39 research outputs found

    Recent Advances on Implantable Wireless Sensor Networks

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    Implantable electronic devices are undergoing a miniaturization age, becoming more efficient and yet more powerful as well. Biomedical sensors are used to monitor a multitude of physiological parameters, such as glucose levels, blood pressure and neural activity. A group of sensors working together in the human body is the main component of a body area network, which is a wireless sensor network applied to the human body. In this chapter, applications of wireless biomedical sensors are presented, along with state-of-the-art communication and powering mechanisms of these devices. Furthermore, recent integration methods that allow the sensors to become smaller and more suitable for implantation are summarized. For individual sensors to become a body area network (BAN), they must form a network and work together. Issues that must be addressed when developing these networks are detailed and, finally, mobility methods for implanted sensors are presented

    Inductively Coupled Split Ring Resonator as Small RFID Pressure Sensor for Biomedical Applications

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    We present an inductively coupled split-ring resonator based small passive RFID pressure sensor for wireless intracranial pressure measurement. The proposed sensor has a volume as small as ฯ€ร—(4 mm) 2 ร—1 mm. In the simulation, the proposed sensor can provide nearly 1 m operation distance when implanted in the intracranial environment. In our preliminary measurement in the air, the sensor has a resolution of 3 cmH2O.acceptedVersionPeer reviewe

    An Energy-Efficient Bridge-to-Digital Converter for Implantable Pressure Monitoring Systems

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    This paper presents an energy-efficient, duty-cycled, and spinning excitation bridge-to-digital converter (BDC) designed for implantable pressure sensing systems. The circuit provides the measure of the pulmonary artery pressure that is particularly relevant for the monitoring of heart failure and pulmonary hypertension patients. The BDC is made of a piezoresistive pressure sensor and a readout integrated circuit (IC) that comprises an instrumentation amplifier (IA) followed by an analog-to-digital converter (ADC). The proposed design spins both the bridge excitation and the ADCโ€™s sampling input voltages simultaneously and exploits duty cycling to reduce the static power consumption of the bridge sensor and IA while cancelling the IAโ€™s offset and 1/f noise at the same time. The readout IC has been designed and fabricated in a standard 180-nm CMOS process and achieves 8.4 effective number of bits (ENOB) at 1 kHz sampling rate while drawing 0.53 ยตA current from a 1.2 V supply. The BDC, built with the readout IC and a differential pressure sensor having 5 kฮฉ bridge resistances, achieves 0.44 mmHg resolution in a 270 mmHg pressure range at 1 ms conversion time. The current consumption of the bridge sensor by employing duty cycling is reduced by 99.8% thus becoming 0.39 ยตA from a 1.2 V supply. The total conversion energy of the pressure sensing system is 1.1 nJ, and achieves a figure-of-merit (FoM) of 3.3 pJ/conversion, which both represent the state of the art

    An Ultra-Low-Power RFID/NFC Frontend IC Using 0.18 ฮผm CMOS Technology for Passive Tag Applications

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    Battery-less passive sensor tags based on RFID or NFC technology have achieved much popularity in recent times. Passive tags are widely used for various applications like inventory control or in biotelemetry. In this paper, we present a new RFID/NFC frontend IC (integrated circuit) for 13.56 MHz passive tag applications. The design of the frontend IC is compatible with the standard ISO 15693/NFC 5. The paper discusses the analog design part in details with a brief overview of the digital interface and some of the critical measured parameters. A novel approach is adopted for the demodulator design, to demodulate the 10% ASK (amplitude shift keying) signal. The demodulator circuit consists of a comparator designed with a preset offset voltage. The comparator circuit design is discussed in detail. The power consumption of the bandgap reference circuit is used as the load for the envelope detection of the ASK modulated signal. The sub-threshold operation and low-supply-voltage are used extensively in the analog design—to keep the power consumption low. The IC was fabricated using 0.18 μ m CMOS technology in a die area of 1.5 mm × 1.5 mm and an effective area of 0.7 m m 2 . The minimum supply voltage desired is 1.2 V, for which the total power consumption is 107 μ W. The analog part of the design consumes only 36 μ W, which is low in comparison to other contemporary passive tags ICs. Eventually, a passive tag is developed using the frontend IC, a microcontroller, a temperature and a pressure sensor. A smart NFC device is used to readout the sensor data from the tag employing an Android-based application software. The measurement results demonstrate the full passive operational capability. The IC is suitable for low-power and low-cost industrial or biomedical battery-less sensor applications. A figure-of-merit (FOM) is proposed in this paper which is taken as a reference for comparison with other related state-of-the-art researches

    12.8 kHz Energy-Efficient Read-Out IC for High Precision Bridge Sensor Sensing System

