Graphene-based Two-Stage Enhancement Pressure Sensor for Subtle Mechanical Force Monitoring.

The development of pressure sensors with high sensitivity and a low detection limit for subtle mechanical force monitoring and the understanding of the sensing mechanism behind subtle mechanical force monitoring are of great significance for intelligent technology. Here, we proposed a graphene-based two-stage enhancement pressure sensor (GTEPS), and we analyzed the difference between subtle mechanical force monitoring and conventional mechanical force monitoring. The GTEPS exhibited a high sensitivity of 62.2 kPa-1 and a low detection limit of 0.1 Pa. Leveraging its excellent performance, the GTEPS was successfully applied in various subtle mechanical force monitoring applications, including acoustic wave detection, voice-print recognition, and pulse wave monitoring. In acoustic wave detection, the GTEPS achieved a 100% recognition accuracy for six words. In voiceprint recognition, the sensor exhibited accurate identification of distinct voiceprints among individuals. Furthermore, in pulse wave monitoring, GTEPS demonstrated effective detection of pulse waves. By combination of the pulse wave signals with electrocardiogram (ECG) signals, it enabled the assessment of blood pressure. These results demonstrate the excellent performance of GTEPS and highlight its great potential for subtle mechanical force monitoring and its various applications. The current results indicate that GTEPS shows great potential for applications in subtle mechanical force monitoring.

Wearable Temperature Sensors Based on Reduced Graphene Oxide Films.

With the development of medical technology and increasing demands of healthcare monitoring, wearable temperature sensors have gained widespread attention because of their portability, flexibility, and capability of conducting real-time and continuous signal detection. To achieve excellent thermal sensitivity, high linearity, and a fast response time, the materials of sensors should be chosen carefully. Thus, reduced graphene oxide (rGO) has become one of the most popular materials for temperature sensors due to its exceptional thermal conductivity and sensitive resistance changes in response to different temperatures. Moreover, by using the corresponding preparation methods, rGO can be easily combined with various substrates, which has led to it being extensively applied in the wearable field. This paper reviews the state-of-the-art advances in wearable temperature sensors based on rGO films and summarizes their sensing mechanisms, structure designs, functional material additions, manufacturing processes, and performances. Finally, the possible challenges and prospects of rGO-based wearable temperature sensors are briefly discussed.

Carbon-Based Textile Sensors for Physiological-Signal Monitoring.

As the focus on physical health increases, the market demand for flexible wearable sensors increases. Textiles combined with sensitive materials and electronic circuits can form flexible, breathable high-performance sensors for physiological-signal monitoring. Carbon-based materials such as graphene, carbon nanotubes (CNTs), and carbon black (CB) have been widely utilized in the development of flexible wearable sensors due to their high electrical conductivity, low toxicity, low mass density, and easy functionalization. This review provides an overview of recent advancements in carbon-based flexible textile sensors, highlighting the development, properties, and applications of graphene, CNTs, and CB for flexible textile sensors. The physiological signals that can be monitored by carbon-based textile sensors include electrocardiogram (ECG), human body movement, pulse and respiration, body temperature, and tactile perception. We categorize and describe carbon-based textile sensors based on the physiological signals they monitor. Finally, we discuss the current challenges associated with carbon-based textile sensors and explore the future direction of textile sensors for monitoring physiological signals.

Wearable Continuous Blood Pressure Monitoring Devices Based on Pulse Wave Transit Time and Pulse Arrival Time: A Review.

Continuous blood pressure (BP) monitoring is of great significance for the real-time monitoring and early prevention of cardiovascular diseases. Recently, wearable BP monitoring devices have made great progress in the development of daily BP monitoring because they adapt to long-term and high-comfort wear requirements. However, the research and development of wearable continuous BP monitoring devices still face great challenges such as obvious motion noise and slow dynamic response speeds. The pulse wave transit time method which is combined with photoplethysmography (PPG) waves and electrocardiogram (ECG) waves for continuous BP monitoring has received wide attention due to its advantages in terms of excellent dynamic response characteristics and high accuracy. Here, we review the recent state-of-art wearable continuous BP monitoring devices and related technology based on the pulse wave transit time; their measuring principles, design methods, preparation processes, and properties are analyzed in detail. In addition, the potential development directions and challenges of wearable continuous BP monitoring devices based on the pulse wave transit time method are discussed.

Soft Electronics for Health Monitoring Assisted by Machine Learning.

