700mV low power low noise implantable neural recording system design

This dissertation presents the work for design and implementation of a low power, low noise neural recording system consisting of Bandpass Amplifier and Pipelined Analog to Digital Converter (ADC) for recording neural signal activities. A low power, low noise two stage neural amplifier for use in an intelligent Radio-Frequency Identification (RFID) based on folded cascode Operational Transconductance Amplifier (OTA) is utilized to amplify the neural signals. The optimization of the number of amplifier stages is discussed to achieve the minimum power and area consumption. The amplifier power supply is 0.7V. The midband gain of amplifier is 58.4dB with a 3dB bandwidth from 0.71 to 8.26 kHz. Measured input-referred noise and total power consumption are 20.7 μVrms and 1.90 μW respectively. The measured result shows that the optimizing the number of stages can achieve lower power consumption and demonstrates the neural amplifier's suitability for instu neutral activity recording. The advantage of power consumption of Pipelined ADC over Successive Approximation Register (SAR) ADC and Delta-Sigma ADC is discussed. An 8 bit fully differential (FD) Pipeline ADC for use in a smart RFID is presented in this dissertation. The Multiplying Digital to Analog Converter (MDAC) utilizes a novel offset cancellation technique robust to device leakage to reduce the input drift voltage. Simulation results of static and dynamic performance show this low power Pipeline ADC is suitable for multi-channel neural recording applications. The performance of all proposed building blocks is verified through test chips fabricated in IBM 180nm CMOS process. Both bench-top and real animal test results demonstrate the system's capability of recording neural signals for neural spike detection

A Closed-Loop Deep Brain Stimulation Device With a Logarithmic Pipeline ADC.

This dissertation is a summary of the research on integrated closed-loop deep brain stimulation for treatment of Parkinson’s disease. Parkinson's disease is a progressive disorder of the central nervous system affecting more than three million people in the United States. Deep Brain Stimulation (DBS) is one of the most effective treatments of Parkinson’s symptoms. DBS excites the Subthalamic Nucleus (STN) with a high frequency electrical signal. The proposed device is a single-chip closed-loop DBS (CDBS) system. Closed-loop feedback of sensed neural activity promises better control and optimization of stimulation parameters than with open-loop devices. Thanks to a novel architecture, the prototype system incorporates more functionality yet consumes less power and area compared to other systems. Eight front-end low-noise neural amplifiers (LNAs) are multiplexed to a single high-dynamic-range logarithmic, pipeline analog-to-digital converter (ADC). To save area and power consumption, a high dynamic-range log ADC is used, making analog automatic gain control unnecessary. The redundant 1.5b architecture relaxes the requirements for the comparator accuracy and comparator reference voltage accuracy. Instead of an analog filter, an on-chip digital filter separates the low frequency neural field potential signal from the neural spike energy. An on-chip controller generates stimulation patterns to control the 64 on-chip current-steering DACs. The 64 DACs are formed as a cascade of a single shared 2-bit coarse current DAC and 64 individual bi-directional 4-bit fine DACs. The coarse/fine configuration saves die area since the MSB devices tend to be large. Real-time neural activity was recorded with the prototype device connected to microprobes that were chronically implanted in two Long Evans rats. The recorded in-vivo signal clearly shows neural spikes of 10.2 dB signal-to-noise ratio (SNR) as well as a periodic artifact from neural stimulation. The recorded neural information has been analyzed with single unit sorting and principal component analysis (PCA). The PCA scattering plots from multi-layers of cortex represent diverse information from either single or multiple neural sources. The single-unit neural sorting analysis along with PCA verifies the feasibility of the implantable CDBS device for to in-vivo neural recording interface applications.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/60733/1/milaca_1.pd

