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Special Issue "Advanced Interface Circuits for Sensor Systems"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: 1 May 2021.

Special Issue Editors

Prof. Dr. Pak Kwong Chan
Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
Interests: sensor interface ICs; smart sensor systems; low-energy low-noise circuit design; sensor power management ICs; PVT-insensitive circuits and systems
Special Issues and Collections in MDPI journals
Prof. Dr. Holden King-Ho Li
Website
Guest Editor
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Interests: MEMS sensors; MOEMS sensors; CMOS-MEMS integration; sensor reliability and long term performance; sensor design for manufacturability
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors are widely used in healthcare, automobiles, consumer electronics, industrial applications, and so forth. With that demand, comes an expectation of high quality and intelligent sensor circuits. In an era of digital technology, digital-aware or software-aware sensor circuits becomes the design agenda. With the emergence of artificial intelligence (AI) Internet-of-Things (AI-IoT) as one of the driving forces, this has posed further design criteria and constraints to the interface circuits that aim to enhance the detection capability through the assistance of AI. It turns out that the interface circuits, which may be coupled with intelligent peripheral support circuits, are to provide advanced features to meet high-performance-aware specifications or high-adaptability, etc. and, therefore, realize smart functions through smart program control. These design concerns impose design challenges and cause a paradigm shift in the design approach to designers or researchers in the emerging field. This Special Issue will publish papers that explore the potential solutions to tackle the stated issues. Potential topics will not be limited to the following:

  • High-performance interface circuits
  • AI-IoT sensor circuit design and techniques
  • Smart power management circuits for sensors
  • Sensor circuits with configurable architectures
  • Intelligent peripheral circuits for sensor circuits
  • Software for sensor circuits
  • Digital-assisted sensor circuits
  • Data communication for sensor circuits
Prof. Dr. Pak Kwong Chan
Prof. Dr. Holden King-Ho Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • readout circuits
  • interface circuit techniques
  • AI-IoT
  • power management
  • system architectures
  • sensor peripheral circuits
  • data communication
  • digital-assisted design
  • software-assisted design

Published Papers (4 papers)

