A Power-Efficient Bio-Potential Acquisition Device with DS-MDE Sensors for Long-Term Healthcare Monitoring Applications

This work describes a power-efficient bio-potential acquisition device for long-term healthcare applications that is implemented using novel microelectromechanical dry electrodes (MDE) and a low power bio-potential processing chip. Using micromachining technology, an attempt is also made to enhance the sensing reliability and stability by fabricating a diamond-shaped MDE (DS-MDE) that has a satisfactory self-stability capability and superior electric conductivity when attached onto skin without any extra skin tissue injury technology. To acquire differential bio-potentials such as ECG signals, the proposed processing chip fabricated in a standard CMOS process has a high common mode rejection ratio (C.M.R.R.) differential amplifier and a 12-bit analog-to-digital converter (ADC). Use of the proposed system and integrate simple peripheral commercial devices can obtain the ECG signal efficiently without additional skin tissue injury and ensure continuous monitoring more than 70 hours with a 400 mAh battery

Continuous-Time and Companding Digital Signal Processors Using Adaptivity and Asynchronous Techniques

The fully synchronous approach has been the norm for digital signal processors (DSPs) for many decades. Due to its simplicity, the classical DSP structure has been used in many applications. However, due to its rigid discrete-time operation, a classical DSP has limited efficiency or inadequate resolution for some emerging applications, such as processing of multimedia and biological signals. This thesis proposes fundamentally new approaches to designing DSPs, which are different from the classical scheme. The defining characteristic of all new DSPs examined in this thesis is the notion of "adaptivity" or "adaptability." Adaptive DSPs dynamically change their behavior to adjust to some property of their input stream, for example the rate of change of the input. This thesis presents both enhancements to existing adaptive DSPs, as well as new adaptive DSPs. The main class of DSPs that are examined throughout the thesis are continuous-time (CT) DSPs. CT DSPs are clock-less and event-driven; they naturally adapt their activity and power consumption to the rate of their inputs. The absence of a clock also provides a complete avoidance of aliasing in the frequency domain, hence improved signal fidelity. The core of this thesis deals with the complete and systematic design of a truly general-purpose CT DSP. A scalable design methodology for CT DSPs is presented. This leads to the main contribution of this thesis, namely a new CT DSP chip. This chip is the first general-purpose CT DSP chip, able to process many different classes of CT and synchronous signals. The chip has the property of handling various types of signals, i.e. various different digital modulations, both synchronous and asynchronous, without requiring any reconfiguration; such property is presented for the first time CT DSPs and is impossible for classical DSPs. As opposed to previous CT DSPs, which were limited to using only one type of digital format, and whose design was hard to scale for different bandwidths and bit-widths, this chip has a formal, robust and scalable design, due to the systematic usage of asynchronous design techniques. The second contribution of this thesis is a complete methodology to design adaptive delay lines. In particular, it is shown how to make the granularity, i.e. the number of stages, adaptive in a real-time delay line. Adaptive granularity brings about a significant improvement in the line's power consumption, up to 70% as reported by simulations on two design examples. This enhancement can have a direct large power impact on any CT DSP, since a delay line consumes the majority of a CT DSP's power. The robust methodology presented in this thesis allows safe dynamic reconfiguration of the line's granularity, on-the-fly and according to the input traffic. As a final contribution, the thesis also examines two additional DSPs: one operating the CT domain and one using the companding technique. The former operates only on level-crossing samples; the proposed methodology shows a potential for high-quality outputs by using a complex interpolation function. Finally, a companding DSP is presented for MPEG audio. Companding DSPs adapt their dynamic range to the amplitude of their input; the resulting can offer high-quality outputs even for small inputs. By applying companding to MPEG DSPs, it is shown how the DSP distortion can be made almost inaudible, without requiring complex arithmetic hardware

Energy Efficient Techniques For Algorithmic Analog-To-Digital Converters

Analog-to-digital converters (ADCs) are key design blocks in state-of-art image, capacitive, and biomedical sensing applications. In these sensing applications, algorithmic ADCs are the preferred choice due to their high resolution and low area advantages. Algorithmic ADCs are based on the same operating principle as that of pipelined ADCs. Unlike pipelined ADCs where the residue is transferred to the next stage, an N-bit algorithmic ADC utilizes the same hardware N-times for each bit of resolution. Due to the cyclic nature of algorithmic ADCs, many of the low power techniques applicable to pipelined ADCs cannot be directly applied to algorithmic ADCs. Consequently, compared to those of pipelined ADCs, the traditional implementations of algorithmic ADCs are power inefficient. This thesis presents two novel energy efficient techniques for algorithmic ADCs. The first technique modifies the capacitors' arrangement of a conventional flip-around configuration and amplifier sharing technique, resulting in a low power and low area design solution. The other technique is based on the unit multiplying-digital-to-analog-converter approach. The proposed approach exploits the power saving advantages of capacitor-shared technique and capacitor-scaled technique. It is shown that, compared to conventional techniques, the proposed techniques reduce the power consumption of algorithmic ADCs by more than 85\%. To verify the effectiveness of such approaches, two prototype chips, a 10-bit 5 MS/s and a 12-bit 10 MS/s ADCs, are implemented in a 130-nm CMOS process. Detailed design considerations are discussed as well as the simulation and measurement results. According to the simulation results, both designs achieve figures-of-merit of approximately 60 fJ/step, making them some of the most power efficient ADCs to date

Communication and energy delivery architectures for personal medical devices

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

The development of an electrochemical sensing device for controlled drugs.

Forensic chemists can be faced with a wide array of substances to test when attending clandestine drug manufacture crime scenes. Whilst many techniques exist at their disposal - such as chemical colour test reagents and immunoassays - these methods are at best semi-quantitative and often subject to false positives. Electrochemical methods of detection offer a potential solution to this problem, as the equipment is portable, cheap and robust. The analysis is quantitative and, if the electrode/electrolyte combination is designed properly, it can be extremely sensitive and selective. The scientific literature contains many examples of voltammetric analyses of controlled drugs. A square wave voltammetric analysis of the novel psychoactive substance benzyl-piperazine is reported here, representing the first time this analysis has been established. A limit of detection of 6 μM was achieved, and resolution against the similar ecstasy-type drug 3-4-methylenedioxymethylamphetamine (MDMA) was demonstrated. Two innovative USB powered prototype potentiostats have been developed. As proof of concept, an ATMega328P microcontroller was used in conjunction with 12-bit digital-to-analog and analog-to-digital converters (MAX532 and MCP3304 respectively). Using ferricyanide for redox at a glassy carbon electrode, reversible cyclic voltammetric analyses and square wave linear calibration (2.7 to 13.7 μM, R2=0.998) were achieved by the first prototype. The second prototype extended the compliance range (from ±2.5 V to ±12 V) and improved the signal to noise ratio. The second prototype also achieved a linear calibration using square wave voltammetry of MDMA (41 to 82 μM, R2=0.995) at a carbon paste electrode

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

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

Embedded System Design

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues