Flexible Sensor Array Research Articles

A Flexible Self-Powered Occlusal Force Sensor Array for Assisting Oral Occlusion Reconstruction

Occlusal force is increasingly being recognized as a key parameter for evaluating masticatory motor dysfunction and the effectiveness of dental management in patients. However, the evaluation of occlusal force lacks objective quantitative assessment and reliable monitoring techniques. Here, a flexible self-powered sensor array is proposed for real-time monitoring occlusal force to further assist in oral occlusion reconstruction. Employing the triboelectric nanogenerator technology, the battery-free sensor succeeds in effectively capturing static and dynamic occlusal forces from teeth and converting them into accurate and quantitative electrical signals. With an average sensitivity of 0.72 volts per Newton and a response time of 15 milliseconds, the sensor features excellent synchronicity in electro-mechanical conversion and durability. Furthermore, the sensor array, based on complementary semicircular electrodes (15 × 15 pixels), enables the construction of visualized electrical signals mapping, which can reflect the intensity and location of occlusal force. The patterned electrical signal distribution can then be analyzed by researchers, providing a quantitative reference for clinical crown restoration. We expect this self-powered sensor array to enrich the approaches of occlusal force detection and provide valuable assistance for the reconstruction of oral occlusion.

Braille Tactile-to-Auditory Conversion System Based on Self-Learning Flexible Tactile Sensor Array With Attention-Mechanism Model

Braille Tactile-to-Auditory Conversion System Based on Self-Learning Flexible Tactile Sensor Array With Attention-Mechanism Model

A Plantar Pressure Detection and Gait Analysis System Based on Flexible Triboelectric Pressure Sensor Array and Deep Learning.

Gait detection is essential for the assessment of human health status and early diagnosis of diseases. The current gait analysis systems are bulky, limited in the scope of use, and cause interference with the movement of the measured person. Hence, it is necessary to develop a wearable gait detection system that is soft, breathable, lightweight, and self-powered. Here, a plantar pressure sensor array and gait analysis system based on a flexible triboelectric pressure sensor (FTPS) array is developed. Soft, breathable, and wearable electrospinning nanofiber film with excellent triboelectric properties is used as the plantar pressure sensor, achieving a high sensitivity of 45.1 mVkPa-1 in the range of 40-200 kPa and 19.4 mVkPa-1 in the range of 200-400 kpa. 32 FTPSs are integrated into an intelligent insole, which has the characteristics of soft, easy production, good air permeability, long-time stability, no external power supply, and etc. Based on the long short-term memory artificial neural network deep learning model, the accuracy of gait judgment can reach 94.23%. This work provides a feasible solution for real-time gait detection, which will have potential applications in human health assessment and early diagnosis of disease.

Manipulator with Integrated Flexible Tactile Sensing Arrays for Kiwifruit Ripeness and Size Classification.

Fruit grading for ripeness and size is an essential process in the supply chain. Incorrect grading can easily lead to spoiled and degraded fruits entering the market, reducing consumers' confidence in purchasing. At the same time, it is easy to cause the fruit supply chain to reduce profits, unreasonable resource allocation, and related practitioners' income. The current mainstream machine vision grading and manual grading in the production line have dilemmas such as susceptibility to environmental interference, inconsistent grading standards, high cost, and labor shortage. To overcome these problems, this study proposes an integrated flexible tactile sensing array (3 × 4) manipulator for efficient, stable, low-cost, and accurate ripeness and size grading of kiwifruit. The flexible sensing manipulator grasps the kiwifruit, detects the hardness of the kiwifruit by relying on tactile sensing, and determines the ripeness level based on the hardness. The size of the kiwifruit is also differentiated according to whether there is a significant change in the resistance of the topmost sensing unit of the flexible pressure sensor array. The 0, 1, 2, 3, 4, and 5 anomalies that may occur in actual production were tested and combined with machine learning KNN, SVM, and RF algorithms for data modeling and grading. The results show that the lowest accuracy of 0, 1, 2, 3, 4, and 5 possible outliers is 86.67% (KNN), 95.83% (SVM), and 92.5% (RF), respectively. KNN has the lowest classification effect, and SVM has the best. This study overcomes the drawbacks of inefficient destructive detection and unstable manual detection and makes up for the vulnerability of single machine vision to interference from environmental factors. This study can alleviate the challenges caused by fruit wastage and promote the sustainable production and consumption of the fruit industry chain.

