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A High Dynamic Range Dual 8x16 capacitive sensor array for Life Science Applications

IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022年第6期16卷 1191-1203页

作者： Tabrizi, Hamed Osouli Forouhi, Saghi Ghafar-Zadeh, Ebrahim York Univ Lassonde Sch Engn Elect Engn & Comp Sci Dept Biolog Inspired Sensor & Actuator Lab Toronto ON M3J 1P3 Canada

This paper presents a fully integrated complementary metal-oxide-semiconductor (CMOS) capacitive sensor array for life science applications. This sensing device consists of an array of 16 x 16 interdigitated electrodes (IDEs) integrated with a charge-based readout and multiplexing circuitries on the same chip. This chip was implemented in 0.35 mu m AMS CMOS process. This sensing device has a wide input capacitance range (ICR) of about 100 fF and a resolution of 150 aF, and the capability of temporal, spatial, and dielectric sensing. It makes it possible to develop a low-cost, multimodal, calibration-free sensing platform for life science applications. Here, we demonstrate and discuss the functionality and applicability of the proposed sensing device by introducing various chemical solvents including ethanol, methanol, and pure water. The simulation and experimental results achieved in this work have taken us one step closer to a fully automated calibration-free multimodal capacitive sensing platform for high-throughput drug development and other purposes.

关键词： sensors sensor arrays capacitive sensors Capacitance CMOS technology Calibration Capacitance measurement capacitive sensor array complementary metal-oxide-semiconductor technology multiplexing scheme wide input capacitance range

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Gesture Classification with Low-Cost capacitive sensor array for Upper Extremity Rehabilitation 18

Gesture Classification with Low-Cost Capacitive Sensor Array...

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18th IEEE sensors Conference

作者： Liu, Haoyan Sanchez, Enrique Parkerson, James Nelson, Alexander Univ Arkansas Dept Comp Sci & Comp Engn Fayetteville AR 72701 USA

ISBN: (纸本)9781728116341

Machine Learning and artificial intelligence play major roles in understanding human activity through various classification and regression tasks. However, for many low-resource devices, high computation cost resulting from the construction of Al models may limit their applications. To that end, this work explores gesture recognition through a low-cost capacitive sensor matrix overlayed on a rehabilitation activity table. For gesture recognition, a convolutional long short-term memory (C-LSTM) neural network structure is applied and hyper-parameters are varied to determine what resources are necessary to perform classification tasks. The 8 X 8 mutual capacitive sensor array (CSA) is constructed with low-cost copper adhesive. The designed capacitive sensors capture hand motions performed by patients during rehabilitative exercise. The motions cause changes in the electric field that is quantified through sampling the changing capacitance between the copper tape electrodes. An MSP430 MCU computes the capacitance-to-digital conversion at a 50 Hz sampling rate. To identify low computation cost models for the C-LSTM neural network, we evaluate different numbers of capacitor sensors, kernels, convolutional layers, and hidden nodes. Six subjects performed 1200 gestures, and the accuracy metrics are calculated using fivefold cross-validation.

关键词： capacitive sensor array CSA machine learning LSTM neural networks embedded systems rehabilitation

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Three-Dimensional Printing of a Flexible capacitive Pressure sensor array in the Assembly Network of Carbon Fiber Electrodes and Interlayer of a Porous Polyurethane Dielectric

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ACS APPLIED ELECTRONIC MATERIALS 2021年第9期3卷 3999-4008页

作者： Li, Ruiqing Dong, Ke Panahi-Sarmad, Mahyar Li, Siming Xiao, Xueliang Jiangnan Univ Key Lab Ecotext Minist Educ Wuxi 214122 Peoples R China

