Two-Stage Micropyramids Enhanced Flexible Piezoresistive Sensor for Health Monitoring and Human-Computer Interaction

High-Sensitivity All-Fiber Sensor Smart Gloves for Hand Perception

Flexible piezoresistive sensors (FPSs) with high sensitivity and conformability are crucial for achieving fine operations in electronic gloves. In this work, a chemical grafting method is used to ensure strong interfacial bonding between the conductive phase and the flexible polyimide (PI) matrix with a high glass transition temperature (Tg). This design helps to tackle the stress relaxation and interfacial debonding problems commonly faced by FPSs. Silver fiber electrodes are prepared by in situ reduction of silver nanoparticles on PI fibers to further improve the sensitivity. This FPS is characterized by high sensitivity (214.6 kPa-1), low response time and recovery time (44 and 42 ms, respectively), outstanding recoverable performance (with a low hysteresis of 4.58% FS), and remarkable dynamic stability (a 3.6% decay of signal intensity after 24,000 cycles). An all-fiber flexible piezoresistive sensor array glove has been constructed to achieve conformal contact with the robot hand. Furthermore, comprehensive detection of multipoint pressures on the hand and high-sensitivity tactile perception for the robot hand have been achieved.

Flexible hybrid self-powered piezo-triboelectric nanogenerator based on BTO-PVDF/PDMS nanocomposites for human machine interaction

As flexible and wearable electronics play more and more important role in smart watches, smart glass and virtual reality, and the power supply to the wearable electronics have been revealed more attentions for long-term usage and continuous healthy monitoring. To overcome the challenge, flexible self-powered BTO-PVDF/PDMS piezoelectric-triboelectric electric hybrid generators (BPP-HNG) are developed to human gesture monitoring and human machine interaction (HMI) application without external power supply. BPP-HNG based on BTO-PVDF and PDMS films are prepared by sol-gel and spin-coating method. When the BTO content is 20 wt.%, BPP-HNG exhibits better electrical performance with an output voltage of 20.51 V. A real-time gesture monitoring system is designed and developed to human machine interaction, which is able to control the motion of robot finger through BPP-HNG. BPP-HNG could monitor and recognize various gestures in real time, enabling synchronization between the human hand and the robot's hand. With the convergence of AI technology and big data, BPP-HNG based HMI technology is expected to realize the potential of smarter and more intuitive interactions.

Flexible Optical Fiber Sensor for Non-Invasive Continuous Monitoring of Human Physiological Signals

With increasing health awareness, monitoring human physiological signals for health status and disease prevention has become crucial. Non-invasive flexible wearable devices address issues like invasiveness, inconvenience, size, and continuous monitoring challenges in traditional devices. Among flexible sensors, optical fiber sensors (OFSs) stand out due to their excellent biocompatibility, anti-electromagnetic interference capabilities, and ability to monitor multiple signals simultaneously. This paper reviews the application of flexible optical fiber sensing technology (OFST) in monitoring human lung function, cardiovascular function, body parameters, motor function, and various physiological signals. It emphasizes the importance of continuous monitoring in personal health management, clinical settings, sports training, and emergency response. The review discusses challenges in OFST for continuous health signal monitoring and envisions its significant potential for future development. This technology underscores the importance of constant health signal monitoring and highlights the advantages and prospects of optical fiber sensing. Innovations in OFS for non-invasive continuous monitoring of physiological signals hold profound implications for materials science, sensing technology, and biomedicine.

Wearable System Integrating Dual Piezoresistive and Photoplethysmography Sensors for Simultaneous Pulse Wave Monitoring

Wearable, flexible piezoresistive pressure sensors have garnered substantial interest due to their diverse applications in fields such as electronic skin, robotic limbs, and cardiovascular monitoring. Among these applications, arterial full pulse waveform monitoring stands out as a critical area of research. The emergence of piezoresistive pressure sensors as a prominent tool for capturing pulse waveforms has led to extensive investigations. However, the lack of a linear response while achieving high sensitivity, limited compactness of signal collection systems, and scaling issues are a few potential causes of the gap between research advances and technology market readiness. Here, we present a scalable dual piezoresistive sensor that uses two complementary resistance-changing mechanisms to balance the trade-off between linear response and high sensitivity. This synergic design enables excellent sensitivity of 8.4 kPa-1 and near linear pressure response. It boasts a fast response time of 95/145 ms for loading and unloading at a pressure of 10.1 kPa. The durability tests, encompassing nearly 5000 two-stage compression cycles, validate the reliable performance of the sensor, even after prolonged use. Leveraging these performance metrics, we developed a high-resolution and compact signal collection device capable of accurately detecting the three distinct peaks associated with the full pulse waveform, including the systolic and reflected diastolic peaks. Moreover, the signal acquisition system incorporates a photoplethysmography sensor, which, when paired with the dual piezoresistive sensor, offers new insights into localized vascular health monitoring. The unique feature of our approach is its ability to perform localized vascular monitoring using multiple sensors placed on different veins. The simultaneous detection of forward- and backward-going pulse waves at the body extremities allows for a comprehensive evaluation of localized vascular health, which is not achievable with a single sensor. Finally, the comparison of wrist pulse waveforms between the compact signal collection device and a standard sourcemeter (such as the Keithley 2460) confirmed that the wearable sensing system is on par with conventional sourcemeters in terms of capturing the typical details of the full pulse waveform (i.e., systolic peak, dicrotic notch, and diastolic peak). This validation underscores the reliability and effectiveness of the developed wearable sensing system for practical and continuous pulse waveform monitoring.

