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arXiv 2023年

作者： Walsemann, A. Karagounis, M. Stanitzki, A. Tutsch, D. University of Applied Sciences and Arts Dortmund Sonnenstraße 96-100 Dortmund44139 Germany Fraunhofer Institute for Microelectronic Circuits and Systems Finkenstraße 61 Duisburg47057 Germany University of Wuppertal Gaußstraße 20 Wuppertal42119 Germany

While microprocessors are used in various applications, they are precluded from the use in high-energy physics applications due to the harsh radiation present. To overcome this limitation a microprocessor design must withstand high doses of radiation and mitigate radiation induced soft errors. A TMR protection scheme is applied to protect a RISC-V microprocessor core against these faults. The protection of the integrated SRAM by an independent scrubbing algorithm is discussed. Initial irradiation results and power consumption measurements of the radiation-resistant RISC-V microprocessor implemented in 65 nm CMOS technology are presented. Copyright © 2023, The Authors. All rights reserved.

关键词： VLSI circuits

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Implementation and Evaluation of a Neural Network-Based LiDAR Histogram Processing Method on FPGA

Implementation and Evaluation of a Neural Network-Based LiDA...

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IEEE International SOC Conference

作者： Gongbo Chen Giray Atabey Kirtiz Christian Wiede Rainer Kokozinski Fraunhofer Institute of Microelectronic Circuits and Systems (IMS) Duisburg Germany University of Duisburg-Essen (UDE) Duisburg Germany

ISBN: (纸本)9781665429320

In applications of advanced driver assistance systems (ADAS), a single photon avalanche diode (SPAD)-based direct time-of-flight (d-TOF) LiDAR system is one of the promising range sensor systems. Many processing algorithms based on this LiDAR system have been developed. Therein, neural network-based multi-peak analysis (NNMPA) is a LiDAR histogram processing method, which improves the distance measurement robustness under harsh environment conditions, e.g. high ambient light or large distances. However, the portability of the NNMPA on embedded systems remains challenging and should be further implemented and evaluated. In this paper, the NNMPA is implemented on Enclustra Mars ZX3 FPGA board to enable a system-on-chip (SoC) test of the method. The presented implementation achieves a frame rate of 20 fps with 96 pixels. The accuracy drop-off of 1.23 % is observed compared to the floating-point arithmetic implementation on PC.

关键词： Histograms Laser radar Artificial neural networks Sensor systems Robustness System-on-chip Advanced driver assistance systems

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Modeling of Random Variations in a Switched Capacitor Circuit based Physically Unclonable Function 8

Modeling of Random Variations in a Switched Capacitor Circui...

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8th International Conference on Information Technology: IoT and Smart City, ICIT 2020

作者： Ahmad, Zahoor Zimmermann, Lukas Müller, Kai-Uwe Sikora, Axel Institute of Reliable Embedded Systems and Communication Electronics 77652 Offenburg Germany and Hochschule Offenburg Germany Germany Fraunhofer Institute for Microelectronic Circuits and Systems IMS Duisburg47057 Germany

ISBN: (纸本)9781450388559

The Internet of Things (IoT) is expanding to a wide range of fields such as home automation, agriculture, environmental monitoring, industrial applications, and many more. Securing tens of billions of interconnected devices in the near future will be one of the biggest challenges. IoT devices are often constrained in terms of computational performance, area, and power, which demand lightweight security solutions. In this context, hardware-intrinsic security, particularly physically unclonable functions (PUFs), can provide lightweight identification and authentication for such devices. In this paper, random capacitor variations in a switched capacitor PUF circuit are used as a source of entropy to generate unique security keys. Furthermore, a mathematical model based on the ordinary least square method is developed to describe the relationship between random variations in capacitors and the resulting output voltages. The model is used to filter out systematic variations in circuit components to improve the quality of the extracted secrets. © 2020 ACM.

关键词： Internet of things

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A 61-GHz RFID Frontend with SiGe Transceiver MMIC and SIW Coupling Network

A 61-GHz RFID Frontend with SiGe Transceiver MMIC and SIW Co...