In this work, a facile three-dimensional (3D) printing of a one-piece flexible capacitive pressure sensor array is proposed with simple, economical, and scalable fabrication characteristics. The printed capacitive pressure sensor array is composed of continuous carbon fiber electrodes in the network and assembly of porous polyurethane dielectric. Also, the 3D printing way confers the fabrication with the advantage of time-saving by eliminating the assembly of electrodes and the dielectric layer. Salt microparticles were utilized as a kind of sacrificial material to embed micropores into the elastic dielectric layer of thermoplastic polyurethane, and a bundle of continuous carbon fibers extruded from the 3D printer nozzle was employed as the sensor electrodes. The formed one-point pressure sensor was constructed at the intersection by the cross-printing path of the upper and lower layers. The microporosity structure in the dielectric led to the sensor containing more compression amplitude, thus increasing the effective dielectric constant under pressure so that the sensor (5.15 N-1) with a 40% table salt content has a higher sensitivity than the unstructured sensor (0.32 N-1). Furthermore, the sensor exhibited a fast response/recovery time (60/80 ms), good stability (over 1000 cycles), and magnificent pressure resolution. Several one-point pressure sensors in the regular array were printed in one piece to be able to detect some distributed compression pressures. Thus, in the end, the sensor array was fixed to human joints such as fingers, knees, and elbows to collect limb motion signals and demonstrated potential application in the field of human motion detection.

关键词： 3D printing pressure sensor integrated molding carbon fibers capacitive sensor array pressure distribution detection wearable electronics polymer composites

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A novel silicon-based sensor array with capacitive EIS structures

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sensorS AND ACTUATORS B-CHEMICAL 1998年第1-3期47卷 225-230页

作者： Schoning, MJ Thust, M Muller-Veggian, M Kordos, P Luth, H Forschungszentrum Julich Inst Schicht & Ionentech D-52425 Julich Germany Fachhsch Aachen Abt Julich D-52428 Julich Germany

A modified C/V (capacitance/voltage) measuring set-up for the synchronous operation of several EIS (electrolyte- insulator-semiconductor) sensors was developed. Therewith, the simultaneous detection of different substances in aqueous analytes is possible by using capacitive sensors that can easily be manufactured. This novel method is exemplarily demonstrated for a sensor array based on a pH-sensitive EIS structure (Al/Si/SiO(2)/Si(3)N(4)) and a penicillin-sensitive EIS structure (Al/Si/SiO(2)/Si(3)N(4)/penicillinase). Both sensors are connected in parallel with each other. By using two additional d.c, voltage sources the single C/V curves are shifted against each other along the voltage axis. The resulting 'step-like' C/V curve allows the distinct assignment of each step fraction to the corresponding sensor, and thus the simultaneous detection of the pH and penicillin concentration in a single measurement. (C) 1998 Elsevier Science S.A. All rights reserved.

关键词： C/V measurement capacitive sensor array EIS structure penicillin pH

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Sectional void fraction measurement of gas-water two-phase flow by using a capacitive array sensor

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FLOW MEASUREMENT AND INSTRUMENTATION 2020年 74卷 101788-101788页

作者： Wang, Xiaoxin Chen, Yangzheng Wang, Bo Tang, Kaihao Hu, Hongli Xian Shiyou Univ Shaanxi Key Lab Measurement & Control Technol Oil Xian 710065 Shaanxi Peoples R China Xian Res Inst Co Ltd China Coal Technol & Engn Grp Corp Xian 710077 Peoples R China Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Peoples R China

The sectional void fraction measurement for multiphase flow is usually influenced by flow patterns. Inspired by electrical capacitance tomography (ECT) devices applied to flow imaging (whose measured capacitance data contain both the flow pattern and sectional void fraction information), a capacitive array sensor is developed to realize two functions, flow pattern recognition and void fraction measurement, simultaneously;so that the void fraction measurement can be conducted for a certain flow pattern and the measurement accuracy can be expected to be improved. The main idea of the proposed method can be described as: firstly, the proper feature vectors are extracted from the electrical signal to identify the flow pattern (the BPNN model with GDX learning algorithm is used for flow pattern identification);and then the average of electrical signal is applied to estimates the void fraction by the corresponding calibration curve. An experimental platform of air/water two-phase flow is built (on which 3 flow patterns can be generated stably) to test the performance of the proposed method. The results support the correctness and effectiveness of the proposed method.

