A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 ??m complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.ope

Signal acquisition challenges in mobile systems

In recent decades, the advent of mobile computing has changed human lives by providing information that was not available in the past. The mobile computing platform opens a new door to the connected world in which various forms of hand-held and wearable systems are ubiquitous. A single mobile device plays multiple roles and shapes human lives towards a better future. In these systems, sensor-based data acquisition plays an essential role in generating and providing useful information. The increased number of sensors is embedded in a single device in order to process various signal modalities. In practice, more than 30 data converters are required in designing a mobile system in which the data-converting blocks become among the most power-hungry components in battery-operated systems. Due to the increased variety of sensors, mobile systems are meant to face several obstacles. For example, the increased number of sensors increase system power consumption during the system operation. The increased power consumption directly affects operation time because mobile systems are powered by a limited energy source. Moreover, an increased amount of information also gives rise to bandwidth problems in communication due to the increased volume of data transmission. Also, this system design requires a larger area in a silicon die so that multiple signal paths can be placed without cross-channel interference. Therefore, the system design has presented a challenge in terms of trying to resolve the design constraints such as power consumption, bandwidth usage, storage space, and design complexity issues. To overcome these obstacles, in this dissertation, efficient data acquisition and processing methods are investigated. Specifically, this thesis considers the problems of energy-efficient sampling and binary event detection. This dissertation begins by presenting a new signal sampling scheme that enables higher precision signal conversion in compressed-sensing-based signal acquisition. The proposed scheme is based on the popular successive approximation register and employs a modified compressive sensing technique to increase the resolution of successive-approximation-register (SAR) analog-to-digital converter (ADC) architecture. Circuit-level architecture is discussed to implement the proposed scheme using the SAR ADC architecture. A non-uniform quantization scheme is proposed and it improves data quality after data acquisition. The proposed scheme is expected to be used for medium- or high- frequency data conversion. Secondly, the possibility of using fewer ADCs than channels is studied by leveraging sparse-signal representation and blind-source-separation (BSS) techniques. In particular, this dissertation examines the problem of using a single ADC or quantizer system for digitizing multi-channel inputs. Mixing and de-mixing strategies are extensively studied for sampling frequency-sparse signals and the proposed multi-channel architecture can be easily implemented using today's analog/mixed-signal circuits. The third part of this dissertation investigates a binary hypothesis testing problem. In mobile devices such as smartphones and tablet PCs, a major portion of energy is consumed in user interfaces (LCD display and touch input processing). For accurate detection and better user interface, energy-efficient sensing and detection schemes are necessary to manage multiple sensor inputs. A highly efficient detection scheme is presented that can detect binary events reliably with a fraction of the energy consumption required in the conventional energy detection.Electrical and Computer Engineerin

CTSU vs CTSU2 comparative

The project consists of a comparative of two Capacitive Touch Sensing Units using a touch user interface. The first one (CTSU) is applied to an existing Renesas Xtreme Family (RX) microcontroller board. A new software has been implemented for the second one (CTSU2), which is applied to Renesas Advanced Family (RA) microcontroller board. Tests in its basic configuration, when configuring multi-frequency and configuring parallel scan have been run and compared for both boards. Based on those test results, two final touch control configurations are selected and ElectroMagnetic Compatibility tests have been executed. Gathering all the results, it can be seen that, when using parallel scan on a RA microcontroller, the measurement time decreases significantly and Signal to Noise Ratio (SNR) results are acceptable, although they are worse than on other configurations. Using multifrequency configuration EMC tests have passed successfully. In conclusion, the results obtained from CTSU2 exceed those from CTSU.El proyecto consiste en una comparativa de dos Capacitive Touch Sensing Units utilizando una interfaz de usuario táctil. La primera (CTSU) se aplica a una placa existente de microcontroladores Renesas Xtreme Family (RX). Se ha implementado un nuevo software para la segunda (CTSU2), que se aplica a una placa de microcontrolador Renesas Advanced Family (RA). Se han realizado tests en su configuración básica, configurando multifrecuencia y escaneo paralelo, y se han comparado para ambas placas. A partir de estos resultados, se han seleccionado dos configuraciones finales de control táctil y se han realizado pruebas de Compatibilidad ElectroMagnética. Recogiendo todos los resultados, puede observarse que, cuando se utiliza el escaneo paralelo en un microcontrolador RA, el tiempo de medida disminuye significativamente y los resultados de relación señal/ruido (SNR) son aceptables, aunque peores que en otras configuraciones. Utilizando la configuración de multifrecuencia, las pruebas de EMC se han superado correctamente. En conclusión, los resultados obtenidos de CTSU2 superan a los de CTSU.El projecte consisteix en una comparativa de dues Capacitive Touch Sensing Units utilitzant una interfície d'usuari tàctil. La primera (CTSU) s'aplica a una placa existent de microcontroladors Renesas Xtreme Family (RX). S'ha implementat un nou programari per a la segona (CTSU2), que s'aplica a una placa de microcontrolador Renesas Advanced Family (RA). S'han realitzat tests en la seva configuració bàsica, configurant multifreqüència i escaneig paral·lel, i s'han comparat per a ambdues plaques. A partir d'aquests resultats, s?han seleccionat dues configuracions finals de control tàctil i s'han realitzat proves de Compatibilitat ElectroMagnètica. Recollint tots els resultats, es pot observar que, quan s'utilitza l'escaneig paral·lel en un microcontrolador RA, el temps de mesura disminueix significativament i els resultats de relació senyal/soroll (SNR) són acceptables, tot i que pitjors que en altres configuracions. Utilitzant la configuració de multifreqüència, les proves d'EMC s?han superat correctament. En conclusió, els resultats obtinguts de CTSU2 superen els de CTSU

A Multi-functional Touch Panel for Multi-Dimensional Sensing in Interactive Displays

This thesis presents a flexible graphene/polyvinylidene difluoride (PVDF)/graphene sandwich for three-dimensional touch interactivity. Here, an x-y plane touch is sensed using graphene capacitive elements, while force sensing in the z-direction is by a piezoelectric PVDF/graphene sandwich. By employing different frequency bands for the capacitive- and force-induced electrical signals, the two stimuli are detected simultaneously, achieving three-dimensional touch sensing. Static force sensing and elimination of propagated stress are achieved by augmenting the transient piezo output with the capacitive touch, thus overcoming the intrinsic inability of the piezoelectric material in detecting non-transient force signals and avoiding force touch mis-registration by propagated stress. As a capacitive signal is important for force touch interpretation, optimization algorithms have been developed and implemented. With correlated double sampling (CDS) and spatial low-pass filtering (SLPF) based techniques, the signal-to-noise ratio (SNR) of the capacitive touch signal is boosted by 15.6 dB, indicating improved detection accuracy. In terms of the readout speed, fixed pattern and random pattern related down-sampling techniques are applied, giving rise to reductions in both readout time (11.3 ms) and power consumption (8.79 mW).China Scholarship Counci

Design of Analog Front-End of Touch-Screen Controller with Enhanced Noise Immunity and Configurable SNR and Frame Rate

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2017. 2. 정덕균.A design of analog front-end (AFE) for touch-screen controller (TSC) with highly enhanced noise immunity and configurable signal-to-noise ratio (SNR) and frame rate is proposed. First, the AFE for the mobile TSC is presented, which provides a configurable SNR and frame rate. The AFE configures its SNR and frame rate by adjusting the sampling cycles of the employed ADC. The test chip is fabricated in a 0.18-μm CMOS process and occupies a 2.2-mm2 active area. The test chip achieves 60-dB SNR and 200-Hz frame rate with 12 × 8 TSP. The SNR can be adjusted from 40 to 67 dB, while the frame rate is then inversely scaled from 50 Hz to 6.4 kHz. The test chip consumes 6.26 mW from a 3.3-V supply. The AFE for the tablet TSC is also presented, which provides highly enhanced noise immunity and configurable SNR and frame rate. The proposed AFE provides TX channels of 36 and RX channels of 64 in order to support a large-size TSP. A multi-driving TX structure with frequency-hopping signal generator is employed to improve the SNR and noise immunity. For a suppression of severe noise interference injected through the TSP, the RX sensing block adopts pre-filtering differential sensing method and high-order noise filtering structure. The AFE supports configurable SNR and frame rate with on-chip frame-rate controller. The test chip is fabri-cated in a 0.18-μm CMOS process. The active area of the test chip is 36 mm2. A 12.2-inch TSP with TX channels of 36 and RX channels of 64 is used in the measurement. The test chip achieves 54-dB SNR and 120-Hz frame rate with a finger touch. The frame rate can be adjusted from 85 to 385 Hz. The test chip achieves up to 20-Vpp noise immunity. The test chip consumes 94.5 mW with a 3.3-V supply.CHAPTER 1 INTRODUCTION 1 1.1 MOTIVATION 1 1.2 THESIS ORGANIZATION 3 CHAPTER 2 BASIC STUDY ON TOUCH-SCREEN CONTROLLER 5 2.1 TOUCH-SCREEN PANEL 5 2.2 TOUCH-SCREEN CONTROLLER 8 2.2.1 OVERVIEW ON TSC 8 2.3 ANALOG FRONT-END OF TSC 11 2.3.1 PERFORMANCE METRIC 12 2.3.2 DESIGN ISSUES OF AFE 15 CHAPTER 3 AFE OF MOBILE TSC WITH CONFIGURABLE SNR AND FRAME RATE 18 3.1 OVERVIEW 18 3.2 SYSTEM ARCHITECTURE 21 3.3 CONFIGURABLE SNR AND FRAME RATE 23 3.4 MEASUREMENT RESULTS 29 CHAPTER 4 AFE OF TABLET TSC WITH ENHANCED NOISE IMMUNITY 35 4.1 OVERVIEW 35 4.2 DESIGN ISSUES BY LARGE-SIZE TSP 38 4.3 DESIGN ISSUES BY NOISE INTERFERENCE 40 4.3.1 NOISE INTERFERENCE 40 4.3.2 DISPLAY NOISE REJECTION TECHNIQUE 43 4.3.3 CHARGER NOISE FILTERING TECHNIQUE 46 4.3.4 HIGH-VOLTAGE TX TECHNIQUE 50 4.3.5 MULTI-DRIVING TX TECHNIQUE 52 4.4 PROPOSED ARCHITECTURE 66 4.4.1 TX DRIVING ARCHITECTURE 67 4.4.2 RX SENSING ARCHITECTURE 71 4.5 MULTI-DRIVING TX STRUCTURE 75 4.5.1 CONSIDERATIONS FOR TX MODULATION SEQUENCE 75 4.5.2 COMPARISON OF MODULATION SEQUENCES 76 4.5.3 MODIFIED BUSH-TYPE HADAMARD MATRIX 79 4.6 NOISE FILTERING RX 83 4.6.1 PRE-FILTERING DIFFERENTIAL SENSING METHOD 83 4.6.2 NOISE-IMMUNE SENSING STRUCTURE 87 4.6.3 CONFIGURABLE SNR AND FRAME RATE 106 4.6.4 RX MODULATION 112 4.7 CIRCUIT IMPLEMENTATION 120 4.7.1 CHARGE AMPLIFIER AND BAND-PASS FILTER 121 4.7.2 CAPACITIVE DIFFERENTIAL AMPLIFIER 123 4.7.3 MIXER AND RX MODULATION 125 4.7.4 LOW-PASS FILTER 127 4.7.5 INCREMENTAL ΔΣ ADC 128 4.7.6 DIGITAL DEMODULATION 130 4.7.7 TX DRIVING BLOCK 131 4.8 MEASUREMENT RESULTS 132 4.8.1 TOUCH-SCREEN PANEL (TSP) 132 4.8.2 MEASUREMENT ENVIRONMENTS 133 4.8.3 FABRICATED AFE 134 4.8.4 OPERATION OF THE FABRICATED AFE 135 4.8.5 SNR MEASUREMENT 139 4.8.6 CONFIGURABLE SNR AND FRAME RATE 139 4.8.7 NOISE IMMUNITY 141 4.8.8 COMPARISON WITH OTHER WORKS 157 CHAPTER 5 CONCLUSION 158 BIBLIOGRAPHY 160 초 록 170Docto

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Department of Electrical EngineeringA Sensor system is advanced along sensor technologies are developed. The performance improvement of sensor system can be expected by using the internet of things (IoT) communication technology and artificial neural network (ANN) for data processing and computation. Sensors or systems exchanged the data through this wireless connectivity, and various systems and applications are possible to implement by utilizing the advanced technologies. And the collected data is computed using by the ANN and the efficiency of system can be also improved. Gas monitoring system is widely need from the daily life to hazardous workplace. Harmful gas can cause a respiratory disease and some gas include cancer-causing component. Even though it may cause dangerous situation due to explosion. There are various kinds of hazardous gas and its characteristics that effect on human body are different each gas. The optimal design of gas monitoring system is necessary due to each gas has different criteria such as the permissible concentration and exposure time. Therefore, in this thesis, conventional sensor system configuration, operation, and limitation are described and gas monitoring system with wireless connectivity and neural network is proposed to improve the overall efficiency. As I already mentioned above, dangerous concentration and permissible exposure time are different depending on gas types. During the gas monitoring, gas concentration is lower than a permissible level in most of case. Thus, the gas monitoring is enough with low resolution for saving the power consumption in this situation. When detecting the gas, the high-resolution is required for the accurate concentration detecting. If the gas type is varied in the above situation, the amount of calculation increases exponentially. Therefore, in the conventional systems, target specifications are decided by the highest requirement in the whole situation, and it occurs increasing the cost and complexity of readout integrated circuit (ROIC) and system. In order to optimize the specification, the ANN and adaptive ROIC are utilized to compute the complex situation and huge data processing. Thus, gas monitoring system with learning-based algorithm is proposed to improve its efficiency. In order to optimize the operation depending on situation, dual-mode ROIC that monitoring mode and precision mode is implemented. If the present gas concentration is decided to safe, monitoring mode is operated with minimal detecting accuracy for saving the power consumption. The precision mode is switched when the high-resolution or hazardous situation are detected. The additional calibration circuits are necessary for the high-resolution implementation, and it has more power consumption and design complexity. A high-resolution Analog-to-digital converter (ADC) is kind of challenges to design with efficiency way. Therefore, in order to reduce the effective resolution of ADC and power consumption, zooming correlated double sampling (CDS) circuit and prediction successive approximation register (SAR) ADC are proposed for performance optimization into precision mode. A Microelectromechanical systems (MEMS) based gas sensor has high-integration and high sensitivity, but the calibration is needed to improve its low selectivity. Conventionally, principle component analysis (PCA) is used to classify the gas types, but this method has lower accuracy in some case and hard to verify in real-time. Alternatively, ANN is powerful algorithm to accurate sensing through collecting the data and training procedure and it can be verified the gas type and concentration in real-time. ROIC was fabricated in complementary metal-oxide-semiconductor (CMOS) 180-nm process and then the efficiency of the system with adaptive ROIC and ANN algorithm was experimentally verified into gas monitoring system prototype. Also, Bluetooth supports wireless connectivity to PC and mobile and pattern recognition and prediction code for SAR ADC is performed in MATLAB. Real-time gas information is monitored by Android-based application in smartphone. The dual-mode operation, optimization of performance and prediction code are adjusted with microcontroller unit (MCU). Monitoring mode is improved by x2.6 of figure-of-merits (FoM) that compared with previous resistive interface.clos

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

3D printed neuromorphic sensing systems

Thanks to the high energy efficiency, neuromorphic devices are spotlighted recently by mimicking the calculation principle of the human brain through the parallel computation and the memory function. Various bio-inspired \u27in-memory computing\u27 (IMC) devices were developed during the past decades, such as synaptic transistors for artificial synapses. By integrating with specific sensors, neuromorphic sensing systems are achievable with the bio-inspired signal perception function. A signal perception process is possible by a combination of stimuli sensing, signal conversion/transmission, and signal processing. However, most neuromorphic sensing systems were demonstrated without signal conversion/transmission functions. Therefore, those cannot fully mimic the function provides by the sensory neuron in the biological system. This thesis aims to design a neuromorphic sensing system with a complete function as biological sensory neurons. To reach such a target, 3D printed sensors, electrical oscillators, and synaptic transistors were developed as functions of artificial receptors, artificial neurons, and artificial synapses, respectively. Moreover, since the 3D printing technology has demonstrated a facile process due to fast prototyping, the proposed 3D neuromorphic sensing system was designed as a 3D integrated structure and fabricated by 3D printing technologies. A novel multi-axis robot 3D printing system was also utilized to increase the fabrication efficiency with the capability of printing on vertical and tilted surfaces seamlessly. Furthermore, the developed 3D neuromorphic system was easily adapted to the application of tactile sensing. A portable neuromorphic system was integrated with a tactile sensing system for the intelligent tactile sensing application of the humanoid robot. Finally, the bio-inspired reflex arc for the unconscious response was also demonstrated by training the neuromorphic tactile sensing system

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

コスト効率のよい農業用土壌モニタリングネットワークのシステム設計

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 瀬崎 薫, 東京大学准教授 川原 圭博, 国立情報学研究所教授 安達 淳, 東京大学准教授 落合 秀也, 東京大学教授 溝口 勝University of Tokyo(東京大学