Capacitive Sensor Array Research Articles

Printed, wearable e-skin force sensor array

The need to develop electronic skin (e-skin) for robotics is essential to provide a sense of touch on a large area, the same as human skin. This paper reports the design and development of printed e-skin force sensor arrays. The performance analysis of these capacitive force sensor arrays showed a resolution of 2.5 sq. mm, localization accuracy of 99% and a sensitivity of 0.53 pF/N. The sensor patches provided significant force sensitivity and stable loading and unloading for static force. A graphical user interface is developed in open-source python software. An unsupervised machine learning algorithm trains the tactile e-skin system for different user styles to distinguish the cluster of lower and higher touch angles for improving accuracy. The proposed e-skin sensor finds application in large-area sensors and gripper pads for prosthetics in biomedical devices where the sense of touch and high resolution is needed.

Flexible capacitive pressure sensor array using acoustic-assisted fabrication of microstructures as surface and dielectric layers

Flexible pressure sensors have attracted considerable interests in the fields of intelligent robotics, human-machine interfaces and health monitoring for their portability, flexibility and real-time sensing performance. The microstructures of dielectric layer significantly affect the sensing performance of capacitive pressure sensors, but the common methods to fabricate microstructures always need physical and/or chemical molds, thus may not suit for low-cost fabrication of sensors. The wavy-shaped microstructures on the surface of fluid can be generated with the excitation of standing surface acoustic waves (SSAWs), which is suitable to be used as dielectric layers. Here, we developed a 6 × 6 flexible capacitive pressure sensor array with fingerprint-like surface cover layer and latticed dielectric layer. Both two layers were fabricated through the novel and rapid acoustic-assisted process. The fabricated capacitive sensor array exhibits high sensitivity of 28.8%/N for normal force loading, with spatial resolution of 1.5 mm. It has been successfully used to monitor the vibration of the Adam’s apple during swallowing and detecting the wrist activities in cycles. These studies demonstrate the great potential of the pressure sensor array with acoustically fabricated microstructures in wearable electronics for health monitoring. • A novel flexible pressure sensor array with spatial resolution of 1.5 mm for three-axis distributed force sensing is developed. • A novel and rapid acoustic-assisted process based on SSAWs is used to fabricate the surface layer and dielectric layer with microstructures. • The tactile sensor array features high flexibility and can be easily worn on neck or wrist for health monitoring. • Both Adam’s apple vibration sensing and wrist activity detection can be achieved by the developed tactile sensor array.

A High Dynamic Range Dual 8×16 Capacitive Sensor Array for Life Science Applications.

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 × 16 interdigitated electrodes (IDEs) integrated with a charge-based readout and multiplexing circuitries on the same chip. This chip was implemented in 0.35 µm 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.

Speed and location tracking of moving multiphase interfaces via a capacitance microsensor array during droplet evaporation

Knowledge of the location and speed of a moving multiphase contact line provides significant and valuable insight into the fundamental physics behind condensation- and evaporation- based processes such as occur in high heat flux thermal management solutions. From an application perspective, this information can be leveraged to ascertain and enhance device design and performance of phase change-based cooling processes. In this work, we present a capacitance-based phase interface sensing approach capable of measuring the location and speed of a moving multi-phase interface at the microscale, evaluate the impact of substrate material on its performance, and demonstrate its ability to function at elevated temperatures during water droplet evaporation. The sensing is accomplished via an array of planar interdigitated electrodes upon either a doped semiconductor or dielectric substrate. Measuring capacitance changes with time facilitates sensing of the contact line as it passes over each electrode pair. This capacitive sensing scheme is noninvasive to the system under study, allowing its implementation into many types of existing hardware and devices and does not require optical access to the phase change area of the device. Results for unconstrained water droplets are presented, and it is shown that the choice of substrate material has a marked impact on sensing behavior in terms of sensor coupling. Finally, data for the moving multiphase contact line of an evaporating water droplet is presented to demonstrate functionality at elevated temperatures and during a dynamic heat transfer process. • Tracking moving contact lines for droplet evaporation via a capacitance sensor array. • Speed and position of moving interfaces able to be measured at elevated temperatures. • Comparison of capacitive microdevice performance and its dependence on substrate type. • Dielectric substrate enables increased signal outputs and reduced coupling effects.