Sleep State Monitoring System Based on Flexible Pressure Sensor Arrays for Evaluating Sleep Quality

Sleep State Monitoring System Based on Flexible Pressure Sensor Arrays for Evaluating Sleep Quality

Robust biomimetic strain sensor based on butterfly wing-derived skeleton structure

A biomimetic strain sensor was designed and constructed based on Ir nanoparticles-modified multi-wall carbon nanotubes (Ir NPs@MWCNTs) and parallel Pt layer/dragon skin with carbonized butterfly wing patterns. This sensor exhibits high gauge factor (∼515.4), extensive tensile range (0%–96%), and swift response (∼300 ms), especially remarkable stability up to 60 000 cycles. The work mechanism has been proposed based on the experimental test and finite-element method. Some important applications such as human motion and micro-expression recognition have been confirmed using 3 × 3 flexible biomimetic sensor array.

Highly robust electronic skin for object recognition of robot hand based on carbon nanomaterials and SEBS

When robot hands work in a complex environment, they not only need to sense the objects in contact but also need to respond to remote events before physical contact. In this way, robot hands can make predictions, to better adapt to the complex environment. In this paper, we have designed a flexible sensor array, which integrates a piezoresistive sensor and a capacitive sensor for detecting pressure and proximity direction and distance signals simultaneously. Piezoresistive sensors can detect pressure signals in real-time, and capacitive sensors detect pressure and proximity signals. The sensors are arranged in a patterned array and installed on the robot hand to help the robot hand detect the distance and direction of approaching objects, as well as the shape and size of the grasped objects. To avoid mechanical mismatch, piezoresistive sensors and capacitive sensors are fabricated with the same flexible materials. In addition, after extreme pressure tests, the sensors can still work normally, to ensure that the robot hands can work normally after collision. We also combined the detected signal with machine learning, so that the robot can accurately identify objects of different shapes. In the fruit recognition test, the recognition accuracy reached 90 %.

A wearable sign language translation device utilizing silicone-hydrogel hybrid triboelectric sensor arrays and machine learning

Sign language is a crucial communication tool for the hearing impaired to interact with the outside world. However, the low prevalence of sign language leads to significant communication barriers between the hearing impaired and others. These barriers can be alleviated by using electronic sign language translation devices, but such devices typically face challenges related to their bulkiness, rigidity, and high cost. Herein, we present a cost-effective, flexible, and wearable device designed for the interpretation of sign language, leveraging machine learning algorithms to transform sign language movements into spoken language accurately. Our device is equipped with flexible and stretchable triboelectric sensor (FS-TS) arrays and a printed circuit board for efficient signal processing and wireless transmission. These FS-TSs are constructed from cost-effective materials including silicone, hydrogel, and fluorinated ethylene propylene (FEP) powders, which, while affordable, ensure rapid response and heightened sensitivity. By analyzing 1,000 sets of sign language gestures with machine learning, our system has achieved an impressive recognition accuracy of 98.5%. This achievement underscores the potential of our system as an economically viable and scalable solution for enhancing sign language recognition within the wearable electronics domain.

Traditional Chinese Medicine (TCM)-Inspired Fully Printed Soft Pressure Sensor Array with Self-Adaptive Pressurization for Highly Reliable Individualized Long-Term Pulse Diagnostics.

Reliable, non-invasive, continuous monitoring of pulse and blood pressure is essential for the prevention and diagnosis of cardiovascular diseases. However, the pulse wave varies drastically among individuals or even over time in the same individual, presenting significant challenges for the existing pulse sensing systems. Inspired by pulse diagnosis methods in traditional Chinese medicine (TCM), this work reports a self-adaptive pressure sensing platform (PSP) that combines the fully printed flexible pressure sensor array with an adaptive wristband-style pressure system can identify the optimal pulse signal. Besides the detected pulse rate/width/length, "Cun, Guan, Chi" position, and "floating, moderate, sinking" pulse features, the PSP combined with a machine learning-based linear regression model can also accurately predict blood pressure such as systolic, diastolic, and mean arterial pressure values. The developed diagnostic platform is demonstrated for highly reliable long-term monitoring and analysis of pulse and blood pressure across multiple human subjects over time. The design concept and proof-of-the-concept demonstrations also pave the way for the future developments of flexible sensing devices/systems for adaptive individualized monitoring in the complex practical environments for personalized medicine, along with the support for the development of digital TCM.

