Design of ultra low power analog-to-digital converter for ambulatory EEG recording

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 65-67).Portable acquisition of biopotential signals requires the design of compact, energy efficient circuits and systems. Such systems typically include analog-to-digital converter for digitizing signals from AFE and feeding it to DBE. An Ultra low power ADC is designed in this work to be integrated within scalable EEG SoC. The full system can capture EEG signals through 1 up to 8 parallel differential channels that are time division multiplexed into a single ADC. The ADC has a fixed resolution of 10 bits which is sufficient for extraction of bio-markers for seizure detection. A SAR ADC architecture is chosen for this design as it is highly energy efficient for medium to high resolution applications with low speed requirements. A differential capacitive DAC is utilized to enhance the CMRR. Concepts of split-capacitor array and sub-DAC are combined to reduce the DAC area and power consumption. Charge pumps are used to boost the control voltage of sampling switches. The ADC performs a conversion every 16 clock cycle while being governed by a self-resetting SAR logic. The sampling rate can be scaled up to 32 kHz by varying the clock frequency to accommodate different number of channels used. The ADC was designed and fabricated in a 0.18 pm CMOS technology. The entire ADC core consumes 1 pW from 1 V supply at a sampling rate of 32 kHz. The ADC has a maximum DNL and INL of 0.55 LSB and 0.75 LSB respectively. The SNDR and SFDR of the converter are measured at a sampling rate of 32 kHz and 15.5 kHz input tone to be 57.9 dB and 68.5 dBFS respectively. The ADC FOM is 51 fJ/Conv-Step.by Dina Reda El-Damak.S.M

Fully-passive switched-capacitor techniques for high performance SAR ADC design

In recent years, SAR ADC becomes more and more popular in various low-power applications such as wireless sensors and low energy radios due to its circuit simplicity, high power efficiency, and scaling compatibility. However, its speed is limited by its successive approximation procedures and its power efficiency greatly reduces with the ADC resolution going beyond 10 bit. To address these issues, this thesis proposes to embed two techniques: 1) compressive sensing (CS) and 2) noise shaping (NS) to a conventional SAR ADC. The realization of both techniques are based on fully-passive switched-capacitor techniques. CS is a recently emerging sampling paradigm, stating that the sparsity of a signal can be exploited to reduce the ADC sampling rate below the Nyquist rate. Different from conventional CS frameworks which require dedicated analog CS encoders, this thesis proposes a fully-passive CS-SAR ADC architecture which only requires minor modification to a conventional SAR ADC. Two chips are fabricated in a 0.13 µm process to prove the concept. One chip is a single-channel CS-SAR ADC which can reduce the ADC conversion rate by 4 times, thus reducing the ADC power by 4 times. In many wireless sensing applications, multiple ADCs are commonly required to sense multi-channel signals such as multi-lead ECG sensing and parallel neural recording. Therefore, the other chip is a multi-channel CS-SAR ADC which can simultaneously convert 4-channel signals with a sampling rate of one channel’s Nyquist rate. At 0.8 V and 1 MS/s, both chips achieve an effective Walden FoM of around 5 fJ/conversion-step. This thesis also proposes a novel NS SAR ADC architecture that is simple, robust and low power for high-resolution applications. Compared to conventional ∆Σ ADCs, it replaces the power-hungry active integrator with a passive integrator which only requires one switch and two capacitors. Compared to previous 1st-order NS SAR ADC works, it achieves the best NS performance and can be easily extended to 2nd-order. A 1st-order 10-bit NS SAR ADC is fabricated in a 0.13 µm process. Through NS, SNDR increases by 6 dB with OSR doubled, achieving a 12- bit ENOB at OSR = 8. An improved version of a 2nd-order 9-bit NS SAR ADC is designed and simulated in a 40 nm process. The SNDR increases by 10 dB with OSR doubled, achieving a 14-bit ENOB at OSR = 16. At a bandwidth of 312.5 kHz, the Schreier FoM is 181 dB and the Walden FoM is 12.5 fJ/conversion-step, proving that the proposed NS SAR ADC architecture can achieve high resolution and high power efficiency simultaneously.Electrical and Computer Engineerin

A Resolution-Reconfigurable 5-to-10-Bit 0.4-to-1 V Power Scalable SAR ADC for Sensor Applications