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European Conference on Microwave

作者： Dominic A. Funke Steffen Hansen Christian Bredendiek Thorben Grenter Gerd vom Bögel Armen Harutyunyan Raik Fiedler Andreas Heinig Nils Pohl Chair for Integrated Systems Ruhr-University Bochum Germany Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR) Germany Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) Germany Fraunhofer Institute for Photonic Microsystems (IPMS) Germany

ISBN: (数字)9782874870590

ISBN: (纸本)9781728170398

This paper presents the frontend of a 61-GHz RFID reader. The frontend consists of a transceiver MMIC, an open waveguide used as a circular polarized antenna and a coupling network. The coupling network connects the MMIC with the open waveguide antenna and provides isolation between the receive and transmit path. It is realized in substrate integrated waveguide technology. The MMIC was fabricated in a 130-nm SiGe BiCMOS technology and includes a voltage controlled oscillator, a receive mixer and a power amplifier. The power amplifier uses Wilkinson-combiners to implement the concept of power combining and achieves an output power of 19dBm at 61GHz. The equivalent isotropically radiated power was measured to be 23.48dBm, which is to the authors' best knowledge the highest value reported for 61-GHz RFID readers.

关键词： Couplings Voltage-controlled oscillators Power amplifiers Transceivers Power generation Radiofrequency identification Silicon germanium

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Combination of sensor-embedded and secure server-distributed artificial intelligence for healthcare applications

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Current Directions in Biomedical Engineering 2019年第1期5卷 29-32页

作者： Gembaczka, Pierre Heidemann, Burkhard Bennertz, Bernhard Groeting, Wolfgang Norgall, Thomas Seidl, Karsten Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) Duisburg Germany Fraunhofer Institute for Integrated Circuits (IIS) Erlangen Germany Department of Electronic Components and Circuits University of Duisburg-Essen Duisburg Germany

The application of artificial intelligence (AI) in the areas of health, care and social participation offers great opportunities but also involves great challenges. Extensive regulatory, ethical and data-security related requirements exist for data recording, storage and processing of respective personalized and patient-related data. "Artificial Intelligence as a Service" (AIaaS) is pushed for consumer applications by global players, which implies data storage on external database server. However, the available solutions do not meet the requirements. Moreover, small and medium-sized enterprises (SMEs) in the field of healthcare fear the loss of data sovereignty and information outflow. In this paper, we propose a secure and resource-efficient approach by embedding AI directly close to the sensor in combination with secure and distributed data processing on local server or certified "Trusted Data Center". For this purpose, we have developed the Artificial Intelligence for Embedded systems (AIfES) platform-independent machine learning library in C programming language. It contains a fully configurable deep artificial neural network with feedforward structure. The library can be run directly on a microcontroller and even allows to train the neural network. Possible healthcare applications include direct (pre-) processing of sensor data, sensor calibration, pattern recognition and classification. © 2019 by Walter de Gruyter Berlin/Boston 2019.

关键词： Embedded systems

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Temperature Characterization of High-Q Resonators of Different Materials for mm-Wave Indoor Localization Tag Landmarks 14

Temperature Characterization of High-Q Resonators of Differe...

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14th European Conference on Antennas and Propagation, EuCAP 2020

作者： Jimenez-Saez, Alejandro Schusler, Martin Pandel, Damian Krause, Christopher Zhao, Yixiong Bogel, Gerd Vom Benson, Niels Jakoby, Rolf Institute of Microwave Engineering and Photonics Technische Universität Darmstadt Darmstadt Germany Institute of Technology for Nanostructures and Cenide University of Duisburg-Essen Duisburg Germany Fraunhofer Institute for Microelectronic Circuits and Systems Duisburg Germany

ISBN: (纸本)9788831299008

This paper discusses a temperature-dependent characterization of deep reactive ion-etched 10 k\Omega cm high-resistive silicon (DRIE HR-Si), 3D printed alumina (Al-{2}O-{3}) and milled Rogers RT/Duroid® 6010.2LM. The characterization is performed by measuring high-Q photonic crystal resonator samples in W-band and the measurements are taken from 30C to 115C. HR-Si is the material with the lowest losses at room temperature. However, its losses increase with temperature and become higher than 3D printed alumina at 75°C, reducing the radar cross-section and maximum readout range of chipless wireless RFID tags integrating several of these resonators. These results demonstrate that, while HR-Si performance is higher for the usual temperatures achieved in an indoor localization scenario, 3D printed alumina is more suitable if a temperature-stable response is needed or if the tags need to operate at high temperatures, such as in case of fire. © 2020 EurAAP.