关键词： Sectional void fraction measurement capacitive sensor array Flow pattern identification Gas-water two-phase flow

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High precision intelligent flexible grasping front-end with CMOS interface for robots application

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Science China(Information Sciences) 2016年第3期59卷 176-186页

作者： Xiaohui HU Xu ZHANG Ming LIU Yuanfang CHEN Peng LI Jialin LIU Zhaolin YAO Weihua PEI Chun ZHANG Hongda CHEN Institute of Semiconductors Academy of Sciences Institute of Microelectronics Tsinghua University

This paper presents a high-precision intelligent flexible robot grasping front-end with an integrated capacitive tactile sensor array and a conditioning chip. The capacitive tactile sensor is the primary part of the front-end, it determines the overall performance. The micro-needle array sandwich structure in the tactile sensor increases the repeatability and stability, and ensures the sensitivity. The assembled sensor exhibits a saturation at 10.53 N(421 k Pa) with a sensitivity of 1.9%/k Pa. Furthermore, a conditioning chip is utilized in a custom readout interface to achieve better performance by reducing signal attenuation, and to increase the compatibility of the front-end. The chip is optimized for the parasitic shunt capacitance in the capacitor array. A dual bidirectional charge-discharge conversion method and a two-port detection method are matched to achieve the goal of reducing the shunting influence, and attenuating the offset voltage or the noise input effects. A prototype of the interface has been fabricated using 180-nm CMOS technology. sensor with the value of 0.5 p F shunted by capacitors of 47 p F has been detected with an error of 1% within 100 μs.

关键词： capacitive sensor array flexible sensor tactile sensor micro-needle array bionic robot

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An FPGA-Based Upper-Limb Rehabilitation Device for Gesture Recognition and Motion Evaluation Using Multi-Task Recurrent Neural Networks

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IEEE sensorS JOURNAL 2022年第4期22卷 3605-3615页

作者： Liu, Haoyan Panahi, Atiyehsadat Andrews, David Nelson, Alexander Univ Arkansas Dept Comp Sci & Comp Engn Fayetteville AR 72703 USA

Upper-Extremity motor impairment affects millions of Americans due to cerebrovascular incidents, spinal cord injuries, or brain trauma. Current therapy practices used to assist these individuals in regaining motor functionality often require extensive time at rehabilitation facilities with potentially prohibitive travel or financial costs. This work presents a mobile low-cost field programmable gate array (FPGA)-smart rehabilitation system that can be used in home environments. The prototype is a rehabilitation table instrumented with a capacitive sensor array (CSA) to track upper-extremity motions of the user through proximity or touch. In addition, inertial measurement units (IMUs) are placed on the affected upper limb and combined with the CSA data with our sensor fusion signal processing architecture. Motions are classified and evaluated using multi-task convolutional recurrent neural networks with three additional motion quality output classes to personalize recognition based on the particular motor skills of each patient. The prototype achieves above 99% accuracy with 32-bit fixed-point format implementation for recognizing dynamic motions and identifying unnatural characteristics (i.e., tremor or limited flexion and extension) in upper limb motions based on sensor values. The convolutional recurrent neural network (C-RNN) fusion classification network is implemented on a 200 MHz Zynq ZCU104 FPGA using an HLS-based design optimized with pipelining and parallelism techniques and achieves 5.4x speedup compared to ARM (R) Cortex-A53 implementation running at an operating frequency of 1.3 GHz. The prototype is also demonstrated to perform the machine learning classification in real-time.

关键词： sensors capacitive sensors Field programmable gate arrays Gesture recognition Recurrent neural networks Multitasking Dynamics capacitive sensor array deep learning FPGA gesture recognition IMUs neural networks rehabilitation engineering

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Towards High Throughput Cell Growth Screening: A New CMOS 8 x 8 Biosensor array for Life Science Applications

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IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2017年第2期11卷 380-391页

作者： Nabovati, Ghazal Ghafar-Zadeh, Ebrahim Letourneau, Antoine Sawan, Mohamad Polytech Montreal Dept Elect Engn Polystim Neurotechnol Lab Montreal PQ H3T 1J4 Canada York Univ Dept Elect Engn & Comp Sci Toronto ON M3J 1P3 Canada

