Flexible Sensor Array Research Articles

Flexible Sensors Array Based on Frosted Microstructured Ecoflex Film and TPU Nanofibers for Epidermal Pulse Wave Monitoring

Recent advances in flexible pressure sensors have fueled increasing attention as promising technologies with which to realize human epidermal pulse wave monitoring for the early diagnosis and prevention of cardiovascular diseases. However, strict requirements of a single sensor on the arterial position make it difficult to meet the practical application scenarios. Herein, based on three single-electrode sensors with small area, a 3 × 1 flexible pressure sensor array was developed to enable measurement of epidermal pulse waves at different local positions of radial artery. The designed single sensor holds an area of 6 × 6 mm2, which mainly consists of frosted microstructured Ecoflex film and thermoplastic polyurethane (TPU) nanofibers. The Ecoflex film was formed by spinning Ecoflex solution onto a sandpaper surface. Micropatterned TPU nanofibers were prepared on a fluorinated ethylene propylene (FEP) film surface using the electrospinning method. The combination of frosted microstructure and nanofibers provides an increase in the contact separation of the tribopair, which is of great benefit for improving sensor performance. Due to this structure design, the single small-area sensor was characterized by pressure sensitivity of 0.14 V/kPa, a response time of 22 ms, a wide frequency band ranging from 1 to 23 Hz, and stability up to 7000 cycles. Given this output performance, the fabricated sensor can detect subtle physiological signals (e.g., respiration, ballistocardiogram, and heartbeat) and body movement. More importantly, the sensor can be utilized in capturing human epidermal pulse waves with rich details, and the consistency of each cycle in the same measurement is as high as 0.9987. The 3 × 1 flexible sensor array is employed to acquire pulse waves at different local positions of the radial artery. In addition, the time domain parameters including pulse wave transmission time (PTT) and pulse wave velocity (PWV) can be obtained successfully, which holds promising potential in pulse-based cardiovascular system status monitoring.

3: A Machine Haptic System based on a Flexible Tactile Sensor Array Enabling Material Classification and Texture Recognition

Human haptic systems such as hand and skin are capable of material classification and texture recognition with a slight training effort where the mechanoreceptor first collects the tactile information, secondly, the nerves and neurons deliver the message and finally, the somatosensory cortex in the brain computes and makes a decision. In this work, we attempt to build a machine haptic system to mimic functions of skin and nervous system for material classification and recognition.

20.1: Invited Paper: Research on Oxide Thin Film Transistors for Wearable Sensors

With the rapid development of the Internet of Things, sensors as an important foundation in the era of smart interconnection, have a significant potential in the emerging fields of smart home, wearable devices, and smart mobile terminals. Flexible sensor has been attracting a great attention due to its portability, miniaturization and long endurance. The high consumption and signal crosstalk are urgent issues for the high‐integration sensing array. These issues could be effectively addressed by active‐matrix thin film transistors (TFT) backplane. In this work, the feasibility of oxide TFT for flexible sensor was discussed, in which high‐quality oxi de semiconductor films, oxide dielectric films, and printing Ag electrodes and wires were investigated, respectively. The device performance of flexible Si‐doped SnO2 TFT was optimized by modulating oxygen partial pressure, which could achieve a relative good electrical properties at room temperature. To implement low‐consumption application, high quality of high‐k ZrO2 dielectric film was investigated by solution‐processed method. The dielectric properties of ZrO2 film with the mircowave‐as sisted or deep ultraviolet irradiation‐assisted annealing process was similar to that of the thermal ann ealing process. The morphology and conductivity of Ag electrodes and wires printed by electrohydrodynamic (EHD) inkjet printing technology were studied. High conductivity of Ag electrodes and wires was achieved at a low curing temperature. These results imply that oxide TFT has a significant potential in the application of flexible sensor array.