Bioinspired Spinosum Capacitive Pressure Sensor Based on CNT/PDMS Nanocomposites for Broad Range and High Sensitivity.

Flexible pressure sensors have garnered much attention recently owing to their prospective applications in fields such as structural health monitoring. Capacitive pressure sensors have been extensively researched due to their exceptional features, such as a simple structure, strong repeatability, minimal loss and temperature independence. Inspired by the skin epidermis, we report a high-sensitivity flexible capacitive pressure sensor with a broad detection range comprising a bioinspired spinosum dielectric layer. Using an abrasive paper template, the bioinspired spinosum was fabricated using carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites. It was observed that nanocomposites comprising 1 wt% CNTs had excellent sensing properties. These capacitive pressure sensors allowed them to function at a wider pressure range (~500 kPa) while maintaining sensitivity (0.25 kPa−1) in the range of 0–50 kPa, a quick response time of approximately 20 ms and a high stability even after 10,000 loading–unloading cycles. Finally, a capacitive pressure sensor array was created to detect the deformation of tires, which provides a fresh approach to achieving intelligent tires.

High-sensitivity flexible tri-axial capacitive tactile sensor for object grab sensing

In this paper, a high sensitivity, flexible capacitive tri-axial tactile sensor is constructed by pyramid-shaped microarray dielectric layer. The tactile sensor consists of a staggered 2 × 2 capacitive sensor array. Through the measure and analysis of the three-dimensional force, which was applied on the sensor, it could decompose into normal and shear force components. The sensor exhibits high sensitivity due to the pyramidal-shaped microarray and low modulus of the dielectric layer. The sensitivity of the sensor in the x,y and z-axis are 56.47, 53.45 and 90.39 %/N in the ranges of 0 ∼ 0.8, 0 ∼ 0.8 and 0 ∼ 0.6 N, respectively. In addition, the sensor also exhibits fast response and recovery times (60 ms), and longtime cycling stability. The low average test error (about 10.4 %) of the tri-axial tactile sensor provides the technical basis for the application of robotics and wearable devices.

Design and Characterization of a CMOS Capacitive Sensor Array for Fast Normal Stress Analysis

This letter presents a dense 32 &#x00D7; 32 sensor array integrated in a complementary metal oxide semiconductor process for fast and sensitive detection of contact forces with fine spatial resolution. The sensing membranes made of metal and oxide thin films with a total thickness of 1.9 <i>&#x03BC;</i>m are released by wet etch of metal layers. Each sensing pixel is 140 &#x00D7; 140 <i>&#x03BC;</i>m² in size, leading to an array size of 4.8 &#x00D7; 2.4 mm². The simulated sensing and parasitic capacitance of 63 and 231 fF, respectively, are very close to the measured data. The array exhibited a capacitive sensitivity of 5.8 fF&#x002F;kPa and an output change of 19.2 mV&#x002F;kPa based on an integration time of 0.125 <i>&#x03BC;</i>s. This letter successfully demonstrated dynamic stress measurements with a maximum frame rate up to 1.8 kHz.

A Capacitive and Piezoresistive Hybrid Sensor for Long‐Distance Proximity and Wide‐Range Force Detection in Human–Robot Collaboration

Electronic Skins Safety is a core concern in human-robot collaboration (HRC), and the active safety control has attracted widespread attention. A capacitive and piezoresistive hybrid sensor array (e-skins) for longdistance proximity and wide-range force detection is presented in article 2100213 by Zhenlong Wang, Jie Zhao, PingAn Hu, Jia Zhang and co-workers. The performance for controlling commercial robots in HRC shows the potential usages in complex conditions.

