Design of Touch Screen Controller IC for Transparent Fingerprint Sensor

Department of Electrical EngineeringA design of system architecture and analog-front-end (AFE) with high SNR and high frame rate for mutual capacitive touch screen with multiple electrodes is presented. Firstly, a differential continuous-mode parallel operation architecture (DCPA) is proposed for large-sized TSP. The proposed architecture achieves a high product of signal-to-noise ratio (SNR) and frame rate, which is a requirement of ROIC for large-sized TSP. DCPA is accomplished by using the proposed differential sensing method with a parallel architecture in a continuous-mode. A continuous-type differential charge amplifier removes the common-mode noise component, and reduces the self-noise by the band-pass filtering effect of the continuous-mode charge amplifier. In addition, the differential parallel architecture cancels the timing skew problem caused by the continuous-mode parallel operation and effectively enhances the power spectrum density of the signal. The proposed ROIC was fabricated using a 0.18-um CMOS process and occupied an active area of 1.25 mm2. The proposed system achieved a 72 dB SNR and 240 Hz frame rate with a 32 channel TX by 10 channel RX mutual capacitive TSP. Moreover, the proposed differential-parallel architecture demonstrated higher immunity to lamp noise and display noise. The proposed system consumed 42.5 mW with a 3.3-V supply. Secondly, readout IC (ROIC) with a differential coded multiple signaling method (DCMS) is proposed to detect an atto-farad capacitance difference for fingerprint recognition in fingerprint TSP. A readout IC with high SNR and fast frame rate are required in the fingerprint recognition. However, the capacitance difference by the ridge and valley of the fingerprint is very small, so that the signal-to-noise ratio is very low. In addition, it takes long time to scan whole fingerprint TSP with multiple electrodes. A fully differential architecture with differential signaling is proposed to detect the low capacitance difference in fingerprint TSP. The internal noise generated is minimized by 2nd fully differential operational amplifier and external noise is eliminated by a lock-in sensing structure. In addition, DCMS reduces an AC offset and enhances a higher product of SNR and frame rate in multiple channels. The proposed architectures can distinguish a 50-atto-farad which is a capacitance difference resulted from the ridges and valley of the finger under the 0.3T glass. The total scan time for 42 ?? 42 fingerprint TSP is less than 21 ms and the power consumption is below 20 mW at 3.3 V supply voltage. IC has been fabricated using a 0.18 ??m standard CMOS process.ope

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

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

Capacitive Touch Panel with Low Sensitivity to Water Drop employing Mutual-coupling Electrical Field Shaping Technique

This paper proposes a novel method to reduce the water interference on the touch panel based on mutual-capacitance sensing in human finger detection. As the height of a finger (height >10 mm) is far larger than that of a water-drop (height 10 mm) and low in the low-height space (height <1 mm), the sensing cell can be designed to distinguish the finger from the water-drop. To achieve this density distribution of the electrical field, the mutual-coupling electrical field shaping (MEFS) technique is employed to build the sensing cell. The drawback of the MEFS sensing cell is large parasitic capacitance, which can be overcome by a readout IC with low sensitivity to parasitic capacitance. Experiments show that the output of the IC with the MEFS sensing cell is 1.11 V when the sensing cell is touched by the water-drop and 1.23 V when the sensing cell is touched by the finger, respectively. In contrast, the output of the IC with the traditional sensing cell is 1.32 and 1.33 V when the sensing cell is touched by the water-drop and the finger, respectively. This demonstrates that the MEFS sensing cell can better distinguish the finger from the water-drop than the traditional sensing cell does.National Research Foundation (NRF)Accepted versionThis work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant 61771363, in part by the China Scholarship Council (CSC) under Grant 201706960042, and in part by the National Research Foundation of Singapore under Grant NRF-CRP11-2012-01

New generation of interactive platforms based on novel printed smart materials

Programa doutoral em Engenharia Eletrónica e de Computadores (área de Instrumentação e Microssistemas Eletrónicos)The last decade was marked by the computer-paradigm changing with other digital devices suddenly becoming available to the general public, such as tablets and smartphones. A shift in perspective from computer to materials as the centerpiece of digital interaction is leading to a diversification of interaction contexts, objects and applications, recurring to intuitive commands and dynamic content that can proportionate more interesting and satisfying experiences. In parallel, polymer-based sensors and actuators, and their integration in different substrates or devices is an area of increasing scientific and technological interest, which current state of the art starts to permit the use of smart sensors and actuators embodied within the objects seamlessly. Electronics is no longer a rigid board with plenty of chips. New technological advances and perspectives now turned into printed electronics in polymers, textiles or paper. We are assisting to the actual scaling down of computational power into everyday use objects, a fusion of the computer with the material. Interactivity is being transposed to objects erstwhile inanimate. In this work, strain and deformation sensors and actuators were developed recurring to functional polymer composites with metallic and carbonaceous nanoparticles (NPs) inks, leading to capacitive, piezoresistive and piezoelectric effects, envisioning the creation of tangible user interfaces (TUIs). Based on smart polymer substrates such as polyvinylidene fluoride (PVDF) or polyethylene terephthalate (PET), among others, prototypes were prepared using piezoelectric and dielectric technologies. Piezoresistive prototypes were prepared with resistive inks and restive functional polymers. Materials were printed by screen printing, inkjet printing and doctor blade coating. Finally, a case study of the integration of the different materials and technologies developed is presented in a book-form factor.A última década foi marcada por uma alteração do paradigma de computador pelo súbito aparecimento dos tablets e smartphones para o público geral. A alteração de perspetiva do computador para os materiais como parte central de interação digital levou a uma diversificação dos contextos de interação, objetos e aplicações, recorrendo a comandos intuitivos e conteúdos dinâmicos capazes de tornarem a experiência mais interessante e satisfatória. Em simultâneo, sensores e atuadores de base polimérica, e a sua integração em diferentes substratos ou dispositivos é uma área de crescente interesse científico e tecnológico, e o atual estado da arte começa a permitir o uso de sensores e atuadores inteligentes perfeitamente integrados nos objetos. Eletrónica já não é sinónimo de placas rígidas cheias de componentes. Novas perspetivas e avanços tecnológicos transformaram-se em eletrónica impressa em polímeros, têxteis ou papel. Neste momento estamos a assistir à redução da computação a objetos do dia a dia, uma fusão do computador com a matéria. A interatividade está a ser transposta para objetos outrora inanimados. Neste trabalho foram desenvolvidos atuadores e sensores e de pressão e de deformação com recurso a compostos poliméricos funcionais com tintas com nanopartículas (NPs) metálicas ou de base carbónica, recorrendo aos efeitos capacitivo, piezoresistivo e piezoelétrico, com vista à criação de interfaces de usuário tangíveis (TUIs). Usando substratos poliméricos inteligentes tais como fluoreto de polivinilideno (PVDF) ou politereftalato de etileno (PET), entre outos, foi possível a preparação de protótipos de tecnologia piezoelétrica ou dielétrica. Os protótipos de tecnologia piezoresistiva foram feitos com tintas resistivas e polímeros funcionais resistivos. Os materiais foram impressos por serigrafia, jato de tinta, impressão por aerossol e revestimento de lâmina doctor blade. Para terminar, é apresentado um caso de estudo da integração dos diferentes materiais e tecnologias desenvolvidos sob o formato de um livro.This project was supported by FCT – Fundação para a Ciência e a Tecnologia, within the doctorate grant with reference SFRH/BD/110622/2015, by POCH – Programa Operacional Capital Humano, and by EU – European Union

Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Grasp-sensitive surfaces

Grasping objects with our hands allows us to skillfully move and manipulate them. Hand-held tools further extend our capabilities by adapting precision, power, and shape of our hands to the task at hand. Some of these tools, such as mobile phones or computer mice, already incorporate information processing capabilities. Many other tools may be augmented with small, energy-efficient digital sensors and processors. This allows for graspable objects to learn about the user grasping them - and supporting the user's goals. For example, the way we grasp a mobile phone might indicate whether we want to take a photo or call a friend with it - and thus serve as a shortcut to that action. A power drill might sense whether the user is grasping it firmly enough and refuse to turn on if this is not the case. And a computer mouse could distinguish between intentional and unintentional movement and ignore the latter. This dissertation gives an overview of grasp sensing for human-computer interaction, focusing on technologies for building grasp-sensitive surfaces and challenges in designing grasp-sensitive user interfaces. It comprises three major contributions: a comprehensive review of existing research on human grasping and grasp sensing, a detailed description of three novel prototyping tools for grasp-sensitive surfaces, and a framework for analyzing and designing grasp interaction: For nearly a century, scientists have analyzed human grasping. My literature review gives an overview of definitions, classifications, and models of human grasping. A small number of studies have investigated grasping in everyday situations. They found a much greater diversity of grasps than described by existing taxonomies. This diversity makes it difficult to directly associate certain grasps with users' goals. In order to structure related work and own research, I formalize a generic workflow for grasp sensing. It comprises *capturing* of sensor values, *identifying* the associated grasp, and *interpreting* the meaning of the grasp. A comprehensive overview of related work shows that implementation of grasp-sensitive surfaces is still hard, researchers often are not aware of related work from other disciplines, and intuitive grasp interaction has not yet received much attention. In order to address the first issue, I developed three novel sensor technologies designed for grasp-sensitive surfaces. These mitigate one or more limitations of traditional sensing techniques: **HandSense** uses four strategically positioned capacitive sensors for detecting and classifying grasp patterns on mobile phones. The use of custom-built high-resolution sensors allows detecting proximity and avoids the need to cover the whole device surface with sensors. User tests showed a recognition rate of 81%, comparable to that of a system with 72 binary sensors. **FlyEye** uses optical fiber bundles connected to a camera for detecting touch and proximity on arbitrarily shaped surfaces. It allows rapid prototyping of touch- and grasp-sensitive objects and requires only very limited electronics knowledge. For FlyEye I developed a *relative calibration* algorithm that allows determining the locations of groups of sensors whose arrangement is not known. **TDRtouch** extends Time Domain Reflectometry (TDR), a technique traditionally used for inspecting cable faults, for touch and grasp sensing. TDRtouch is able to locate touches along a wire, allowing designers to rapidly prototype and implement modular, extremely thin, and flexible grasp-sensitive surfaces. I summarize how these technologies cater to different requirements and significantly expand the design space for grasp-sensitive objects. Furthermore, I discuss challenges for making sense of raw grasp information and categorize interactions. Traditional application scenarios for grasp sensing use only the grasp sensor's data, and only for mode-switching. I argue that data from grasp sensors is part of the general usage context and should be only used in combination with other context information. For analyzing and discussing the possible meanings of grasp types, I created the GRASP model. It describes five categories of influencing factors that determine how we grasp an object: *Goal* -- what we want to do with the object, *Relationship* -- what we know and feel about the object we want to grasp, *Anatomy* -- hand shape and learned movement patterns, *Setting* -- surrounding and environmental conditions, and *Properties* -- texture, shape, weight, and other intrinsics of the object I conclude the dissertation with a discussion of upcoming challenges in grasp sensing and grasp interaction, and provide suggestions for implementing robust and usable grasp interaction.Die Fähigkeit, Gegenstände mit unseren Händen zu greifen, erlaubt uns, diese vielfältig zu manipulieren. Werkzeuge erweitern unsere Fähigkeiten noch, indem sie Genauigkeit, Kraft und Form unserer Hände an die Aufgabe anpassen. Digitale Werkzeuge, beispielsweise Mobiltelefone oder Computermäuse, erlauben uns auch, die Fähigkeiten unseres Gehirns und unserer Sinnesorgane zu erweitern. Diese Geräte verfügen bereits über Sensoren und Recheneinheiten. Aber auch viele andere Werkzeuge und Objekte lassen sich mit winzigen, effizienten Sensoren und Recheneinheiten erweitern. Dies erlaubt greifbaren Objekten, mehr über den Benutzer zu erfahren, der sie greift - und ermöglicht es, ihn bei der Erreichung seines Ziels zu unterstützen. Zum Beispiel könnte die Art und Weise, in der wir ein Mobiltelefon halten, verraten, ob wir ein Foto aufnehmen oder einen Freund anrufen wollen - und damit als Shortcut für diese Aktionen dienen. Eine Bohrmaschine könnte erkennen, ob der Benutzer sie auch wirklich sicher hält und den Dienst verweigern, falls dem nicht so ist. Und eine Computermaus könnte zwischen absichtlichen und unabsichtlichen Mausbewegungen unterscheiden und letztere ignorieren. Diese Dissertation gibt einen Überblick über Grifferkennung (*grasp sensing*) für die Mensch-Maschine-Interaktion, mit einem Fokus auf Technologien zur Implementierung griffempfindlicher Oberflächen und auf Herausforderungen beim Design griffempfindlicher Benutzerschnittstellen. Sie umfasst drei primäre Beiträge zum wissenschaftlichen Forschungsstand: einen umfassenden Überblick über die bisherige Forschung zu menschlichem Greifen und Grifferkennung, eine detaillierte Beschreibung dreier neuer Prototyping-Werkzeuge für griffempfindliche Oberflächen und ein Framework für Analyse und Design von griff-basierter Interaktion (*grasp interaction*). Seit nahezu einem Jahrhundert erforschen Wissenschaftler menschliches Greifen. Mein Überblick über den Forschungsstand beschreibt Definitionen, Klassifikationen und Modelle menschlichen Greifens. In einigen wenigen Studien wurde bisher Greifen in alltäglichen Situationen untersucht. Diese fanden eine deutlich größere Diversität in den Griffmuster als in existierenden Taxonomien beschreibbar. Diese Diversität erschwert es, bestimmten Griffmustern eine Absicht des Benutzers zuzuordnen. Um verwandte Arbeiten und eigene Forschungsergebnisse zu strukturieren, formalisiere ich einen allgemeinen Ablauf der Grifferkennung. Dieser besteht aus dem *Erfassen* von Sensorwerten, der *Identifizierung* der damit verknüpften Griffe und der *Interpretation* der Bedeutung des Griffes. In einem umfassenden Überblick über verwandte Arbeiten zeige ich, dass die Implementierung von griffempfindlichen Oberflächen immer noch ein herausforderndes Problem ist, dass Forscher regelmäßig keine Ahnung von verwandten Arbeiten in benachbarten Forschungsfeldern haben, und dass intuitive Griffinteraktion bislang wenig Aufmerksamkeit erhalten hat. Um das erstgenannte Problem zu lösen, habe ich drei neuartige Sensortechniken für griffempfindliche Oberflächen entwickelt. Diese mindern jeweils eine oder mehrere Schwächen traditioneller Sensortechniken: **HandSense** verwendet vier strategisch positionierte kapazitive Sensoren um Griffmuster zu erkennen. Durch die Verwendung von selbst entwickelten, hochauflösenden Sensoren ist es möglich, schon die Annäherung an das Objekt zu erkennen. Außerdem muss nicht die komplette Oberfläche des Objekts mit Sensoren bedeckt werden. Benutzertests ergaben eine Erkennungsrate, die vergleichbar mit einem System mit 72 binären Sensoren ist. **FlyEye** verwendet Lichtwellenleiterbündel, die an eine Kamera angeschlossen werden, um Annäherung und Berührung auf beliebig geformten Oberflächen zu erkennen. Es ermöglicht auch Designern mit begrenzter Elektronikerfahrung das Rapid Prototyping von berührungs- und griffempfindlichen Objekten. Für FlyEye entwickelte ich einen *relative-calibration*-Algorithmus, der verwendet werden kann um Gruppen von Sensoren, deren Anordnung unbekannt ist, semi-automatisch anzuordnen. **TDRtouch** erweitert Time Domain Reflectometry (TDR), eine Technik die üblicherweise zur Analyse von Kabelbeschädigungen eingesetzt wird. TDRtouch erlaubt es, Berührungen entlang eines Drahtes zu lokalisieren. Dies ermöglicht es, schnell modulare, extrem dünne und flexible griffempfindliche Oberflächen zu entwickeln. Ich beschreibe, wie diese Techniken verschiedene Anforderungen erfüllen und den *design space* für griffempfindliche Objekte deutlich erweitern. Desweiteren bespreche ich die Herausforderungen beim Verstehen von Griffinformationen und stelle eine Einteilung von Interaktionsmöglichkeiten vor. Bisherige Anwendungsbeispiele für die Grifferkennung nutzen nur Daten der Griffsensoren und beschränken sich auf Moduswechsel. Ich argumentiere, dass diese Sensordaten Teil des allgemeinen Benutzungskontexts sind und nur in Kombination mit anderer Kontextinformation verwendet werden sollten. Um die möglichen Bedeutungen von Griffarten analysieren und diskutieren zu können, entwickelte ich das GRASP-Modell. Dieses beschreibt fünf Kategorien von Einflussfaktoren, die bestimmen wie wir ein Objekt greifen: *Goal* -- das Ziel, das wir mit dem Griff erreichen wollen, *Relationship* -- das Verhältnis zum Objekt, *Anatomy* -- Handform und Bewegungsmuster, *Setting* -- Umgebungsfaktoren und *Properties* -- Eigenschaften des Objekts, wie Oberflächenbeschaffenheit, Form oder Gewicht. Ich schließe mit einer Besprechung neuer Herausforderungen bei der Grifferkennung und Griffinteraktion und mache Vorschläge zur Entwicklung von zuverlässiger und benutzbarer Griffinteraktion

Tactile and Touchless Sensors Printed on Flexible Textile Substrates for Gesture Recognition

Tesis por compendio[EN] The main objective of this thesis is the development of new sensors and actuators using Printed Electronics technology. For this, conductive, semiconductor and dielectric polymeric materials are used on flexible and/or elastic substrates. By means of suitable designs and application processes, it is possible to manufacture sensors capable of interacting with the environment. In this way, specific sensing functionalities can be incorporated into the substrates, such as textile fabrics. Additionally, it is necessary to include electronic systems capable of processing the data obtained, as well as its registration. In the development of these sensors and actuators, the physical properties of the different materials are precisely combined. For this, multilayer structures are designed where the properties of some materials interact with those of others. The result is a sensor capable of capturing physical variations of the environment, and convert them into signals that can be processed, and finally transformed into data. On the one hand, a tactile sensor printed on textile substrate for 2D gesture recognition was developed. This sensor consists of a matrix composed of small capacitive sensors based on a capacitor type structure. These sensors were designed in such a way that, if a finger or other object with capacitive properties, gets close enough, its behaviour varies, and it can be measured. The small sensors are arranged in this matrix as in a grid. Each sensor has a position that is determined by a row and a column. The capacity of each small sensor is periodically measured in order to assess whether significant variations have been produced. For this, it is necessary to convert the sensor capacity into a value that is subsequently digitally processed. On the other hand, to improve the effectiveness in the use of the developed 2D touch sensors, the way of incorporating an actuator system was studied. Thereby, the user receives feedback that the order or action was recognized. To achieve this, the capacitive sensor grid was complemented with an electroluminescent screen printed as well. The final prototype offers a solution that combines a 2D tactile sensor with an electroluminescent actuator on a printed textile substrate. Next, the development of a 3D gesture sensor was carried out using a combination of sensors also printed on textile substrate. In this type of 3D sensor, a signal is sent generating an electric field on the sensors. This is done using a transmission electrode located very close to them. The generated field is received by the reception sensors and converted to electrical signals. For this, the sensors are based on electrodes that act as receivers. If a person places their hands within the emission area, a disturbance of the electric field lines is created. This is due to the deviation of the lines to ground using the intrinsic conductivity of the human body. This disturbance affects the signals received by the electrodes. Variations captured by all electrodes are processed together and can determine the position and movement of the hand on the sensor surface. Finally, the development of an improved 3D gesture sensor was carried out. As in the previous development, the sensor allows contactless gesture detection, but increasing the detection range. In addition to printed electronic technology, two other textile manufacturing technologies were evaluated.[ES] La presente tesis doctoral tiene como objetivo fundamental el desarrollo de nuevos sensores y actuadores empleando la tecnología electrónica impresa, también conocida como Printed Electronics. Para ello, se emplean materiales poliméricos conductores, semiconductores y dieléctricos sobre sustratos flexibles y/o elásticos. Por medio de diseños y procesos de aplicación adecuados, es posible fabricar sensores capaces de interactuar con el entorno. De este modo, se pueden incorporar a los sustratos, como puedan ser tejidos textiles, funcionalidades específicas de medición del entorno y de respuesta ante cambios de este. Adicionalmente, es necesario incluir sistemas electrónicos, capaces de realizar el procesado de los datos obtenidos, así como de su registro. En el desarrollo de estos sensores y actuadores se combinan las propiedades físicas de los diferentes materiales de forma precisa. Para ello, se diseñan estructuras multicapa donde las propiedades de unos materiales interaccionan con las de los demás. El resultado es un sensor capaz de captar variaciones físicas del entorno, y convertirlas en señales que pueden ser procesadas y transformadas finalmente en datos. Por una parte, se ha desarrollado un sensor táctil impreso sobre sustrato textil para reconocimiento de gestos en 2D. Este sensor se compone de una matriz formada por pequeños sensores capacitivos basados en estructura de tipo condensador. Estos se han diseñado de forma que, si un dedo u otro objeto con propiedades capacitivas se aproxima suficientemente, su comportamiento varía, pudiendo ser medido. Los pequeños sensores están ordenados en dicha matriz como en una cuadrícula. Cada sensor tiene una posición que viene determinada por una fila y por una columna. Periódicamente se mide la capacidad de cada pequeño sensor con el fin de evaluar si ha sufrido variaciones significativas. Para ello es necesario convertir la capacidad del sensor en un valor que posteriormente es procesado digitalmente. Por otro lado, con el fin de mejorar la efectividad en el uso de los sensores táctiles 2D desarrollados, se ha estudiado el modo de incorporar un sistema actuador. De esta forma, el usuario recibe una retroalimentación indicando que la orden o acción ha sido reconocida. Para ello, se ha complementado la matriz de sensores capacitivos con una pantalla electroluminiscente también impresa. El resultado final ofrece una solución que combina un sensor táctil 2D con un actuador electroluminiscente realizado mediante impresión electrónica sobre sustrato textil. Posteriormente, se ha llevado a cabo el desarrollo de un sensor de gestos 3D empleando una combinación de sensores impresos también sobre sustrato textil. En este tipo de sensor 3D, se envía una señal que genera un campo eléctrico sobre los sensores impresos. Esto se lleva a cabo mediante un electrodo de transmisión situado muy cerca de ellos. El campo generado es recibido por los sensores y convertido a señales eléctricas. Para ello, los sensores se basan en electrodos que actúan de receptores. Si una persona coloca su mano dentro del área de emisión, se crea una perturbación de las líneas de los campos eléctricos. Esto es debido a la desviación de las líneas de campo a tierra utilizando la conductividad intrínseca del cuerpo humano. Esta perturbación cambia/afecta a las señales recibidas por los electrodos. Las variaciones captadas por todos los electrodos son procesadas de forma conjunta pudiendo determinar la posición y el movimiento de la mano sobre la superficie del sensor. Finalmente, se ha llevado a cabo el desarrollo de un sensor de gestos 3D mejorado. Al igual que el desarrollo anterior, permite la detección de gestos sin necesidad de contacto, pero incrementando la distancia de alcance. Además de la tecnología de impresión electrónica, se ha evaluado el empleo de otras dos tecnologías de fabricación textil.[CA] La present tesi doctoral té com a objectiu fonamental el desenvolupament de nous sensors i actuadors fent servir la tecnologia de electrònica impresa, també coneguda com Printed Electronics. Es va fer us de materials polimèrics conductors, semiconductors i dielèctrics sobre substrats flexibles i/o elàstics. Per mitjà de dissenys i processos d'aplicació adequats, és possible fabricar sensors capaços d'interactuar amb l'entorn. D'aquesta manera, es poden incorporar als substrats, com ara teixits tèxtils, funcionalitats específiques de mesurament de l'entorn i de resposta davant canvis d'aquest. Addicionalment, és necessari incloure sistemes electrònics, capaços de realitzar el processament de les dades obtingudes, així com del seu registre. En el desenvolupament d'aquests sensors i actuadors es combinen les propietats físiques dels diferents materials de forma precisa. Cal dissenyar estructures multicapa on les propietats d'uns materials interaccionen amb les de la resta. manera El resultat es un sensor capaç de captar variacions físiques de l'entorn, i convertirles en senyals que poden ser processades i convertides en dades. D'una banda, s'ha desenvolupat un sensor tàctil imprès sobre substrat tèxtil per a reconeixement