A triboelectric nanogenerator-based tactile sensor array system for monitoring pressure distribution inside prosthetic limb

In the prosthetic field, quantifying interfacial pressure distribution between the amputee's residual limb and the socket’s internal environment is imperative for developing new technologies. However, the commercially available pressure sensors have several disadvantages, namely external power supply requirements, low stability, high cost, and complexities related to integrating the sensor system into prosthetic devices. Herein, we propose a self-powered triboelectric nanogenerator (TENG) based flexible tactile sensor array system to monitor prosthetic socket internal pressure distribution in real-time. The proposed sensor consists of biocompatible polydimethylsiloxane (PDMS) polymer and polycaprolactone (PCL) nanofiber membranes as triboelectric materials. The biodegradable PCL nanofiber membrane, fabricated via a scalable and cost-effective electrospinning process, possesses a high surface area-to-volume ratio, facilitating enhanced charge generation during triboelectrification. The as-fabricated TENG-based tactile sensor is highly stable up to 10,000 cycles. Furthermore, the voltage of the tactile sensor is independent of different temperature and humidity values, demonstrating the stability of the sensor under various environmental conditions. Finally, we successfully integrated the tactile sensor array within a prosthetic device to monitor real-time pressure distribution inside the prosthetic socket during gait simulation. We believe that the proposed novel design provides a new dimension for the rapid development of self-powered, low-cost, and highly stable pressure monitoring systems with considerable potential for commercialization.

High-Density Flexible Piezoelectric Sensor Array With Double Working Modes

Flexible and self-powered sensing device has aroused considerable interest in the field of the Internet of Things (IoT) and artificial intelligence (AI) in recent years. For more detailed and sensitive perception of the surroundings and external stimuli, sensors with high density and sensitivity are highly desirable. Here, this article reported a simple and low-cost strategy to realize a high-performance flexible piezoelectric sensor array composed of 30 sensing points with a high density of 11.11 cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-{2}}$ </tex-math></inline-formula> . The piezoelectric sensor array was analyzed by a finite-element model and characterized through sound pressure measurement and wrist bending for motion monitoring under <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${d}_{{33}}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${d}_{{31}}$ </tex-math></inline-formula> modes, respectively. The flexible sensor array with the total thickness of 125 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> exhibits a high sensitivity of 447.82 mV <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\cdot $ </tex-math></inline-formula> kPa <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-{1}}$ </tex-math></inline-formula> with an ultralow detection limit of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 3.60$ </tex-math></inline-formula> Pa. Our work provides a simple strategy for the application potential in smart wearable electronics and human–machine interaction (HMI) areas.

Hardness-and-Type Recognition of Different Objects Based on a Novel Porous Graphene Flexible Tactile Sensor Array.

Accurately recognizing the hardness and type of different objects by tactile sensors is of great significance in human-machine interaction. In this paper, a novel porous graphene flexible tactile sensor array with great performance is designed and fabricated, and it is mounted on a two-finger mechanical actuator. This is used to detect various tactile sequence features from different objects by slightly squeezing them by 2 mm. A Residual Network (ResNet) model, with excellent adaptivity and feature extraction ability, is constructed to realize the recognition of 4 hardness categories and 12 object types, based on the tactile time sequence signals collected by the novel sensor array; the average accuracies of hardness and type recognition are 100% and 99.7%, respectively. To further verify the classification ability of the ResNet model for the tactile feature information detected by the sensor array, the Multilayer Perceptron (MLP), LeNet, Multi-Channel Deep Convolutional Neural Network (MCDCNN), and ENCODER models are built based on the same dataset used for the ResNet model. The average recognition accuracies of the 4hardness categories, based on those four models, are 93.6%, 98.3%, 93.3%, and 98.1%. Meanwhile, the average recognition accuracies of the 12 object types, based on the four models, are 94.7%, 98.9%, 85.0%, and 96.4%. All of the results demonstrate that the novel porous graphene tactile sensor array has excellent perceptual performance and the ResNet model can very effectively and precisely complete the hardness and type recognition of objects for the flexible tactile sensor array.

