826 research outputs found

    A compact current-mode instrumentation amplifier for general-purpose sensor interfaces

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    The proposed amplifier architecture follows a consolidated topology based on second-generation current conveyors (CCIIs), optimized for fully-differential operation. The architecture uses gain-boosting to improve the offset and noise characteristics of a recently proposed design. Wide input and output ranges and high accuracy are obtained by designing the CCIIs according to an original two-stage architecture with local voltage feedback. Embedding of chopper switch matrices into the amplifier enables vector analysis of the input signal, expanding the application field. The main strengths of the proposed amplifier are compactness and versatility. Measurements performed on a prototype designed with a 0.18 μm CMOS process are described

    A high performance LIA-based interface for battery powered sensing devices

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    This paper proposes a battery-compatible electronic interface based on a general purpose lock-in amplifier (LIA) capable of recovering input signals up to the MHz range. The core is a novel ASIC fabricated in 1.8 V 0.18 µm CMOS technology, which contains a dual-phase analog lock-in amplifier consisting of carefully designed building blocks to allow configurability over a wide frequency range while maintaining low power consumption. It operates using square input signals. Hence, for battery-operated microcontrolled systems, where square reference and exciting signals can be generated by the embedded microcontroller, the system benefits from intrinsic advantages such as simplicity, versatility and reduction in power and size. Experimental results confirm the signal recovery capability with signal-to-noise power ratios down to -39 dB with relative errors below 0.07% up to 1 MHz. Furthermore, the system has been successfully tested measuring the response of a microcantilever-based resonant sensor, achieving similar results with better power-bandwidth trade-off compared to other LIAs based on commercial off-the-shelf (COTS) components and commercial LIA equipment

    A neural probe with up to 966 electrodes and up to 384 configurable channels in 0.13 μm SOI CMOS

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    In vivo recording of neural action-potential and local-field-potential signals requires the use of high-resolution penetrating probes. Several international initiatives to better understand the brain are driving technology efforts towards maximizing the number of recording sites while minimizing the neural probe dimensions. We designed and fabricated (0.13-μm SOI Al CMOS) a 384-channel configurable neural probe for large-scale in vivo recording of neural signals. Up to 966 selectable active electrodes were integrated along an implantable shank (70 μm wide, 10 mm long, 20 μm thick), achieving a crosstalk of −64.4 dB. The probe base (5 × 9 mm2) implements dual-band recording and a 1

    A 5.5 μW 42nV/√Hz Chopper stabilized Amplifier for Biomedical Application with Input Impedance Enhancement

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    The continuous real-time monitoring of diverse physical parameters using biosignals like ECG and EEG requires the biomedical sensors. Such sensor consists of analog frontend unit for which low noise and low power Operational transconductance amplifier (OTA) is essential. In this paper, the novel chopper-stabilized bio-potential amplifier is proposed. The chopper stabilization technique is used to reduce the offset and flicker noise. Further, the OTA is likewise comprised of a method to enhance the input impedance without consuming more power. Also, the ripple reduction technique is used at the output branch of the OTA. The designed amplifier consumes 5.5 μW power with the mid-band gain of 40dB. The pass-band for the designed amplifier is 0.1Hz to 1KHz. The input impedance is likewise boosted with the proposed method. The noise is 42 nV/√Hz with CMRR of 82 dB. All simulations are carried out in 180nm parameters

    Wideband Fully-Programmable Dual-Mode CMOS Analogue Front-End for Electrical Impedance Spectroscopy