关键词： Radar cross section

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Design of an Artificial Neural Network Circuit for detecting Atrial Fibrillation in ECG Signals

Design of an Artificial Neural Network Circuit for detecting...

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IEEE SENSORS

作者： Renee Lerch Babak Hosseini Pierre Gembaczka Gernot A. Fink Andre Lüdecke Viktor Brack Furkan Ercan Alexander Utz Karsten Seidl Fraunhofer Institute for Microelectronic Circuits and Systems IMS Duisburg Germany Computer Science Faculty TU Dortmund Dortmund Germany University of Duisburg-Essen Duisburg Germany

In this paper we present the design of a low-power on-chip sensor signal processing system which analyzes electrocardiogram (ECG) data for signs of atrial fibrillation. By optimizing an artificial neural network and using highly optimized and flexible register-transfer-level circuit models, an energy-efficient digital circuit was designed with a regular standard cell synthesis design flow in a 130 nm CMOS technology. The resulting circuit consumes 360 nJ of energy for the processing of one complete ECG trace and occupies 5 mm 2 of silicon in the chosen target CMOS technology. While some of the methods are specific to the task, the general principles can be adapted to other signal analysis tasks and allow the use of machine learning under constraints of energy, size and cost.

关键词： Semiconductor device modeling Atrial fibrillation Artificial neural networks Electrocardiography CMOS technology Silicon System-on-chip

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Hyperspectral near infrared imaging using a tunable spectral phasor

arXiv

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arXiv 2024年

作者： Stegemann, Jan Gröniger, Franziska Neutsch, Krisztian Li, Han Flavel, Benjamin Metternich, Justus Tom Erpenbeck, Luise Petersen, Poul Hedde, Per Niklas Kruss, Sebastian Department of Chemistry and Biochemistry Bochum University Bochum Germany Fraunhofer Institute for Microelectronic Circuits and Systems Duisburg Germany Department of Mechanical and Materials Engineering University of Turku TurkuFI-20014 Finland Turku Collegium for Science Medicine and Technology University of Turku TurkuFI-20520 Finland Institute of Nanotechnology Karlsruhe Institute of Technology Karlsruhe Germany Department of Dermatology University Hospital Münster Münster Germany Beckman Laser Institute & Medical Clinic University of California IrvineCA United States

Hyperspectral imaging captures both spectral and spatial information from a sample. The near infrared (NIR, > 800 nm) is advantageous for biomedical imaging as it falls into the tissue transparency window but also contains vibrational overtone and combination modes useful for molecular fingerprinting. Here, we demonstrate hyperspectral NIR imaging using a spectral phasor transformation (HyperNIR). This method employs a liquid crystal variable retarder (LCVR) for tunable, wavelength-dependent sine-, cosine and no filtering that transforms optical signals into phasor space. Spectral information is thus obtained with just three images. The LCVR can be adjusted to cover a spectral range from 900 nm to 1600 nm in windows tunable from 50 nm to 700 nm. This approach enables distinguishing NIR fluorophores with emission peaks less than 5 nm apart. Furthermore, we demonstrate label-free hyperspectral NIR reflectance imaging to identify plastic polymers and to monitor in vivo plant health. The approach uses the full camera resolution and reaches hyperspectral frame rates of 0.2 per second, limited only by the switching rate of the LCVR. HyperNIR facilitates straightforward hyperspectral imaging with standard NIR cameras for applications in biomedical imaging and environmental monitoring. © 2024, CC BY.