Droplet-Dispensed Graphene Oxide as Capacitive Sensing Elements for Flexible Pressure-Pulse Sensing Array

We report a novel flexible capacitive pressure-pulse sensor array developed by integrating droplet-dispensed graphene oxide (GO) sensing elements and flexible electronics. The utilization of droplet-dispensing technology enables the fabrication multiple capacitive sensing elements rapidly while producing sensitive pressure sensors with excellent repeatability. The dispensed droplet volume (GO aqueous dispersion) ranged from around 33.5 to 65.4 pL with diameter ranging from 40 to 50 μm. The size (i.e., footprint and dielectric material thickness) of a sensing element can be controlled by the total GO dispersed per droplet. The fabrication process and preliminary characterization of these GO capacitive sensors are discussed in this paper. Thus far, we have shown that these sensors have a sensitivity of ∼10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> kPa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> , with the relative permittivity of the dispensed GO being ∼6 (measured at a frequency of 600 kHz). We have also demonstrated that the printed sensing elements can be used for human wrist pulse sensing. Hence the technology described in this paper could potentially be used in wearable electronics for healthcare applications.

Smart Glove Human-Machine Interface Based on Strain Sensors Array for Control UAV

Smart gloves have attracted much attention as a typical representative of wearable human-machine interface (HMI). Traditional sensors on smart gloves are limited due to high cost, complex manufacture, which can’t meet the requirements of bio-friendliness and sustainability. This paper presents a smart glove human-machine interface based on strain sensor array of conductive hydrogels. A flexible, transparent, stretchable and sensitive hydrogel strain sensor is prepared based on a “one-pot” preparation method. The smart glove was constructed using 3D structural design combined with the sensor array. Combing with the signal processing system, the smart glove can realize the spatial motion control of the Unmanned Aerial Vehicle (UAV). The smart glove based on the hydrogel flexible sensor array showed great application prospects in the field of human-machine interaction of robot and Virtual Reality (VR).

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.

All Digital Light Processing‐3D Printing of Flexible Sensor

AbstractFlexible sensor with high sensitivity, high durability, and facile fabrication process has promising applications in structural health monitoring, human–machine interface, and soft robotics areas. Digital light processing‐3D (DLP‐3D) printing can print flexible sensor in a scalable process. However, to achieve all DLP‐3D printing of flexible sensor, there still exist challenges of how to print sensing units with high sensitivity to external stimuli, interconnectors with high conductive stability at deformations, and robust interfaces between them for long‐term usage. To address this, a hybrid DLP‐3D printing method is developed, including the key steps of printing carbon nanotube/elastomer (MWCNT/EA) as sensing units and selective electrostatic self‐assembly of silver nanowires (Ag NWs) as interconnectors. As a demonstration, a flexible pressure sensor array integrated with amplifier circuit is fabricated by the method. The MWCNT/EA sensing unit with woodpile structure has nine times improved sensitivity than the solid one. The Ag NW interconnector with serpentine configuration shows insensitivity to strain and good mechanical stability. The interface between sensing unit and interconnector is mechanical robust due to the chemical bond formation under ultraviolet radiation. The flexible sensor could detect external stimuli with enhanced signals enabled by integrated amplifier circuit, exhibiting potentials of the method for flexible electronic fabrication.