All-Fabric-Based Flexible Capacitive Sensors with Pressure Detection and Non-Contact Instruction Capability

The flexible and wearable capacitive sensors have captured tremendous interest due to their enormous potential for healthcare monitoring, soft robotics, and human−computer interface. However, despite recent progress, there are still pressing challenges to develop a fully integrated textile sensor array with good comfort, high sensitivity, multisensing capabilities, and ultra-light detection. Here, we demonstrate a pressure and non-contact bimodal fabric-only capacitive sensor with highly sensitive and ultralight detection. The graphene nanoplatelets-decorated multidimensional honeycomb fabric and nickel-plated woven fabric serve as the dielectric layer and electrode, respectively. Our textile-only capacitive bimodal sensor exhibits an excellent pressure-sensing sensitivity of 0.38 kPa−1, an ultralow detection limit (1.23 Pa), and cycling stability. Moreover, the sensor exhibits superior non-contact detection performance with a detection distance of 15 cm and a maximum relative capacitance change of 10%. The sensor can successfully detect human motion, such as finger bending, saliva swallowing, etc. Furthermore, a 4 × 4 (16 units) textile-only capacitive bimodal sensor array was prepared and has excellent spatial resolution and response performance, showing great potential for the wearable applications.

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

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&#x0025; 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&#x00AE; 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.

An improved BP neural network‐based calibration method for the capacitive flexible three‐axis tactile sensor array

Flexible tactile sensing based on capacitive sensing has become a research hotspot in recent years because of its low energy consumption, high performance and wide application prospects. However, the axis error caused by the coupling deformation of the dielectric will seriously affect the accuracy of the sensor. In this paper, a capacitive flexible three-axis tactile sensor array is modelled and simulated, and a neural network-based calibrator for the three-axis sensor array is proposed, which can be used to calibrate the simulated measurement data. The simulation results show that even though the correlation coefficient of linear regression for each axis is very close to 1, the effect of dielectric nonlinear coupling distortion cannot be eliminated. The calibration method based on the neural network can effectively suppress the nonlinear coupling distortion of the dielectric, and reduce the measurement coupling rate of the sensor model from 26% to 1%. At the same time, in order to ensure the measurement accuracy and robustness of different units in the sensor array, the input layer of the calibrator is expanded, and the data set containing capacitance information and two-dimensional location information is used for training. The experimental results show that the proposed calibration method combining two-dimensional position information training accurately calibrates the capacitive flexible three-dimensional tactile sensor array.

Optimization of All-Textile Capacitive Sensor Array for Smart Chair

All-textile capacitive sensor arrays made of a polyurethane foam, fabric and electrically-conducting yarn were fabricated for a ‘smart chair’. Polyurethane foam slab that functioned as a dielectric medium was encased between two pieces of commercially available fabric. The electrically-conducting yarn was used to embroider the capacitor electrodes on both fabric pieces. The completed sensor arrays were investigated under normal compressive load with the targeted pressure range of 2 to 30 kPa for the chair seat and 2 to 8 kPa for the backrest. The sensor capacitance versus normal compressive load exhibited a load/unload hysteresis for all sensor arrays. The hysteresis was modelled with sigmoid function and much narrower hysteresis was observed when all sensors were loaded simultaneously, as opposed to their individual loading, allowing development of a phenomenological model for the former. Among the studied sensor arrays, the array with dimensions of 30 cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 30$ </tex-math></inline-formula> cm made of a 10-mm-thick polyurethane foam with density of ~18.6 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> was the most suitable for the following reasons: (a) unloaded sensor capacitance was ~2.7 pF, (b) the sensor location did not affect its response, (c) ~10 kg load applied across individual sensor raised its capacitance by ~12 pF, and (d) 60 kg load applied uniformly across the whole sensor array increased the capacitance by ~5 pF. During the compression of the individual sensors the top fabric affected the sensor’s electro-mechanical response and elastic fabric would be favored for applications with non-uniform pressure distribution.