关键词： Hyperspectral imaging

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A Piezoelectric Flexural Plate Wave (FPW) Bio-MEMS Sensor with Improved Molecular Mass Detection for Point-of-Care Diagnostics

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Current Directions in Biomedical Engineering 2019年第1期5卷 265-268页

作者： Walk, Christian Wiemann, Matthias Görtz, Michael Weidenmüller, Jens Jupe, Andreas Seidl, Karsten Fraunhofer Institute for Microelectronic Circuits and Systems (IMS) Finkenstrasse 61 Duisburg Germany Fraunhofer IMS Duisburg Germany University of Duisburg-Essen Dep. of Electronic Components and Circuits Duisburg Germany

A piezoelectric FPW-sensor has been developed for a point of care device in this work. The Bio- MEMS FPW-sensor consists of an electrode configuration termed as an interdigital transducer (IDT) placed on a membrane. An input IDT excites and an output IDT detects the propagating acoustic waves through a PZT layer. Design optimizations and fabrication improvements of the FPW-sensor led to significantly reduced attenuation of the wave signal and the damping of the propagating waves between the IDTs. The working principle of mass loading is shown using different low-viscous liquids. A densitydependent sensitivity of -0.39 MHz/g/cm3 was evaluated. After the membrane was functionalized, the Bio-MEMS FPW-sensor was used to measure a specific chemokine in complex solution. By design improvements, the resolution was significantly increased from 0.7 Hz/nM to 14 Hz/nM. © 2019 by Walter de Gruyter Berlin/Boston.

关键词： Piezoelectricity

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Scalable hybrid microelectronic-microfluidic integration of highly sensitive biosensors

Advancing Microelectronics

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Advancing microelectronics 2020年第2期47卷 20-26页

作者： Reinecke, Patrick Putze, Marie-Theres Georgi, Leopold Kahle, Ruben Kaiser, David Hüger, Daniel Livshits, Pavel Weidenmüller, Jens Weimann, Thomas Turchanin, Andrey Braun, Tanja Becker, Karl-Friedrich Schneider-Ramelow, Martin Lang, Klaus-Dieter Technical University Berlin Berlin10623 Germany Fraunhofer Institute for Reliability and Microintegration Berlin13355 Germany Friedrich Schiller University Jena Jena07743 Germany Fraunhofer Institute for Microelectronic Circuits and Systems Duisburg47057 Germany Physikalisch-Technische Bundesanstalt Braunschweig38116 Germany

Point of Care devices for medical applications are becoming more and more widespread. The advantage of having test results after a very short period and without any laboratory is beneficial for doctors in developing countries far away from laboratory infrastructure to clinical devices disburdening in-house laboratories, for example, in case of an outbreak of an epidemic. Especially infectious diseases are one of the world's leading cause of morbidity and death [1]. Viral respiratory infections are a major cause of burden of disease in children. Annual human respiratory syncytial virus (RSV) related death are around 253,000, mainly in developing countries. It accounts for up to 6.7 % of mortality of children younger than 1 year. Therefore, RSV is the second most important global cause of death during infancy. Furthermore, RSV infection has been linked to an increased risk in the development of childhood wheezing and asthma in later life [2, 3]. Fast and cheap diagnostic, independent from laboratory infrastructure, will have a high impact on the healthcare system. Highly sensitive microelectronic biosensors have a superior sensitivity and accuracy compared to paper stripes. The higher miniaturization potential and production stability accompanied by a better readout simplicity makes them a cheaper alternative to optical systems. In this paper a hybrid microelectronic-microfluidic packaging strategy for a disposable, two different microelectronic biosensor platforms will be presented, targeting the diagnostic of RSV. The multiplexed detection of both, host and pathogen biomarkers in the same sample will lead to a rapid, cheap and accurate diagnosis and prognosis, providing almost real-time results. Platform 1, the BioGrFET sensor, uses a graphene field effect transistor (GrFET). The liquid sample containing the biomarkers flows over the sensor's surface with probe molecules, where the target molecules (specific biomarkers) of the fluid can be immobilized. The charge of

关键词： Biomarkers

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