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2022.2. ๊น€์ˆ˜ํ™˜.In the thesis, a high energy-efficient read-out integrated circuit (read-out IC) for a high-precision bridge sensor sensing system is proposed. A low-noise capacitively-coupled chopper instrumentation amplifier (CCIA) followed by a high-resolution incremental discrete-time delta-sigma modulator (DTฮ”ฮฃฮœ) analog-to-digital converter (ADC) is implemented. To increase energy-efficiency, CCIA is chosen, which has the highest energy-efficiency among IA types. CCIA has a programmable gain of 1 to 128 that can amplify the small output of the bridge sensor. Impedance boosting loop (IBL) is applied to compensate for the low input impedance, which is a disadvantage of a CCIA. Also, the sensor offset cancellation technique was applied to CCIA to eliminate the offset resulting from the resistance mismatch of the bridge sensor, and the bridge sensor offset from -350 mV to 350 mV can be eliminated. In addition, the output data rate of the read-out IC is designed to be 12.8 kHz to quickly capture data and to reduce the power consumption of the sensor by turning off the sensor and read-out IC for the rest of the time. Generally, bridge sensor system is much slower than 12.8 kHz. To suppress 1/f noise, system level chopping and correlated double sampling (CDS) techniques are used. Implemented in a standard 0.13-ฮผm CMOS process, the ROICโ€™s effective resolution is 17.0 bits at gain 1 and that of 14.6 bits at gain 128. The analog part draws the average current of 139.4 ฮผA from 3-V supply, and 60.2 ฮผA from a 1.8 V supply.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ณ ์ •๋ฐ€ ๋ธŒ๋ฆฌ์ง€ ์„ผ์„œ ์„ผ์‹ฑ ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์—๋„ˆ์ง€ ํšจ์œจ์ด ๋†’์€ Read-out Integrated Circuit (read-out IC)๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ € ์žก์Œ Capacitively-Coupled Instrumentation Amplifier (CCIA)์— ์ด์€ ๊ณ ํ•ด์ƒ๋„ Discrete-time Delta-Sigma ๋ณ€์กฐ๊ธฐ(DTฮ”ฮฃฮœ) ์•„๋‚ ๋กœ๊ทธ-๋””์ง€ํ„ธ ๋ณ€ํ™˜๊ธฐ(ADC)๋ฅผ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ์—๋„ˆ์ง€ ํšจ์œจ์„ ๋†’์ด๊ธฐ ์œ„ํ•ด IA ์œ ํ˜• ์ค‘ ์—๋„ˆ์ง€ ํšจ์œจ์ด ๊ฐ€์žฅ ๋†’์€ CCIA๋ฅผ ์„ ํƒํ•˜์˜€๋‹ค. CCIA๋Š” ๋ธŒ๋ฆฌ์ง€ ์„ผ์„œ์˜ ์ž‘์€ ์ถœ๋ ฅ์„ ์ฆํญํ•  ์ˆ˜ ์žˆ๋Š” 1 ์—์„œ 128์˜ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๊ฐ€๋Šฅํ•œ ์ „์•• ์ด๋“์„ ๊ฐ€์ง„๋‹ค. CCIA์˜ ๋‹จ์ ์ธ ๋‚ฎ์€ ์ž…๋ ฅ ์ž„ํ”ผ๋˜์Šค๋ฅผ ๋ณด์ƒํ•˜๊ธฐ ์œ„ํ•ด Impedance Boosting Loop (IBL)์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋˜ํ•œ CCIA์— ์„ผ์„œ ์˜คํ”„์…‹ ์ œ๊ฑฐ ๊ธฐ์ˆ ์„ ์ ์šฉํ•˜์—ฌ ๋ธŒ๋ฆฌ์ง€ ์„ผ์„œ์˜ ์ €ํ•ญ ๋ฏธ์Šค๋งค์น˜๋กœ ์ธํ•œ ์˜คํ”„์…‹์„ ์ œ๊ฑฐ ๊ธฐ๋Šฅ์„ ํƒ‘์žฌํ•˜์˜€์œผ๋ฉฐ -350mV์—์„œ 350mV๊นŒ์ง€ ๋ธŒ๋ฆฌ์ง€ ์„ผ์„œ ์˜คํ”„์…‹์„ ์ œ๊ฑฐํ•  ์ˆ˜ ์žˆ๋‹ค. Read-out IC์˜ ์ถœ๋ ฅ ๋ฐ์ดํ„ฐ ์ „์†ก๋ฅ ์€ 12.8kHz๋กœ ์„ค๊ณ„ํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ๋น ๋ฅด๊ฒŒ ์ฑ„๊ณ  ๋‚˜๋จธ์ง€ ์‹œ๊ฐ„ ๋™์•ˆ ์„ผ์„œ์™€ read-out IC๋ฅผ ๊บผ์„œ ์„ผ์„œ์˜ ์ „๋ ฅ ์†Œ๋น„๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋„๋ก ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ๋ธŒ๋ฆฌ์ง€ ์„ผ์„œ ์‹œ์Šคํ…œ์€ 