Matrix-addressed crosstalk-free self-powered pressure sensor array based on electrospun isolated PVDF-TrFE cells

Flexible pressure sensor array has attracted much attention in wearable electronics, but still lacks self-power, high resolution, large-area fabrication, and low crosstalk. Herein, we present a self-powered pressure sensor array via patterned piezoelectric polyvinylidene fluoride-trifluoroethylene (PVDF-TrFE) nanofibrous. The PVDF-TrFE nanofibers were collected by patterned metal ground electrodes that isolated each piezoelectric cell. The isolated sensing cells can effectively reduce the crosstalk caused by additional deformation. The potential from individual cell is detected through the row+column electrode configuration to determine the corresponding pressure point and trajectory information. The as-fabricated pressure sensor array showed an excellent linear piezoelectric response (2.5 mV/kPa), a fast response time (5 ms), and good repeatability (25,000 cycles). Furthermore, our piezoelectric devices with constructed PVDF-TrFE layer are feasible in scaling up to a large-area sensor array. Accurate recognitions of the letter "h" trajectory tracking and tactile sensation by our self-powered tactile sensor array show potential applications in electronic skin and artificial intelligence. • The piezoelectric sensor array with isolated PVDF-TrFE cell is constructed to cancel out the voltage crosstalk. • The electrospinning is a versatile and low-cost method to produce self-patterned and polarized nanofibers. • The accurate trajectory recognition based on our sensor array is successfully demonstrated.

Real-Time and Cost-Effective Smart Mat System Based on Frequency Channel Selection for Sleep Posture Recognition in IoMT

Sleep posture, which affects the quality of sleep and could lead to medical conditions, such as pressure ulcers, is a key metric for sleep analysis in Internet of Medical Things (IoMT). In this article, a real-time and low-cost smart mat system for sleep posture recognition based on frequency channel selection is proposed. The system can recognize postures unobtrusively with a dense flexible sensor array. In addition, to enable real-time recognition with a relatively low-cost STM32 processor system, a lightweight algorithm that includes frequency channel selection, model pretraining, and real-time classification is proposed. Through a series of short-term and overnight experiments with 21 subjects, the feasibility and reliability of the proposed system were evaluated. Experimental results show that the accuracy of the short-term experiment is up to 95.43% and of the overnight experiment is up to 86.80% for four posture categories (supine, prone, right, and left) classification. The model size is just 56 kB which is much smaller than other methods. The runtime of the complete algorithm is about 6 ms with a low-power STM32 embedded system, which shows the system’s ability to provide real-time posture recognition. As an edge device, the proposed system could lead to the development of fast, convenient, and low-cost sleep posture recognition products for IoMT.

Flexible Ring Sensor Array and Machine Learning Model for the Early Blood Leakage Detection during Dialysis

Severe blood leakage resulting from the detachment of dialysis tubing is often difficult to detect by nurses in busy clinics. This paper presents a flexible blood leakage detection system featuring a ring-light sensor array with an operating wavelength of 500–700 nm, which is held in place by the gauze covering the dialysis puncture site. A ring-light sensor is connected to a bidirectional hetero-associative memory network, which interprets detected changes in signal strength, the output signal of which is transmitted via WiFi to a server at the nursing station where a machine learning algorithm determines whether blood leakage has occurred. The compact design of this early warning system greatly enhances the comfort and mobility of patients undergoing dialysis. The efficacy of the proposed system was demonstrated in experiments involving artificial blood.

Triboelectric Pressure Sensors Using Laser-Directed Synthesis of Strain-Induced Crumpled MoS2

Two-dimensional (2D) transition metal dichalcogenide (TMDC) nanomaterials are currently regarded as next generation electronic materials for future flexible, transparent, and wearable electronics. Due to the lack of compatible synthesis and study, however, the characteristic influences of 2D TMDC nanomaterials have been little investigated in the field of triboelectric nanogenerator (TENG) devices that are currently one of the main technologies for mechanical energy harvesting. In this report, we demonstrate a fast, non-vacuum, wafer-scale, and patternable synthesis method for 2D MoS2 using pulsed laser-directed thermolysis. The laser-based synthesis technique that we have developed can apply internal stress to MoS2 crystal by adjusting its morphological structure, so that a surface-crumpled MoS2 TENG device generates ~40% more power than a flat MoS2 one. Compared to other MoS2-based TENG devices, it shows high-performance energy harvesting (up to ~25 V and ~1.2 μA) without assistance from other materials, even when the counterpart triboelectric surface has a slightly different triboelectric series. This enhanced triboelectrification is attribute to work function change as well as enlarged surface roughness. Finally, the direct-synthesized MoS2 patterns are utilized to fabricate a self-powered flexible haptic sensor array. The technique we propose here is intended to stimulate further investigation of the triboelectric effects and applications of 2D TMDC nanomaterials.