A power-scalable SAR ADC for sensor applications is presented. The ADC features a reconfigurable 5-to-10-bit DAC whose power scales exponentially with resolution. At low resolutions where noise and linearity requirements are reduced, supply voltage scaling is leveraged to further reduce the energy-per-conversion. The ADC operates up to 2 MS/s at 1 V and 5 kS/s at 0.4 V, and its power scales linearly with sample rate down to leakage levels of 53 nW at 1 V and 4 nW at 0.4 V. Leakage power-gating during a SLEEP mode in between conversions reduces total power by up to 14% at sample rates below 1 kS/s. Prototyped in a low-power 65 nm CMOS process, the ADC in 10-bit mode achieves an INL and DNL of 0.57 LSB and 0.58 LSB respectively at 0.6 V, and the Nyquist SNDR and SFDR are 55 dB and 69 dB respectively at 0.55 V and 20 kS/s. The ADC achieves an optimal FOM of 22.4 fJ/conversion-step at 0.55 V in 10-bit mode. The combined techniques of DAC resolution and voltage scaling maximize efficiency at low resolutions, resulting in an FOM that increases by only 7x over the 5-bit scaling range, improving upon a 32x degradation that would otherwise arise from truncation of bits from an ADC of fixed resolution and voltage.United States. Defense Advanced Research Projects AgencyNatural Sciences and Engineering Research Council of Canad

Systematic Design Methodology for Successive – Approximation ADCs

Successive – Approximation ADCs are widely used in ultra – low – power applications. This paper describes a systematic design procedure for designing Successive – Approximation ADCs for biomedical sensor nodes. The proposed scheme is adopted in the design of a 12 bit 1 kS/s ADC. Implemented in 65 nm CMOS, the ADC consumes 354 nW at a sampling rate of 1 kS/s operating with 1.2 supply voltage. The achieved ENOB is 11.6, corresponding to a FoM of 114 fJ/conversion – step

A 1.67 pJ/Conversion-step 8-bit SAR-Flash ADC Architecture in 90-nm CMOS Technology

A novice advanced architecture of 8-bit analog todigital converter is introduced and analyzed in this work. Thestructure of proposed ADC is based on the sub-ranging ADCarchitecture in which a 4-bit resolution flash-ADC is utilized. Theproposed ADC architecture is designed by employing a comparatorwhich is equipped with common mode current feedback andgain boosting technique (CMFD-GB) and a residue amplifier. Theproposed 8 bits ADC structure can achieve the speed of 140 megasamplesper second. The proposed ADC architecture is designedat a resolution of 8 bits at 10 MHz sampling frequency. DNL andINL values of the proposed design are -0.94/1.22 and -1.19/1.19respectively. The ADC design dissipates a power of 1.24 mWwith the conversion speed of 0.98 ns. The magnitude of SFDRand SNR from the simulations at Nyquist input is 39.77 and 35.62decibel respectively. Simulations are performed on a SPICE basedtool in 90 nm CMOS technology. The comparison shows betterperformance for the proposed ADC design in comparison toother ADC architectures regarding speed, resolution and powerconsumption

Smart Sensor Networks For Sensor-Neural Interface

One in every fifty Americans suffers from paralysis, and approximately 23% of paralysis cases are caused by spinal cord injury. To help the spinal cord injured gain functionality of their paralyzed or lost body parts, a sensor-neural-actuator system is commonly used. The system includes: 1) sensor nodes, 2) a central control unit, 3) the neural-computer interface and 4) actuators. This thesis focuses on a sensor-neural interface and presents the research related to circuits for the sensor-neural interface. In Chapter 2, three sensor designs are discussed, including a compressive sampling image sensor, an optical force sensor and a passive scattering force sensor. Chapter 3 discusses the design of the analog front-end circuit for the wireless sensor network system. A low-noise low-power analog front-end circuit in 0.5μm CMOS technology, a 12-bit 1MS/s successive approximation register (SAR) analog-to-digital converter (ADC) in 0.18μm CMOS process and a 6-bit asynchronous level-crossing ADC realized in 0.18μm CMOS process are presented. Chapter 4 shows the design of a low-power impulse-radio ultra-wide-band (IR-UWB) transceiver (TRx) that operates at a data rate of up to 10Mbps, with a power consumption of 4.9pJ/bit transmitted for the transmitter and 1.12nJ/bit received for the receiver. In Chapter 5, a wireless fully event-driven electrogoniometer is presented. The electrogoniometer is implemented using a pair of ultra-wide band (UWB) wireless smart sensor nodes interfacing with low power 3-axis accelerometers. The two smart sensor nodes are configured into a master node and a slave node, respectively. An experimental scenario data analysis shows higher than 90% reduction of the total data throughput using the proposed fully event-driven electrogoniometer to measure joint angle movements when compared with a synchronous Nyquist-rate sampling system. The main contribution of this thesis includes: 1) the sensor designs that emphasize power efficiency and data throughput efficiency; 2) the fully event-driven wireless sensor network system design that minimizes data throughput and optimizes power consumption