12.8kHz๋ณด๋‹ค ๋Š๋ฆฌ๊ธฐ ๋•Œ๋ฌธ์— ์ด๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ํ•˜์ง€๋งŒ, ์ผ๋ฐ˜์ ์ธ CCIA๋Š” ์ž…๋ ฅ ์ž„ํ”ผ๋˜์Šค ๋•Œ๋ฌธ์— ๋น ๋ฅธ ์†๋„์—์„œ ์„ค๊ณ„๊ฐ€ ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด demodulate ์ฐจํ•‘์„ ์•ฐํ”„ ๋‚ด๋ถ€๊ฐ€ ์•„๋‹Œ ์‹œ์Šคํ…œ ์ฐจํ•‘์„ ์ด์šฉํ•ด ํ•ด๊ฒฐํ•˜์˜€๋‹ค. 1/f ๋…ธ์ด์ฆˆ๋ฅผ ์–ต์ œํ•˜๊ธฐ ์œ„ํ•ด ์‹œ์Šคํ…œ ๋ ˆ๋ฒจ ์ฐจํ•‘ ๋ฐ ์ƒ๊ด€ ์ด์ค‘ ์ƒ˜ํ”Œ๋ง(CDS) ๊ธฐ์ˆ ์ด ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. 0.13ฮผm CMOS ๊ณต์ •์—์„œ ๊ตฌํ˜„๋œ read-out IC์˜ Effective Resolution (ER)์€ ์ „์•• ์ด๋“ 1์—์„œ 17.0๋น„ํŠธ์ด๊ณ  ์ „์•• ์ด๋“ 128์—์„œ 14.6๋น„ํŠธ๋ฅผ ๋‹ฌ์„ฑํ•˜์˜€๋‹ค. ์•„๋‚ ๋กœ๊ทธ ํšŒ๋กœ๋Š” 3 V ์ „์›์—์„œ 139.4ฮผA์˜ ํ‰๊ท  ์ „๋ฅ˜๋ฅผ, ๋””์ง€ํ„ธ ํšŒ๋กœ๋Š” 1.8 V ์ „์›์—์„œ 60.2ฮผA์˜ ํ‰๊ท  ์ „๋ฅ˜๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค.CHAPTER 1 INTRODUCTION 1 1.1 SMART DEVICES 1 1.2 SMART SENSOR SYSTEMS 4 1.3 WHEATSTONE BRIDGE SENSOR 5 1.4 MOTIVATION 8 1.5 PREVIOUS WORKS 10 1.6 INTRODUCTION OF THE PROPOSED SYSTEM 14 1.7 THESIS ORGANIZATION 16 CHAPTER 2 SYSTEM OVERVIEW 17 2.1 SYSTEM ARCHITECTURE 17 CHAPTER 3 IMPLEMENTATION OF THE CCIA 19 3.1 CAPACITIVELY-COUPLED CHOPPER INSTRUMENTATION AMPLIFIER 19 3.2 IMPEDANCE BOOSTING 22 3.3 SENSOR OFFSET CANCELLATION 25 3.4 AMPLIFIER OFFSET CANCELLATION 29 3.5 AMPLIFIER IMPLEMENTATION 32 3.6 IMPLEMENTATION OF THE CCIA 35 CHAPTER 4 INCREMENTAL ฮ”ฮฃ ADC 37 4.1 INTRODUCTION OF INCREMENTAL ฮ”ฮฃ ADC 37 4.2 IMPLEMENTATION OF INCREMENTAL ฮ”ฮฃ MODULATOR 40 CHAPTER 5 SYSTEM-LEVEL DESIGN 43 5.1 DIGITAL FILTER 43 5.2 SYSTEM-LEVEL CHOPPING & TIMING 46 CHAPTER 5 MEASUREMENT RESULTS 48 6.1 MEASUREMENT SUMMARY 48 6.2 LINEARITY & NOISE MEASUREMENT 51 6.3 SENSOR OFFSET CANCELLATION MEASUREMENT 57 6.4 INPUT IMPEDANCE MEASUREMENT 59 6.5 TEMPERATURE VARIATION MEASUREMENT 63 6.6 PERFORMANCE SUMMARY 66 CHAPTER 7 CONCLUSION 68 APPENDIX A. 69 ENERGY-EFFICIENT READ-OUT IC FOR HIGH-PRECISION DC MEASUREMENT SYSTEM WITH IA POWER REDUCTION TECHNIQUE 69 BIBLIOGRAPHY 83 ํ•œ๊ธ€์ดˆ๋ก 87๋ฐ•

    Integrated Electronics for Wireless Imaging Microsystems with CMUT Arrays

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    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

    Advances in Ophthalmology

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    This book focuses on the different aspects of ophthalmology - the medical science of diagnosis and treatment of eye disorders. Ophthalmology is divided into various clinical subspecialties, such as cornea, cataract, glaucoma, uveitis, retina, neuro-ophthalmology, pediatric ophthalmology, oncology, pathology, and oculoplastics. This book incorporates new developments as well as future perspectives in ophthalmology and is a balanced product between covering a wide range of diseases and expedited publication. It is intended to be the appetizer for other books to follow. Ophthalmologists, researchers, specialists, trainees, and general practitioners with an interest in ophthalmology will find this book interesting and useful
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