, which is two orders of magnitude lower than commercially available parts. The second half of this thesis focuses on ultra-low-power system design and energy-efficient neural stimulation for a proof-of-concept fully-implantable cochlear implant. First, implantable acoustic sensing is demonstrated by sensing the motion of a human cadaveric middle ear with a piezoelectric sensor. Second, alternate energy-efficient electrical stimulation waveforms are investigated to reduce neural stimulation power when compared to the conventional rectangular waveform. The energy-optimal waveform is analyzed using a computational nerve fiber model, and validated with in-vivo ECAP recordings in the auditory nerve of two cats and with psychophysical tests in two human cochlear implant users. Preliminary human subject testing shows that charge and energy savings of 20-30% and 15-35% respectively are possible with alternative waveforms. A system-on-chip comprising the sensor interface, reconfigurable sound processor, and arbitrary-waveform neural stimulator is implemented in a 0.18[mu]m high-voltage CMOS process to demonstrate the feasibility of this system. The sensor interface and sound processor consume just 12[mu]W of power, representing just 2% of the overall system power which is dominated by stimulation. As a result, the energy savings from using alternative stimulation waveforms transfer directly to the system.

This book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors describe an approach referred to as “analog-and-algorithm-assisted” signal processing.This enables significant power consumption reductions by implementing low power biosignal acquisition systems, leveraging analog preprocessing and algorithmic approaches to reduce the data rate very early in the signal processing chain.They demonstrate savings for wearable sensor networks (WSN) and body area networks (BAN), in the sensors’ stimulation power consumption, as well in the power consumption of the digital signal processing and the radio link. Two specific implementations, an adaptive sampling electrocardiogram (ECG) acquisition and a compressive sampling (CS) photoplethysmogram (PPG) acquisition system, are demonstrated. First book to present the so called, “analog-and-algorithm-assisted” approaches for ultra-low power biosignal acquisition and processing platforms; Covers the recent trend of “beyond Nyquist rate” signal acquisition and processing in detail, including adaptive sampling and compressive sampling paradigms; Includes chapters on compressed domain feature extraction, as well as acquisition of photoplethysmogram, an emerging optical sensing modality, including compressive sampling based PPG readout with embedded feature extraction; Discusses emerging trends in sensor fusion for improving the signal integrity, as well as lowering the power consumption of biosignal acquisition systems.

The book addresses the need to investigate new approaches to lower energy requirement in multiple application areas and serves as a guide into emerging circuit technologies. It explores revolutionary device concepts, sensors, and associated circuits and architectures that will greatly extend the practical engineering limits of energy-efficient computation. The book responds to the need to develop disruptive new system architecutres, circuit microarchitectures, and attendant device and interconnect technology aimed at achieving the highest level of computational energy efficiency for general purpose computing systems. Features Discusses unique technologies and material only available in specialized journal and conferences Covers emerging applications areas, such as ultra low power communications, emerging bio-electronics, and operation in extreme environments Explores broad circuit operation, ex. analog, RF, memory, and digital circuits Contains practical applications in the engineering field, as well as graduate studies Written by international experts from both academia and industry