de gestos en 2D. Aquest sensor es compon d'una matriu formada amb petits sensors capacitius basats en una estructura de tipus condensador. Aquests s'han dissenyat de manera que, si un dit o un altre objecte amb propietats capacitives s'aproxima prou, el seu comportament varia, podent ser mesurat. Els petits sensors estan ordenats en aquesta matriu com en una quadrícula. Cada sensor té una posició que ve determinada per una fila i per una columna. Periòdicament es mesura la capacitat de cada petit sensor per tal d'avaluar si ha sofert variacions significatives. Per a això cal convertir la capacitat del sensor a un valor que posteriorment és processat digitalment. D'altra banda, per tal de millorar l'efectivitat en l'ús dels sensors tàctils 2D desenvolupats, s'ha estudiat la manera d'incorporar un sistema actuador. D'aquesta forma, l'usuari rep una retroalimentació indicant que l'ordre o acció ha estat reconeguda. Per a això, s'ha complementat la matriu de sensors capacitius amb una pantalla electroluminescent també impresa. El resultat final ofereix una solució que combina un sensor tàctil 2D amb un actuador electroluminescent realitzat mitjançant impressió electrònica sobre substrat tèxtil. Posteriorment, s'ha dut a terme el desenvolupament d'un sensor de gestos 3D emprant una combinació d'un mínim de sensors impresos també sobre substrat tèxtil. En aquest tipus de sensor 3D, s'envia un senyal que genera un camp elèctric sobre els sensors impresos. Això es porta a terme mitjançant un elèctrode de transmissió situat molt a proper a ells. El camp generat és rebut pels sensors i convertit a senyals elèctrics. Per això, els sensors es basen en elèctrodes que actuen de receptors. Si una persona col·loca la seva mà dins de l'àrea d'emissió, es crea una pertorbació de les línies dels camps elèctrics. Això és a causa de la desviació de les línies de camp a terra utilitzant la conductivitat intrínseca de el cos humà. Aquesta pertorbació afecta als senyals rebudes pels elèctrodes. Les variacions captades per tots els elèctrodes són processades de manera conjunta per determinar la posició i el moviment de la mà sobre la superfície del sensor. Finalment, s'ha dut a terme el desenvolupament d'un sensor de gestos 3D millorat. A l'igual que el desenvolupament anterior, permet la detecció de gestos sense necessitat de contacte, però incrementant la distància d'abast. A més a més de la tecnologia d'impressió electrònica, s'ha avaluat emprar altres dues tecnologies de fabricació tèxtil.Ferri Pascual, J. (2020). Tactile and Touchless Sensors Printed on Flexible Textile Substrates for Gesture Recognition [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/153075TESISCompendi

The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m^3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb--Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.Comment: 55 pages, 82 figure

A novel device for precise training and perturbing of motor cortically driven forelimb behaviors in the rat

Compared to humans and non-human primates, the rat is a promising model for studying the motor cortex during structured behavioral tasks due to its low cost and rapid trainability. However, options for behavioral tools for investigating motor cortically driven forelimb behaviors are limited. Here, we developed a one-dimensional rotation manipulandum for rat forelimb supination training that has low-latency, high-resolution detection of holding and turning. Additionally, we characterized the system to accurately produce a range of torques that could be used to dynamically perturb rodent forelimb rotation behavior with high precision. Following characterization, we validated the behavioral device using two behavioral paradigms, a static holding task and a knob turning task with virtual stiffness. Rats trained on the static holding task saw significant increases in their holding durations, while those trained on the knob turning task had significantly decreased peak turning angles as motor torque was increased. This end-to-end characterization showed our device to be effective at training and perturbing multiple potentially motor cortically driven behaviors. Ultimately, we hope to use this tool to uncover evidence of a dynamical system in rat motor cortex, like those already discovered in humans and monkeys.M.S