Artificial Tactile Sensory Finger for Contact Pattern Identification Based on High Spatiotemporal Piezoresistive Sensor Array

Human fingertip tactile perception relies on the activation of densely distributed tactile receptors to identify contact patterns in the brain. Despite significant efforts to integrate tactile sensors with machine learning algorithms for recognizing physical patterns on object surfaces, developing a tactile sensing system that emulates human fingertip capabilities for identifying contact patterns with a high spatiotemporal resolution remains a formidable challenge. In this study, we present the development of an artificial tactile finger for accurate contact pattern identification, achieved through the integration of a high spatiotemporal piezoresistive sensor array (PRSA) and a convolutional neural network (CNN) model. Spatiotemporal characterization tests reveal that the artificial finger exhibits a fast temporal resolution of approximately 7 ms and achieves a two-point threshold of 1.5 mm, surpassing that of the human fingertip. To compare the performance of the artificial finger with the human finger in recognizing different patterns, we acquired pressure images by pressing the artificial finger, coated with a flexible PRSA film, onto both simple embossed and complex curved patterns while also recording human recognition results of perceiving these patterns. Experimental findings demonstrate that the artificial finger achieves higher classification accuracy in recognizing both simple and complex patterns (99.0 and 96.1%, respectively) compared to the human fingertip (69.1 and 22.7%). This artificial finger serves as a promising platform with great potential for various robotic tactile sensing applications including prosthetics, skin electronics, and robotic surgery.

Intelligent Song Recognition via a Hollow-Microstructure-Based, Ultrasensitive Artificial Eardrum

Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa-1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1-2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow-microstructure-based sensor, indicating its potential applications in human-machine interaction and wearable acoustical technologies.

Recent Progress on Flexible Self-Powered Tactile Sensing Platforms for Health Monitoring and Robotics

Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self-powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e-skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self-powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self-powered tactile sensing systems are discussed.

Highly Sensitive Dual-Mode Touch Sensing Device Using Poly(vinylidene fluoride)/Graphene Nitride for Wearable E-Skin: Patterning, High-Temperature Annealing, and Remote Data Transmission

In recent years, significant advancements in printed electronics and flexible materials have catalyzed the development of electronic skins for wearable applications. However, the low glass transition temperature of flexible substrates poses a challenge as it is incompatible with the high-temperature annealing required for electrode fabrication, thereby limiting the performance of flexible electronic devices. In this study, we address these limitations by proposing a novel flexible device manufacturing process that combines adhesive printing patterning with a transfer printing technology. By employing poly(vinylidene fluoride) (PVDF)/graphene nitride (GCN) as the transfer substrate and dielectric layer, we successfully fabricated a high-performance dual-mode touch sensor on a large scale. The successful development of this dual-mode sensor can be attributed to two key factors: the construction of a robust hydrogen-bonding network between the PVDF/GCN dielectric layer and the carbon electrode and the ability of GCN to restrict the movement of PVDF molecular chains within the dielectric layer. This restriction reduces the overall polarization of the film, enabling the formation of a complete device structure with a highly sensitive edge electric field. The noncontact sensors developed in this study are fully printable into sensor arrays and can be seamlessly integrated with internet of things technology for wearable applications. These sensors exhibit exceptional tactile response and facilitate effective human-machine interactions over extended distances, underscoring their significant potential in fields such as healthcare and artificial intelligence.

Silver nanowires/waterborne polyurethane composite film based piezoresistive pressure sensor for ultrasensitive human motion monitoring

Flexible piezoresistive pressure sensors are gaining significant attention, particularly in the realm of flexible wearable electronic skin. Here, a flexible piezoresistive pressure sensor was developed with a broad sensing range and high sensitivity. We achieved this by curing polydimethylsiloxane (PDMS) on sandpaper, creating a PDMS film as the template with a micro-protrusion structure. The core sensing layer was formed using a composite of silver nanowires (AgNWs) and waterborne polyurethane (WPU) with a similar micro-protrusion structure. The sensor stands out with its exceptional sensitivity, showing a value of 1.04 × 106kPa-1with a wide linear range from 0 to 27 kPa. It also boasts a swift response and recovery time of 160 ms, coupled with a low detection threshold of 17 Pa. Even after undergoing more than 1000 cycles, the sensor continues to deliver stable performance. The flexible piezoresistive pressure sensor based on AgNWs/WPU composite film (AWCF) can detect small pressure changes such as pulse, swallowing, etc, which indicates that the sensor has great application potential in monitoring human movement and flexible wearable electronic skin.