In this paper we present a CMOS capacitive sensor array as a compact and low-cost platform for high-throughput cell growth monitoring. The proposed biosensor, consists of an array of 8 x 8 CMOS fully differential charge-based capacitive measurement sensors. A DC-input Sigma Delta modulator is used to convert the sensors' signals to digital values for reading out the biological/chemical data and further signal processing. To compensate the mismatch variations between the current mirror transistors, a calibration circuitry is proposed which removes the output voltage offset with less than 8.2% error. We validate the chip functionality using various organic solvents with different dielectric constants. Moreover, we show the response of the chip to different concentrations of Polystyrene beads that have the same electrical properties as the living cells. The experimental results show that the chip allows the detection of a wide range of Polystyrene beads concentrations from as low as 10 beads/ml to 100 k beads/ml. In addition, we present the experimental results from H1299 (human lung carcinoma) cell line where we show that the chip successfully allows the detection of cell attachment and growth over capacitive electrodes in a 30 h measurement time and the results are in consistency with the standard cell-based assays. The capability of proposed device for label-free and real-time detection of cell growth with very high sensitivity opens up the important opportunity for utilizing the device in rapid screening of living cells.

关键词： capacitive sensor array cell growth monitoring CMOS high-throughput screening

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An 8.2-μW 0.14-mm² 16-Channel CDMA-Like Capacitance-to-Digital Converter

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2020年第5期55卷 1361-1373页

作者： Luo, Yuxuan Li, Yida Thean, Aaron Voon-Yew Heng, Chun-Huat Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore

This article presents a multi-channel capacitance-todigital converter (CDC) circuits using the continuous-time Walsh coding multiplexing. The proposed circuits modulate the input capacitive sensors with orthogonal codes, enable simultaneous read-in of 16 capacitive sensors, and provide the combined 16 digitized outputs in a single conversion. By correlating 16 successive digitized outputs with the corresponding orthogonal codes in post-processing, the 16 capacitive channels can then be demodulated separately. The proposed continuous-time Walsh coding modulation preserves temporal information with minimum circuitry duplication and bandwidth requirement. This chip is fabricated in 130-nm CMOS technology and occupies an area of 0.14 mm2. With a reference clock of 4 MHz, the proposed multi-channel CDC achieves 11.4 ENOB with an average conversion time of 482 mu s. It consumes 0.51 mu W/channel and achieves an FoM of 87 fJ/conversion step.

关键词： Capacitance-to-digital converter (CDC) capacitive sensor array electronic skin (e-skin) multi-channel sensor interface circuits pressure sensors

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A 70-μW 1.35-mm² Wireless sensor With 32 Channels of Resistive and capacitive sensors and Edge-Encoded PWM UWB Transceiver

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2021年第7期56卷 2065-2076页

作者： Luo, Yuxuan Li, Yida Thean, Aaron Voon-Yew Heng, Chun-Huat Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore Zhejiang Univ Sch Micronanoelect Inst VLSI Design Hangzhou 310027 Peoples R China Southern Univ Sci & Technol Sch Microelect Shenzhen 518055 Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

This article presents a wireless multi-channel sensor interface circuit for emerging e-skin applications. The proposed interface circuit uses a CDMA-like sensing method to simultaneously record 16-channel resistive sensors and 16-channel capacitive sensors. The code-modulated multi-channel signals are conditioned and wirelessly transmitted through an edge-encoded pulsewidth-modulation ultra-wideband (PWM UWB) transmitter in the time domain. The PWM UWB transmitter eliminates the need for digitization on the sensor node, reducing the number of data to be sent. This improves the sensing and wireless transmission efficiency. With the proposed edge-encoding technique, the PWM UWB transmitter can recover the sensor data with SNR above 70 dB despite 20% data loss under a lossy environment. Fabricated in 130-nm technology, the wireless multi-channel sensor node occupies a die area of 1.35 mm(2) and consumes a power of 70 mu W. It achieves an energy efficiency of 0.87 pJ/Conversion-step per channel.

关键词： Pulse width modulation Wireless communication Wireless sensor networks sensor arrays Capacitance Capacitors capacitive sensor array electronic-skin multi-channel sensor interface circuits proximity sensor PWM UWB resistive sensor array temperature sensor

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