Biomimetic Contact Behavior Inspired Tactile Sensing Array with Programmable Microdomes Pattern by Scalable and Consistent Fabrication.

Flexible sensor arrays have attracted extensive attention in human-computer interaction. However, realizing high-performance sensor units with programmable properties, and expanding them to multi-pixel flexible arrays to maintain high sensing consistency is still struggling. Inspired by the contact behavior of octopus antenna, this paper proposes a programmable multistage dome structure-based flexible sensing array with robust sensing stability and high array consistency. The biomimetic multistage dome structure is pressurized to gradually contact the electrode to achieve high sensitivity and a large pressure range. By adjusting the arrangement of the multistage dome structure, the pressure range and sensitivity can be customized. More importantly, this biomimetic structure can be expanded to a multi-pixel sensor array at the wafer level with high consistency through scalable and high-precision imprinting technologies. In the imprinting process, the conductive layer is conformally embedded into the multistage dome structure to improve the stability (maintain stability over 22000 cycles). In addition, the braced isolation structure is designed to effectively improve the anti-crosstalk performance of the sensor array (crosstalk coefficient: 26.62dB). Benefitting from the programmable structural design and high-precision manufacturing process, the sensor array can be customized and is demonstrated to detect human musculation in medical rehabilitation applications.

A compressible high-sensitivity flexible sensor array for real-time motion artifact detection in magnetic resonance imaging

Magnetic Resonance Imaging (MRI) serves as a critical tool in modern medical diagnosis, and its accuracy is directly linked to patient treatment and recovery. However, unintentional patient movement during MRI scans often results in motion artifacts on the images, significantly compromising the precision of diagnosis. Traditional solutions typically involve identifying and addressing these issues after the scanning sequence is completed, leading to significant resource waste and delays in patient treatment. Here, we propose a flexible tactile sensor array system based on triboelectric nanogenerators (TENGs) for real-time monitoring of head motion artifacts in MRI. The unique design of the tactile sensor structure, operating in a dual-electrode mode, maintains high sensitivity and a wide response range, even with a minimal surface area. The advantage of TENG is the wide range of material choices, ensuring that a proper selection will not interfere with MRI during application. By integrating TENG sensor technology and control program systems, this solution provides a novel approach for monitoring head motion artifacts in MRI. On the basis of ensuring patient comfort, it has saved the time and money costs of monitoring, improved the efficiency of detection, and demonstrated significant potential in the field of medical imaging.

Breaking the Saturation of Sensitivity for Ultrawide Range Flexible Pressure Sensors by Soft-Strain Effect.

The flexible pressure sensors with a broad pressure range and unsaturated sensitivity are highly desired in practical applications. However, pressure sensors by piezoresistive effect are always limited by the compressibility of sensing layers, resulting in a theoretically decreasing sensitivity of less than 100%. Here, a unique strategy is proposed that utilizes the strain effect, simultaneously achieving a trade-off between a wider pressure detection range and unsaturated sensitivity. Ascribed to the strain effect of sensing layers induced by interlaced microdomes, the sensors possess an increased sensitivity (5.22-70 MPa-1) over an ultrawide pressure range (45 Pa-4.1 MPa), a high-pressure resolution (5 Pa), fast response/recovery time (30/45 ms), and a robust response under a high-pressure loading of 3.5 MPa for more than 5000 cycles. These superior sensing performances allow the sensor to monitor large pressure. The flexible pressure sensor array can assist doctors in restoring the neutral mechanical axis, tracking knee flexion angles, and extracting gait features. Moreover, the flexible sensing array can be integrated into the joint motion surveillance system to map the balance medial-lateral contact forces on the metal compartments in real time, demonstrating the potential for further development into precise medical human-machine interfaces during total knee replacement surgery.

Thin, flexible hybrid-structured piezoelectric sensor array with enhanced resolution and sensitivity

Wearable piezoelectric electronics have garnered significant interest in healthcare and human-machine interfaces due to their unique ability to convert mechanical stimuli into electrical signals. However, current wearable piezoelectric sensors struggle with low spatial resolution, limited sensitivity, and insufficient mechanical flexibility. Here, we report materials and designs of a thin, flexible piezoelectric sensor array with a balanced performance that could be used for spatiotemporal pressure mapping on human skin. The device with a soft-rigid hybrid structure integrates small-pixel, highly sensitive piezoceramic thick films into a conformally adaptable format that achieves satisfactory spatial resolution (6 mm), high sensitivity (15.08 mV/kPa) and optimal flexibility (bending radius of 4.23 mm). Theoretical analysis indicates that the thickness of substrate presents a trade-off between output performance and mechanical flexibility. To demonstrate the capabilities of the device, it has been employed to monitor joint bending, human gait, and throat sounds. Furthermore, it incorporates a convolutional neural network (CNN-2D) for voice recognition, achieving an impressive accuracy of 98.18 %. These capabilities underscore the potential of the device in advanced wearable applications, offering a robust platform for real-time, high-resolution physiological monitoring.

An ultrathin, rapidly fabricated, flexible giant magnetoresistive electronic skin

In recent years, there has been a significant increase in the prevalence of electronic wearables, among which flexible magnetoelectronic skin has emerged as a key component. This technology is part of the rapidly progressing field of flexible wearable electronics, which has facilitated a new human perceptual development known as the magnetic sense. However, the magnetoelectronic skin is limited due to its low sensitivity and substantial field limitations as a wearable electronic device for sensing minor magnetic fields. Additionally, achieving efficient and non-destructive delamination in flexible magnetic sensors remains a significant challenge, hindering their development. In this study, we demonstrate a novel magnetoelectronic touchless interactive device that utilizes a flexible giant magnetoresistive sensor array. The flexible magnetic sensor array was developed through an electrochemical delamination process, and the resultant ultra-thin flexible electronic system possessed both ultra-thin and non-destructive characteristics. The flexible magnetic sensor is capable of achieving a bending angle of up to 90 degrees, maintaining its performance integrity even after multiple repetitive bending cycles. Our study also provides demonstrations of non-contact interaction and pressure sensing. This research is anticipated to significantly contribute to the advancement of high-performance flexible magnetic sensors and catalyze the development of more sophisticated magnetic electronic skins.

Temperature-Switching Flexible Strain Sensors Based on Vanadium Dioxide for Intelligent Packaging Applications.

Flexible sensors are promising for intelligent packaging and artificial intelligence, but the required multistimulus response is still a challenge in external environments. A candidate material for such multistimulus response is VO2 due to its unique semiconducting properties. Herein, W-doped VO2(M) with a tunable phase transition temperature was prepared by the hydrothermal method, and then, VO2(M)-based flexible sensors were fabricated employing a direct-write strategy, where conductive inks with VO2(M) powders were patterned onto various substrates. These sensors achieve dual responses to temperature and strain and exhibit high stability (over 2000 stretch-release cycles) to accurately monitor various statuses (opening and closing, temperature changes, etc.) of intelligent packaging. The spatial pressure distribution of different objects was discerned by the prepared VO2(M)/poly(dimethylsiloxane) (PDMS) sponge flexible pressure sensor arrays, and the information was successfully edited using the Morse code. The sensing signals from the intelligent packaging were collected and remotely transmitted to intelligent terminals via a wireless local-area network to achieve real-time monitoring of the packaged contents. Therefore, in this work, we not only designed new flexible sensors with multiple stimulus responses but also demonstrated the potential applications of W-doped VO2(M)-based flexible sensors in intelligent packaging.

GW-MUSIC focusing algorithm with high accuracy for composite damage diagnosis

The Guided Wave (GW)-based Multiple Signal Classification (MUSIC) method for damage imaging in composite structures offers high-resolution and flexible sensor array placement, demonstrating considerable potential for precise damage localization. However, the application to real aircraft composite structures, characterized by complex structural features, presents substantial challenges. These include complex boundary reflections, pronounced anisotropy, and diminished scattered signals from damage sites. This paper presents a novel single-peak anisotropy-compensated MUSIC method for damage imaging of complex composites. This method, designed for improved localization accuracy, combines a self-excited calibration strategy to mitigate anisotropy with single wave peak focusing to amplify signals and reduce boundary reflections. Experimental validation on a complex composite wing structure demonstrated significant enhancements in localization precision, affirming the method's efficacy.

Stretch-tolerant interconnects derived from silanization-assisted capping layer lamination for smart skin-attachable electronics

Flexible strain sensor arrays hold great promise in on-skin monitoring of human signals and activities. Despite the development of strain-sensitive materials and patterning technologies for improved performance and device integration, the metal film serving as interconnects is always vulnerable upon stretch, which hinders the operation under large strains. Herein, a novel strategy is developed for achieving stretch-tolerant interconnects within a sensor array. Through introducing a high-modulus capping layer for the deposition of Ag interconnects, followed by silanization-assisted lamination onto the stretchable substrate where strain-sensitive graphene patches are inkjet-printed, the deformation of Ag interconnects is largely suppressed upon the global strain of the device, and a high working range of 40 % strain is achieved. Moreover, the chemical bonding between the capping layer and the stretchable substrate ensures a stable contact between the electrode and the sensitive layer under vigorous bending. The as-prepared sensor array demonstrates high sensitivity (gauge factor (GF) > 100) within a wide range (18 %), and could reliably monitor various physiological signals and human activities. A machine learning-assisted wearable gesture recognition system is developed based on the sensor array and a convolutional neural network (CNN), which could distinguish from 10 defined gestures with 100 % accuracy after 14 training processes. The facile and effective strategy could be universally applied for metal interconnects protection under stretch, and dramatically facilitate the design of smart flexible electronics.

Wearable multichannel-active pressurized pulse sensing platform

With the modernization of traditional Chinese medicine (TCM), creating devices to digitalize aspects of pulse diagnosis has proved to be challenging. The currently available pulse detection devices usually rely on external pressure devices, which are either bulky or poorly integrated, hindering their practical application. In this work, we propose an innovative wearable active pressure three-channel pulse monitoring device based on TCM pulse diagnosis methods. It combines a flexible pressure sensor array, flexible airbag array, active pressure control unit, advanced machine learning approach, and a companion mobile application for human–computer interaction. Due to the high sensitivity (460.1 kPa−1), high linearity (R2 > 0.999) and flexibility of the flexible pressure sensors, the device can accurately simulate finger pressure to collect pulse waves (Cun, Guan, and Chi) at different external pressures on the wrist. In addition, by measuring the change in pulse wave amplitude at different pressures, an individual’s blood pressure status can be successfully predicted. This enables truly wearable, actively pressurized, continuous wireless dynamic monitoring of wrist pulse health. The innovative and integrated design of this pulse monitoring platform could provide a new paradigm for digitizing aspects of TCM and other smart healthcare systems.

A Flexible Double-Sided Curvature Sensor Array for Use in Soft Robotics.

This paper describes the design, fabrication, integration, characterization, and demonstration of a novel flexible double-sided curvature sensor array for use in soft robotics. The paper explores the performance and potential applications of a piezoresistive sensor array consisting of four gold strain gauges on a flexible polyimide (PI) substrate arranged in a Wheatstone bridge configuration. Multiple sensor strips were arranged like the fingers of a hand. Integrating Shape Memory Alloy (SMA) foils alongside the fingers was explored to mimic a human hand-gripping motion controlled with temperature, while curvature sensor array strips measure the resulting finger shapes. Moreover, object sensing in a flexible granular material gripper was demonstrated. The sensors were embedded within Polydimethylsiloxane (PDMS) to enhance their tactile feel and adhesive properties. The findings of this study are promising for future applications, particularly in robotics and prosthetics, as the ability to accurately mimic human hand movements and reconstruct sensor surfaces paves the way for robotic hand functionality.

Flexible Tactile Sensor Arrays With Capacitive and Resistive Dual-Mode Transduction

Flexible Tactile Sensor Arrays With Capacitive and Resistive Dual-Mode Transduction