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    This paper presents a multi-channel dual-mode CMOS analogue front-end (AFE) for electrochemical and bioimpedance analysis. Current-mode and voltage-mode readouts, integrated on the same chip, can provide an adaptable platform to correlate single-cell biosensor studies with large-scale tissue or organ analysis for real-time cancer detection, imaging and characterization. The chip, implemented in a 180-nm CMOS technology, combines two current-readout (CR) channels and four voltage-readout (VR) channels suitable for both bipolar and tetrapolar electrical impedance spectroscopy (EIS) analysis. Each VR channel occupies an area of 0.48 mm 2 , is capable of an operational bandwidth of 8 MHz and a linear gain in the range between -6 dB and 42 dB. The gain of the CR channel can be set to 10 kΩ, 50 kΩ or 100 kΩ and is capable of 80-dB dynamic range, with a very linear response for input currents between 10 nA and 100 μ A. Each CR channel occupies an area of 0.21 mm 2 . The chip consumes between 530 μ A and 690 μ A per channel and operates from a 1.8-V supply. The chip was used to measure the impedance of capacitive interdigitated electrodes in saline solution. Measurements show close matching with results obtained using a commercial impedance analyser. The chip will be part of a fully flexible and configurable fully-integrated dual-mode EIS system for impedance sensors and bioimpedance analysis

    Low power low noise analog front-end IC design for biomedical sensor interface

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    Ph.DDOCTOR OF PHILOSOPH

    Ultra-low power mixed-signal frontend for wearable EEGs

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    Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

    DESIGN OF SMART SENSORS FOR DETECTION OF PHYSICAL QUANTITIES

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    Microsystems and integrated smart sensors represent a flourishing business thanks to the manifold benefits of these devices with respect to their respective macroscopic counterparts. Miniaturization to micrometric scale is a turning point to obtain high sensitive and reliable devices with enhanced spatial and temporal resolution. Power consumption compatible with battery operated systems, and reduced cost per device are also pivotal for their success. All these characteristics make investigation on this filed very active nowadays. This thesis work is focused on two main themes: (i) design and development of a single chip smart flow-meter; (ii) design and development of readout interfaces for capacitive micro-electro-mechanical-systems (MEMS) based on capacitance to pulse width modulation conversion. High sensitivity integrated smart sensors for detecting very small flow rates of both gases and liquids aiming to fulfil emerging demands for this kind of devices in the industrial to environmental and medical applications. On the other hand, the prototyping of such sensor is a multidisciplinary activity involving the study of thermal and fluid dynamic phenomenon that have to be considered to obtain a correct design. Design, assisted by finite elements CAD tools, and fabrication of the sensing structures using features of a standard CMOS process is discussed in the first chapter. The packaging of fluidic sensors issue is also illustrated as it has a great importance on the overall sensor performances. The package is charged to allow optimal interaction between fluids and the sensors and protecting the latter from the external environment. As miniaturized structures allows a great spatial resolution, it is extremely challenging to fabricate low cost packages for multiple flow rate measurements on the same chip. As a final point, a compact anemometer prototype, usable for wireless sensor network nodes, is described. The design of the full custom circuitry for signal extraction and conditioning is coped in the second chapter, where insights into the design methods are given for analog basic building blocks such as amplifiers, transconductors, filters, multipliers, current drivers. A big effort has been put to find reusable design guidelines and trade-offs applicable to different design cases. This kind of rational design enabled the implementation of complex and flexible functionalities making the interface circuits able to interact both with on chip sensors and external sensors. In the third chapter, the chip floor-plan designed in the STMicroelectronics BCD6s process of the entire smart flow sensor formed by the sensing structures and the readout electronics is presented. Some preliminary tests are also covered here. Finally design and implementation of very low power interfaces for typical MEMS capacitive sensors (accelerometers, gyroscopes, pressure sensors, angular displacement and chemical species sensors) is discussed. Very original circuital topologies, based on chopper modulation technique, will be illustrated. A prototype, designed within a joint research activity is presented. Measured performances spurred the investigation of new techniques to enhance precision and accuracy capabilities of the interface. A brief introduction to the design of active pixel sensors interface for hybrid CMOS imagers is sketched in the appendix as a preliminary study done during an internship in the CNM-IMB institute of Barcelona

    Development of a Waveform Sampling ASIC with Femtosecond Timing for a Low Occupancy Vertex Detector.

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    Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018
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