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Open AccessArticle
A Self-Powered Hybrid SSHI Circuit with a Wide Operation Range for Piezoelectric Energy Harvesting
Sensors 2021, 21(2), 615; https://doi.org/10.3390/s21020615 - 17 Jan 2021
Abstract
This paper presents a piezoelectric (PE) energy harvesting circuit, which integrates a Synchronized Switch Harvesting on Inductor (SSHI) circuit and a diode bridge rectifier. A typical SSHI circuit cannot transfer the power from a PE cantilever into the load when the rectified voltage [...] Read more.
This paper presents a piezoelectric (PE) energy harvesting circuit, which integrates a Synchronized Switch Harvesting on Inductor (SSHI) circuit and a diode bridge rectifier. A typical SSHI circuit cannot transfer the power from a PE cantilever into the load when the rectified voltage is higher than a certain voltage. The proposed circuit addresses this problem. It uses the two resonant loops for flipping the capacitor voltage and energy transfer in each half cycle. One resonant loop is typically used for the parallel SSHI scheme, and the other for the series SSHI scheme. The hybrid SSHI circuit using the two resonant loops enables the proposed circuit’s output voltage to no longer be limited. The circuit is self-powered and has the capability of starting without the help of an external battery. Eleven simple discrete components prototyped the circuit. The experimental results show that, compared with the full-bridge (FB) circuit, the amount of power harvested from a PE cantilever and the Voltage Range of Interest (VRI) of the proposed circuit is increased by 2.9 times and by 4.4 times, respectively. A power conversion efficiency of 83.2% is achieved. Full article
(This article belongs to the Special Issue Advanced Interface Circuits for Sensor Systems)
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Open AccessArticle
Implementation of Analog Perceptron as an Essential Element of Configurable Neural Networks
Sensors 2020, 20(15), 4222; https://doi.org/10.3390/s20154222 - 29 Jul 2020
Abstract
Perceptron is an essential element in neural network (NN)-based machine learning, however, the effectiveness of various implementations by circuits is rarely demonstrated from chip testing. This paper presents the measured silicon results for the analog perceptron circuits fabricated in a 0.6 μm/±2.5 [...] Read more.
Perceptron is an essential element in neural network (NN)-based machine learning, however, the effectiveness of various implementations by circuits is rarely demonstrated from chip testing. This paper presents the measured silicon results for the analog perceptron circuits fabricated in a 0.6 μm/±2.5 V complementary metal oxide semiconductor (CMOS) process, which are comprised of digital-to-analog converter (DAC)-based multipliers and phase shifters. The results from the measurement convinces us that our implementation attains the correct function and good performance. Furthermore, we propose the multi-layer perceptron (MLP) by utilizing analog perceptron where the structure and neurons as well as weights can be flexibly configured. The example given is to design a 2-3-4 MLP circuit with rectified linear unit (ReLU) activation, which consists of 2 input neurons, 3 hidden neurons, and 4 output neurons. Its experimental case shows that the simulated performance achieves a power dissipation of 200 mW, a range of working frequency from 0 to 1 MHz, and an error ratio within 12.7%. Finally, to demonstrate the feasibility and effectiveness of our analog perceptron for configuring a MLP, seven more analog-based MLPs designed with the same approach are used to analyze the simulation results with respect to various specifications, in which two cases are used to compare to their digital counterparts with the same structures. Full article
(This article belongs to the Special Issue Advanced Interface Circuits for Sensor Systems)
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Open AccessLetter
A Real-Time Thermal Monitoring System Intended for Embedded Sensors Interfaces
Sensors 2020, 20(19), 5657; https://doi.org/10.3390/s20195657 - 03 Oct 2020
Abstract
This paper proposes a real-time thermal monitoring method using embedded integrated sensor interfaces dedicated to industrial integrated system applications. Industrial sensor interfaces are complex systems that involve analog and mixed signals, where several parameters can influence their performance. These include the presence of [...] Read more.
This paper proposes a real-time thermal monitoring method using embedded integrated sensor interfaces dedicated to industrial integrated system applications. Industrial sensor interfaces are complex systems that involve analog and mixed signals, where several parameters can influence their performance. These include the presence of heat sources near sensitive integrated circuits, and various heat transfer phenomena need to be considered. This creates a need for real-time thermal monitoring and management. Indeed, the control of transient temperature gradients or temperature differential variations as well as the prediction of possible induced thermal shocks and stress at early design phases of advanced integrated circuits and systems are essential. This paper addresses the growing requirements of microelectronics applications in several areas that experience fast variations in high-power density and thermal gradient differences caused by the implementation of different systems on the same chip, such as the new-generation 5G circuits. To mitigate adverse thermal effects, a real-time prediction algorithm is proposed and validated using the MCUXpresso tool applied to a Freescale embedded sensor board to monitor and predict its temperature profile in real time by programming the embedded sensor into the FRDM-KL26Z board. Based on discrete temperature measurements, the embedded system is used to predict, in advance, overheating situations in the embedded integrated circuit (IC). These results confirm the peak detection capability of the proposed algorithm that satisfactorily predicts thermal peaks in the FRDM-KL26Z board as modeled with a finite element thermal analysis tool (the Numerical Integrated elements for System Analysis (NISA) tool), to gauge the level of local thermomechanical stresses that may be induced. In this paper, the FPGA implementation and comparison measurements are also presented. This work provides a solution to the thermal stresses and local system overheating that have been a major concern for integrated sensor interface designers when designing integrated circuits in various high-performance technologies or harsh environments. Full article
(This article belongs to the Special Issue Advanced Interface Circuits for Sensor Systems)
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Open AccessBrief Report
A High-Efficiency Driver Circuit for a Gas-Sensor Microheater Based on a Switch-Mode DC-to-DC Converter
Sensors 2020, 20(18), 5367; https://doi.org/10.3390/s20185367 - 19 Sep 2020
Abstract
Low power consumption is one of the critical factors for successful Internet of Things (IoT) applications. In such applications, gas sensors have become a main source of power consumption because energy conversion efficiency of the microheater is relative over a wide range of [...] Read more.
Low power consumption is one of the critical factors for successful Internet of Things (IoT) applications. In such applications, gas sensors have become a main source of power consumption because energy conversion efficiency of the microheater is relative over a wide range of operating temperatures. To improve the energy-conversion efficiency of gas-sensor microheaters, this paper proposes integrated switch-mode DC-to-DC power converter technology which we compare with traditional driving methods such as pulse-width modulation and the linear mode. The results indicate that energy conversion efficiency with this proposed method remains over 90% from 150 °C to 400 °C when using a 3.0, 4.2 and 5.0 V power supply. Energy-conversion efficiency increases by 1–74% compared with results obtained using the traditional driving methods, and the sensing film still detects alcohol and toluene at 200 °C and 280 °C, respectively, with high energy conversion efficiency. These results show that the proposed method is useful and should be further developed to drive gas-sensor microheaters, and then integrated into the circuits of the complementary metal-oxide-semiconductor micro electro mechanical systems (CMOS-MEMS). Full article
(This article belongs to the Special Issue Advanced Interface Circuits for Sensor Systems)
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