Curing quality monitoring and loading detection of composite structures with embedded capacitive sensor array

Structural health monitoring of composite structures from manufacturing to operation is receiving significant attention to ensure their performance and safety. In this paper, capacitive sensor arrays were designed and embedded between adhesively bonded composite laminates for curing quality monitoring during manufacturing and loading detection in operation. A loading inversion method was proposed to quantitatively determine the loading location and value on composite structure. The results showed that the whole curing process of adhesive bonding was successfully monitored. Based on capacitance monitoring, the embedded sensors can capture poor curing quality of adhesively bonded composite laminates due to abnormal curing conditions. The embedded sensors between composite laminates after curing showed perception of external loading. With the evenly distributed sensing capacitors, loading applications on composite laminates were detected. Based on the proposed loading inversion method, loading distribution mapping on the composite laminates was constructed, and the quantitative calculation of the coordinate location and value of loading was achieved. The calculated results agreed well with the actual loading in experiments, affirming the feasibility of the capacitive sensor array and the loading inversion method.

Multifunctional Electronic Skin With a Stack of Temperature and Pressure Sensor Arrays

This paper presents multifunctional electronic skin (e-Skin) with a stack of pressure and temperature sensors arrays. The pressure sensor layer comprises of an 8x 8 array of capacitive sensors using soft elastomers as the dielectric medium and the temperature sensing layer comprises of 4 x4 array of conductive polymers based resistive sensors. Three variants of capacitive pressure sensors were developed using two different dielectric materials (PDMS and Ecoflex) to find the best combination of performance and softness. The Ecoflex-based pressure sensor showed high sensitivity (~4.11 kPa-1) at a low-pressure regime ( 1 kPa). Two variants of temperature sensors were fabricated using CNT and CNT & PEDOT:PSS conducting polymer composite and their performance compared. Finally, a highly sensitive CNT+PEDOT:PSS based resistive temperature sensors layer was integrated on top of 7.5:1 PDMS based capacitive pressure sensors layer to realize the e-Skin prototype. The developed e-Skin is capable of sensing pressures greater than 10 kPa with a high sensitivity of ~2.32 kPa-1 at 1 kPa and temperatures with the sensitivity of ~ 0.64 (%)/(°C) up to 80°C, thus demonstrating high potential for use in robotics and touch based interactive systems.

Three-Axis Capacitive Sensor Arrays for Local and Global Shear Force Detection

We report the real time characterization and measurement results of a new tri-axial capacitive sensing array. Each unit cell of the Kapton based sensor has an overlapping electrode geometry that allows for the measurement of normal and shear force magnitudes, and the estimation of the 2D and 3D angle of the shear force. The use of a patterned Ecoflex dielectric layer further improves the shear force response and the tunability of the sensor. A custom readout circuit was developed to selectively read the differential capacitances in the sensor array. The local (unit cell) and global (array) force response of the sensor was characterized using a tilt stage, allowing us to determine both the normal and the shear response at different angles in the range of 0-20N. The results show that the Unit Cell response is uniform in the linear range of 0-10N for normal forces (4.6fF/N for all four differential capacitances) and shows good sensitivity for shear forces (1.4 fF/N difference between the right and left differential capacitances at the minimum) and low cross talk. Similar results were seen when a global force was applied across the sensor array. 2D and 3D models were developed to extrapolate the shear force angle from the capacitance data. We also characterized the flexible patterned dielectric layer to understand the effect of its structural dimensions on the effective relative permittivity and developed an analytical model to easily calculate the effective relative permittivity, which showed excellent correlation with the experimentally obtained results. [2020-0382]