Integrated Electronics for Wireless Imaging Microsystems with CMUT Arrays

Integration of transducer arrays with interface electronics in the form of single-chip CMUT-on-CMOS has emerged into the field of medical ultrasound imaging and is transforming this field. It has already been used in several commercial products such as handheld full-body imagers and it is being implemented by commercial and academic groups for Intravascular Ultrasound and Intracardiac Echocardiography. However, large attenuation of ultrasonic waves transmitted through the skull has prevented ultrasound imaging of the brain. This research is a prime step toward implantable wireless microsystems that use ultrasound to image the brain by bypassing the skull. These microsystems offer autonomous scanning (beam steering and focusing) of the brain and transferring data out of the brain for further processing and image reconstruction. The objective of the presented research is to develop building blocks of an integrated electronics architecture for CMUT based wireless ultrasound imaging systems while providing a fundamental study on interfacing CMUT arrays with their associated integrated electronics in terms of electrical power transfer and acoustic reflection which would potentially lead to more efficient and high-performance systems. A fully wireless architecture for ultrasound imaging is demonstrated for the first time. An on-chip programmable transmit (TX) beamformer enables phased array focusing and steering of ultrasound waves in the transmit mode while its on-chip bandpass noise shaping digitizer followed by an ultra-wideband (UWB) uplink transmitter minimizes the effect of path loss on the transmitted image data out of the brain. A single-chip application-specific integrated circuit (ASIC) is de- signed to realize the wireless architecture and interface with array elements, each of which includes a transceiver (TRX) front-end with a high-voltage (HV) pulser, a high-voltage T/R switch, and a low-noise amplifier (LNA). Novel design techniques are implemented in the system to enhance the performance of its building blocks. Apart from imaging capability, the implantable wireless microsystems can include a pressure sensing readout to measure intracranial pressure. To do so, a power-efficient readout for pressure sensing is presented. It uses pseudo-pseudo differential readout topology to cut down the static power consumption of the sensor for further power savings in wireless microsystems. In addition, the effect of matching and electrical termination on CMUT array elements is explored leading to new interface structures to improve bandwidth and sensitivity of CMUT arrays in different operation regions. Comprehensive analysis, modeling, and simulation methodologies are presented for further investigation.Ph.D

A wireless ExG interface for patch-type ECG holter and EMG-controlled robot hand

This paper presents a wearable electrophysiological interface with enhanced immunity to motion artifacts. Anti-artifact schemes, including a patch-type modular structure and real-time automatic level adjustment, are proposed and verified in two wireless system prototypes of a patch-type electrocardiogram (ECG) module and an electromyogram (EMG)-based robot-hand controller. Their common ExG readout integrated circuit (ROIC), which is reconfigurable for multiple physiological interfaces, is designed and fabricated in a 0.18 ??m CMOS process. Moreover, analog pre-processing structures based on envelope detection are integrated with one another to mitigate signal processing burdens in the digital domain effectivel

Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

Low-Noise Micro-Power Amplifiers for Biosignal Acquisition

There are many different types of biopotential signals, such as action potentials (APs), local field potentials (LFPs), electromyography (EMG), electrocardiogram (ECG), electroencephalogram (EEG), etc. Nerve action potentials play an important role for the analysis of human cognition, such as perception, memory, language, emotions, and motor control. EMGs provide vital information about the patients which allow clinicians to diagnose and treat many neuromuscular diseases, which could result in muscle paralysis, motor problems, etc. EEGs is critical in diagnosing epilepsy, sleep disorders, as well as brain tumors. Biopotential signals are very weak, which requires the biopotential amplifier to exhibit low input-referred noise. For example, EEGs have amplitudes from 1 μV [microvolt] to 100 μV [microvolt] with much of the energy in the sub-Hz [hertz] to 100 Hz [hertz] band. APs have amplitudes up to 500 μV [microvolt] with much of the energy in the 100 Hz [hertz] to 7 kHz [hertz] band. In wearable/implantable systems, the low-power operation of the biopotential amplifier is critical to avoid thermal damage to surrounding tissues, preserve long battery life, and enable wirelessly-delivered or harvested energy supply. For an ideal thermal-noise-limited amplifier, the amplifier power is inversely proportional to the input-referred noise of the amplifier. Therefore, there is a noise-power trade-off which must be well-balanced by the designers. In this work I propose novel amplifier topologies, which are able to significantly improve the noise-power efficiency by increasing the effective transconductance at a given current. In order to reject the DC offsets generated at the tissue-electrode interface, energy-efficient techniques are employed to create a low-frequency high-pass cutoff. The noise contribution of the high-pass cutoff circuitry is minimized by using power-efficient configurations, and optimizing the biasing and dimension of the devices. Sufficient common-mode rejection ratio (CMRR) and power supply rejection ratio (PSRR) are achieved to suppress common-mode interferences and power supply noises. Our design are fabricated in standard CMOS processes. The amplifiers’ performance are measured on the bench, and also demonstrated with biopotential recordings

Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices

This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability. For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality