A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

Power and area efficient MOSFET-C filter for very low frequency applications

New circuit design techniques for implementing very high-valued resistors are presented, significantly improving power and area efficiency of analog front-end signal processing in ultra-low power biomedical systems. Ranging in value from few hundreds of \hbox{M}\Upomega to few hundreds of \hbox{G}\Upomega , the proposed floating resistors occupy a very small area, and produce accurately tunable characteristics. Using this approach, a low-pass MOSFET-C filter with tunable cutoff frequency (f C =20Hz-184kHz) has been implemented in a conventional 0.18μm CMOS technology. Occupying 0.045mm2/pole, the power consumption of this filter is 540 pW/Hz/pole with a measured IMFDR of 70 d

A Monolithic Gm-C Filter based Very Low Power, Programmable, and Multi-Channel Harmonic Discrimination System using Analog Signal Processing

A highly selective monolithic band-pass filter with programmable characteristics at micro-power operation is presented. Very low power signal processing is of great interest in wireless sensing and Internet-of-Things applications. This filter enables long-term battery powered operation of a highly selective harmonic signal discriminator for an analog signal processing system. The Gm-C biquadratic circuits were fabricated in a 0.18-μm [micrometer] CMOS process. Each 2nd-order biquad filter nominally consumes 20 μW [microwatt] and can be programmed for the desired gain (0db3dB), quality factor (5 to 20), and center-frequency from 1kHz to 100kHz. The 8th-order filter channel achieved an effective quality factor of 30 at 100kHz with an overall power consumption of 108 μW

HIGH PERFORMANCE CMOS WIDE-BAND RF FRONT-END WITH SUBTHRESHOLD OUT OF BAND SENSING

In future, the radar/satellite wireless communication devices must support multiple standards and should be designed in the form of system-on-chip (SoC) so that a significant reduction happen on cost, area, pins, and power etc. However, in such device, the design of a fully on-chip CMOS wideband receiver front-end that can process several radar/satellite signal simultaneously becomes a multifold complex problem. Further, the inherent high-power out-of-band (OB) blockers in radio spectrum will make the receiver more non-linear, even sometimes saturate the receiver. Therefore, the proper blocker rejection techniques need to be incorporated. The primary focus of this research work is the development of a CMOS high-performance low noise wideband receiver architecture with a subthreshold out of band sensing receiver. Further, the various reconfigurable mixer architectures are proposed for performance adaptability of a wideband receiver for incoming standards. Firstly, a high-performance low- noise bandwidthenhanced fully differential receiver is proposed. The receiver composed of a composite transistor pair noise canceled low noise amplifier (LNA), multi-gate-transistor (MGTR) trans-conductor amplifier, and passive switching quad followed by Tow Thomas bi-quad second order filter based tarns-impedance amplifier. An inductive degenerative technique with low-VT CMOS architecture in LNA helps to improve the bandwidth and noise figure of the receiver. The full receiver system is designed in UMC 65nm CMOS technology and measured. The packaged LNA provides a power gain 12dB (including buffer) with a 3dB bandwidth of 0.3G – 3G, noise figure of 1.8 dB having a power consumption of 18.75mW with an active area of 1.2mm*1mm. The measured receiver shows 37dB gain at 5MHz IF frequency with 1.85dB noise figure and IIP3 of +6dBm, occupies 2mm*1.2mm area with 44.5mW of power consumption. Secondly, a 3GHz-5GHz auxiliary subthreshold receiver is proposed to estimate the out of blocker power. As a redundant block in the system, the cost and power minimization of the auxiliary receiver are achieved via subthreshold circuit design techniques and implementing the design in higher technology node (180nm CMOS). The packaged auxiliary receiver gives a voltage gain of 20dB gain, the noise figure of 8.9dB noise figure, IIP3 of -10dBm and 2G-5GHz bandwidth with 3.02mW power consumption. As per the knowledge, the measured results of proposed main-high-performancereceiver and auxiliary-subthreshold-receiver are best in state of art design. Finally, the various viii reconfigurable mixers architectures are proposed to reconfigure the main-receiver performance according to the requirement of the selected communication standard. The down conversion mixers configurability are in the form of active/passive and Input (RF) and output (IF) bandwidth reconfigurability. All designs are simulated in 65nm CMOS technology. To validate the concept, the active/ passive reconfigurable mixer configuration is fabricated and measured. Measured result shows a conversion gain of 29.2 dB and 25.5 dB, noise figure of 7.7 dB and 10.2 dB, IIP3 of -11.9 dBm and 6.5 dBm in active and passive mode respectively. It consumes a power 9.24mW and 9.36mW in passive and active case with a bandwidth of 1 to 5.5 GHz and 0.5 to 5.1 GHz for active/passive case respectively

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