Ultralight Smart Patch with Reduced Sensing Array Based on Reduced Graphene Oxide for Hand Gesture Recognition

Flexible sensors for hand gesture recognition and human–machine interface (HMI) applications have witnessed tremendous advancements during the last decades. Current state‐of‐the‐art sensors placed on fingers or embedded into gloves are incapable of fully capturing all hand gestures and are often uncomfortable for the wearer. Herein, a flake‐sphere hybrid structure of reduced graphene oxide (rGO) doped with polystyrene (PS) spheres is fabricated to construct the highly sensitive, fast response, and flexible piezoresistive sensor array, which is ultralight in the weight of only 2.8 g and possesses the remarkable curved‐surface conformability. The flexible wrist‐worn device with a five‐sensing array is used to measure pressure distribution around the wrist for accurate and comfortable hand gesture recognition. The intelligent wristband is able to classify 12 hand gestures with 96.33% accuracy for five participants using a machine learning algorithm. To showcase our wristband, a real‐time system is developed to control a robotic hand via the classification results, which further demonstrates the potential of this work for HMI applications.

Low-cost fabrication of flexible tactile sensor arrays

While for vision and audio the same mass-produced units can be embedded in many different systems from smartphones to robots, tactile sensors have to be built in application-specific shapes and sizes. To use a commercially available tactile sensor, it can be necessary to develop the entire system around an existing sensor model. We present a set of open-source solutions for designing, manufacturing, reading and integrating custom application-specific tactile matrix sensors. Our manufacturing process only requires an off-the-shelf cutting plotter and widely available plastic and metal foils. This allows creating sensors of diverse sizes, shapes, and layouts, which can be adapted to various specific use cases as demonstrated with exemplary robot integrations. For interfacing and readout, we develop an Arduino-like prototype board (Tacduino) with amplifier circuits to ensure good resolution and to suppress crosstalk. As an example, we give step-by-step instructions to build tactile fingertips for the RobotiQ 3-Finger Gripper, and we provide design files for the readout circuit board together with Arduino firmware and driver software. Both, wired and wireless communication between the sensors and a host PC are supported by this system. The hardware was originally presented and investigated in [1].

Large-Scale Integrated Flexible Tactile Sensor Array for Sensitive Smart Robotic Touch.

In the long pursuit of smart robotics, it has been envisioned to empower robots with human-like senses, especially vision and touch. While tremendous progress has been made in image sensors and computer vision over the past decades, tactile sense abilities are lagging behind due to the lack of large-scale flexible tactile sensor array with high sensitivity, high spatial resolution, and fast response. In this work, we have demonstrated a 64 × 64 flexible tactile sensor array with a record-high spatial resolution of 0.9 mm (equivalently 28.2 pixels per inch) by integrating a high-performance piezoresistive film (PRF) with a large-area active matrix of carbon nanotube thin-film transistors. PRF with self-formed microstructures exhibited high pressure-sensitivity of ∼385 kPa-1 for multi-walled carbon nanotubes concentration of 6%, while the 14% one exhibited fast response time of ∼3 ms, good linearity, broad detection range beyond 1400 kPa, and excellent cyclability over 3000 cycles. Using this fully integrated tactile sensor array, the footprint maps of an artificial honeybee were clearly identified. Furthermore, we hardware-implemented a smart tactile system by integrating the PRF-based sensor array with a memristor-based computing-in-memory chip to record and recognize handwritten digits and Chinese calligraphy, achieving high classification accuracies of 98.8% and 97.3% in hardware, respectively. The integration of sensor networks with deep learning hardware may enable edge or near-sensor computing with significantly reduced power consumption and latency. Our work could empower the building of large-scale intelligent sensor networks for next-generation smart robotics.

Analysis of Leakage in a Sustainable Water Pipeline Based on a Magnetic Flux Leakage Technique

Pipelines are typically used to transport oil, natural gas, water, etc. It is one of the most effective methods for transferring fluids over long distances. However, long-term usage of these pipes without maintenance results in the formation of residues, which will pave the way for pipeline accidents and soil contamination. To ensure the safety and protection of resources, these sustainable pipelines need to be inspected to avoid losses. This work aims to investigate various internal defect leaks in the non-uniform thickness of sustainable water pipes that are joined with a pipe expander. The magnetic flux leakage technique was implemented to evaluate these defects by means of a flexible GMR sensor array. An inspection robot containing two units was fabricated with the aid of 3D printing. The power unit provides the necessary thrust to actuate the entire robot whereas the sensing unit is responsible for analyzing the leaks. The robot’s movement is predicted by the MPU6050 and ultrasonic distance sensors that are plotted as motion plots. The sensing unit consists of permanent magnets and a giant magnetoresistance (GMR) array to interrogate the flux leakage in the defect region. The flux leakage from the defects was stored with the help of an Arduino microcontroller, which controls the overall process. In addition, the spring suspension is provided to regulate the motion of the robot. The flux leakage from the defect region was plotted as waveform graphs. Thus, the results are effectively presented and compared. The calculated signal-to-noise ratio (SNR) of the magnetic flux leakages (MFLs) for 4.5 mm-thick pipe defects was 12 to 20.8 dB, and for 6.52 mm-thick pipe defects, it was 9.5 to 19 dB. In sum, the MFL technique provides a reliable method for the sustainable development of water supply to wide areas.

Flexible Electronic Skin for Monitoring of Grasping State During Robotic Manipulation.

Electronic skin for robotic tactile sensing has been studied extensively over the past years, yet practical applications of electronic skin for the grasping state monitoring during robotic manipulation are still limited. In this study, we present the fabrication and implementation of electronic skin sensor arrays for the detection of unstable grasping. The piezoresistive sensor arrays have the advantages of facile fabrication, fast response, and high reliability. With the tactile data from the sensor array, we propose two quantitative indicators, correlation coefficient and wavelet coefficient, to identify grasping with variable forces and slippage. Those two indicators reflect both time and frequency domain characteristics in the contact forces from the sensor array and can be obtained without large amount of calculation. We demonstrate the utility of this method under various conditions, the results indicate grasping with variable forces, and slippage can be distinguished by this method. The flexible sensor arrays are adopted for tactile sensing on a bionic hand, and the effectiveness of this method in detecting various grasping states has been verified. The electronic skin sensor array and the grasping state monitoring method are promising for applications in robotic dexterous manipulation.

Recent Progress in Flexible Pressure Sensor Arrays.

Flexible pressure sensors that can maintain their pressure sensing ability with arbitrary deformation play an essential role in a wide range of applications, such as aerospace, prosthetics, robotics, healthcare, human–machine interfaces, and electronic skin. Flexible pressure sensors with diverse conversion principles and structural designs have been extensively studied. At present, with the development of 5G and the Internet of Things, there is a huge demand for flexible pressure sensor arrays with high resolution and sensitivity. Herein, we present a brief description of the present flexible pressure sensor arrays with different transduction mechanisms from design to fabrication. Next, we discuss the latest progress of flexible pressure sensor arrays for applications in human–machine interfaces, healthcare, and aerospace. These arrays can monitor the spatial pressure and map the trajectory with high resolution and rapid response beyond human perception. Finally, the outlook of the future and the existing problems of pressure sensor arrays are presented.