Sub-Femto-Farad Resolution Electronic Interfaces for Integrated Capacitive Sensors: A Review

Capacitance detection is a universal transduction mechanism used in a wide variety of sensors and applications. It requires an electronic front-end converting the capacitance variation into another more convenient physical variable, ultimately determining the performance of the whole sensor. In this paper we present a comprehensive review of the different signal conditioning front-end topologies targeted in particular at sub-femtofarad resolution. Main design equations and analysis of the limits due to noise are reported in order to provide the designer with guidelines for choosing the most suitable topology according to the main design specifications, namely energy consumption, area occupation, measuring time and resolution. A data-driven comparison of the different solutions in literature is also carried out revealing that resolution, measuring time, area occupation and energy/conversion lower than 100 aF, 1 ms 0.1 mm2, and 100 pJ/conv. can be obtained by capacitance to digital topologies, which therefore allow to get the best compromise among all design specifications

Diseño de circuitos para lectura de sensores MEMS en tecnología CMOS

En los últimos años el desarrollo de tecnologías Wireless ha permitido el desarrollo de redes de sensores. Dichas redes de sensores gozan cada vez más de mayor importancia, y permiten realizar sistemas cada vez más inteligentes al comunicar en tiempo real a distintos dispositivos entre sí y al permitirles a su vez obtener información vital para su funcionamiento. Todo esto ha permitido desarrollar un nuevo concepto conocido como internet de las cosas o Internet of Things. En el internet de las cosas distintos dispositivos se relacionan entre sí y con el medio. En muchos casos ello permite controlar distintos dispositivos así como recibir información de los mismos desde algo tan cotidiano como un teléfono móvil. Para poder realizar estos sistemas se necesitan sensores de bajo coste y bajo consumo que puedan interactuar con los dispositivos digitales. En el presente trabajo se presenta un diseño a alto nivel de un circuito para mediad de presión mediante un sensor microelectromecánico, MEM. Dicho circuito se caracteriza por su bajo consumo y su alta resolución que alcanza unos 18 bits. Para la realización de este circuito se emplea una topología de tipo doble rampa debido a su bajo coste y simplicidad. Para obtener una elevada resolución se diseña un modo de operación de dicho circuito que hace que este se comporte como un convertidor de tipo Sigma-Delta de primer orden. Así mismo dicho circuito se conecta directamente al sensor de forma que no son necesarios circuitos de adaptación adicionales. Por último se trata la implementación física de dicho circuito haciendo hincapié en el problema del ruido flicker. Para solucionarlo se estudia la forma más adecuada de implementación de la técnica para reducir los efectos del ruido flicker conocida como chopping.Ingeniería Electrónica Industrial y Automátic

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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

Interface Circuits for Microsensor Integrated Systems

ca. 200 words; this text will present the book in all promotional forms (e.g. flyers). Please describe the book in straightforward and consumer-friendly terms. [Recent advances in sensing technologies, especially those for Microsensor Integrated Systems, have led to several new commercial applications. Among these, low voltage and low power circuit architectures have gained growing attention, being suitable for portable long battery life devices. The aim is to improve the performances of actual interface circuits and systems, both in terms of voltage mode and current mode, in order to overcome the potential problems due to technology scaling and different technology integrations. Related problems, especially those concerning parasitics, lead to a severe interface design attention, especially concerning the analog front-end and novel and smart architecture must be explored and tested, both at simulation and prototype level. Moreover, the growing demand for autonomous systems gets even harder the interface design due to the need of energy-aware cost-effective circuit interfaces integrating, where possible, energy harvesting solutions. The objective of this Special Issue is to explore the potential solutions to overcome actual limitations in sensor interface circuits and systems, especially those for low voltage and low power Microsensor Integrated Systems. The present Special Issue aims to present and highlight the advances and the latest novel and emergent results on this topic, showing best practices, implementations and applications. The Guest Editors invite to submit original research contributions dealing with sensor interfacing related to this specific topic. Additionally, application oriented and review papers are encouraged.