Detection of foodborne pathogens using novel vertical capacitive sensors

Food poisoning, infection of open wounds, and sepsis are the serious clinical consequences that pathogens can cause. Rapid identification of these pathogens allows prompt monitoring of infections, which improves clinical outcomes. An integrated platform is proposed to manipulate and identify the microorganisms (e.g., foodborne pathogens) in this work. An electrokinetic-based Actuator and capacitive-based sensor are the two primary components of the proposed platform. Dielectrophoresis-based microelectrode is proposed to manipulate the microorganisms. A novel vertical array of capacitive sensors is suggested To identify the levitated microorganisms. The mass of microorganisms can be extracted according to the applied dielectrophoretic force respecting the gravitational force. The whole platform is simulated using 2D numerical simulation, COMSOL Multiphysics, to evaluate design efficiency. Furthermore, the proposed platform is developed and experimentally evaluated using the most common food bacterium type (Escherichia coli (E. coli)). The practical prototype is implemented using cheap technology (rigid and flexible printed circuit board technology). Experiments demonstrated that the proposed biochip could identify E. coli without the need of complex and expensive tools and with a simple manufacturing method.

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

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

Programmable robotized ‘transfer-and-jet’ printing for large, 3D curved electronics on complex surfaces

Large, 3D curved electronics are a trend of the microelectronic industry due to their unique ability to conformally coexist with complex surfaces while retaining the electronic functions of 2D planar integrated circuit technologies. However, these curved electronics present great challenges to the fabrication processes. Here, we propose a reconfigurable, mask-free, conformal fabrication strategy with a robot-like system, called robotized ‘transfer-and-jet’ printing, to assemble diverse electronic devices on complex surfaces. This novel method is a ground-breaking advance with the unique capability to integrate rigid chips, flexible electronics, and conformal circuits on complex surfaces. Critically, each process, including transfer printing, inkjet printing, and plasma treating, are mask-free, digitalized, and programmable. The robotization techniques, including measurement, surface reconstruction and localization, and path programming, break through the fundamental constraints of 2D planar microfabrication in the context of geometric shape and size. The transfer printing begins with the laser lift-off of rigid chips or flexible electronics from donor substrates, which are then transferred onto a curved surface via a dexterous robotic palm. Then the robotic electrohydrodynamic printing directly writes submicrometer structures on the curved surface. Their permutation and combination allow versatile conformal microfabrication. Finally, robotized hybrid printing is utilized to successfully fabricate a conformal heater and antenna on a spherical surface and a flexible smart sensing skin on a winged model, where the curved circuit, flexible capacitive and piezoelectric sensor arrays, and rigid digital–analog conversion chips are assembled. Robotized hybrid printing is an innovative printing technology, enabling additive, noncontact and digital microfabrication for 3D curved electronics.

Oil property sensing array based on a general regression neural network

Online monitoring of multiple lubricant properties is critical in maintaining and extending the health of high-speed rotating and reciprocating machinery used in many of the nation’s key industries including aerospace, manufacturing, and energy. There have been many efforts on the development of sensors focused on measuring specific chemical/physical properties of lubricant oil. One long-standing challenge for these property sensors is the overlapping output problem (cross-sensitivity), meaning they cannot provide accurate measurements. Here we demonstrated a capacitive oil property sensor array based on a new general regression neural network (GRNN) for measuring acid, base, and water content in lubricant oil. Results showed that the GRNN can pinpoint individual oil properties from the overlapped sensor array’s responses with high accuracy and speed.

P‐5: New Capacitive Active‐Pixel Sensor Based on LTPS‐TFT Backplane Technology for Fingerprint Recognition

We report a new type of capacitive active pixel sensor based on LTPS TFT backplane technology. It is a pixel design method for image sensors, which combines amplifiers and capacitors to form a pixel unit. Each pixel contains three transistors. This structure includes a capacitor as a sensing element, a reset transistor RST (T3), a row selector RS (T1), and a signal amplifier SF (T2). The advantage is to amplify the signal before reading, which is effective reduce the influence of noise and interference sources, so as to achieve high image quality. Based on the new capacitive active pixel sensor, a capacitive fingerprint sensor array was realized and the fingerprint image was successfully captured.