Due to the development of the novel materials, the past two decades have witnessed the rapid advances of soft electronics. The soft electronics have huge potential in the physical sign monitoring and health care. One of the important advantages of soft electronics is forming good interface with skin, which can increase the user scale and improve the signal quality. Therefore, it is easy to build the specific dataset, which is important to improve the performance of machine learning algorithm. At the same time, with the assistance of machine learning algorithm, the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis. The soft electronics and machining learning algorithms complement each other very well. It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future. Therefore, in this review, we will give a careful introduction about the new soft material, physiological signal detected by soft devices, and the soft devices assisted by machine learning algorithm. Some soft materials will be discussed such as two-dimensional material, carbon nanotube, nanowire, nanomesh, and hydrogel. Then, soft sensors will be discussed according to the physiological signal types (pulse, respiration, human motion, intraocular pressure, phonation, etc.). After that, the soft electronics assisted by various algorithms will be reviewed, including some classical algorithms and powerful neural network algorithms. Especially, the soft device assisted by neural network will be introduced carefully. Finally, the outlook, challenge, and conclusion of soft system powered by machine learning algorithm will be discussed.

Two-stage amplification of an ultrasensitive MXene-based intelligent artificial eardrum.

We report an artificial eardrum using an acoustic sensor based on two-dimensional MXene (Ti3C2Tx), which mimics the function of a human eardrum for realizing voice detection and recognition. Using MXene with a large interlayer distance and micropyramid polydimethylsiloxane arrays can enable a two-stage amplification of pressure and acoustic sensing. The MXene artificial eardrum shows an extremely high sensitivity of 62 kPa-1 and a very low detection limit of 0.1 Pa. Notably, benefiting from the ultrasensitive MXene eardrum, the machine-learning algorithm for real-time voice classification can be realized with high accuracy. The 280 voice signals are successfully classified for seven categories, and a high accuracy of 96.4 and 95% can be achieved by the training dataset and the test dataset, respectively. The current results indicate that the MXene artificial intelligent eardrum shows great potential for applications in wearable acoustical health care devices.

Intelligent and highly sensitive strain sensor based on indium tin oxide micromesh with a high crack density.

Cracks play an important role in strain sensors. However, a systematic analysis of how cracks influence the strain sensors has not been proposed. In this work, an intelligent and highly sensitive strain sensor based on indium tin oxide (ITO)/polyurethane (PU) micromesh is realized. The micromesh has good skin compatibility, water vapor permeability, and stability. Due to the color of the ITO/PU micromesh, it can be invisible on the skin. Based on the fragility of ITO, the density and resistance of cracks in the micromesh are greatly improved. Therefore, the ITO/PU micromesh strain sensor (IMSS) has an ultrahigh gauge factor (744.3). In addition, a finite element model based on four resistance layers is proposed to explain the performance of the IMSS and show the importance of high-density cracks. Compared with other strain sensors based on low-density cracks, the IMSS based on high-density cracks has larger sensitivity and better linearity. Physiological signals, such as respiration, pulse, and joint motion, can be monitored using the IMSS self-fixed on the skin. Finally, an invisible and artificial throat has been realized by combining the IMSS with a convolutional neural network algorithm. The artificial throat can translate the throat vibrations of the tester automatically with an accuracy of 86.5%. This work has great potential in health care and language function reconstruction.

Intelligent and Multifunctional Graphene Nanomesh Electronic Skin with High Comfort.

As the aging population increases in many countries, electronic skin (e-skin) for health monitoring has been attracting much attention. However, to realize the industrialization of e-skin, two factors must be optimized. The first is to achieve high comfort, which can significantly improve the user experience. The second is to make the e-skin intelligent, so it can detect and analyze physiological signals at the same time. In this article, intelligent and multifunctional e-skin consisting of laser-scribed graphene and polyurethane (PU) nanomesh is realized with high comfort. The e-skin can be used as a strain sensor with large measurement range (>60%), good sensitivity (GF≈40), high linearity range (60%), and excellent stability (>1000 cycles). By analyzing the morphology of e-skin, a parallel networks model is proposed to express the mechanism of the strain sensor. In addition, laser scribing is also applied to etch the insulating PU, which greatly decreases the impedance in detecting electrophysiology signals. Finally, the e-skin is applied to monitor the electrocardiogram, electroencephalogram (EEG), and electrooculogram signals. A time- and frequency-domain concatenated convolution neural network is built to analyze the EEG signal detected using the e-skin on the forehead and classify the attention level of testers.

Programmable Sensitivity Screening of Strain Sensors by Local Electrical and Mechanical Properties Coupling.

Owing to the canonical trade-off between the gauge factor and the working range, there is an emergent need for strain sensors with customizable sensitivity for various applications of different deformation ranges. However, current optimization strategies typically allow possessing either, not both, high-sensing performance or customizable sensing performance. Here, a laser-programmed heterogeneous strain sensor featured locally coupled electrical and mechanical properties (named an LCoup sensor) is developed to access customized sensor performance. Coupled electromechanical properties enable the applied strain to be mainly experienced by the higher sensitivity regions when stretched. By optimizing the parameters of laser processes, the gauge factor can systematically screen within 2 orders of magnitude (from 7.8 to 266.6) while maintaining good stretchability (50%). To prove the potential in human-machine interaction, the real-time monitoring and recognition of set hand gestures (left-click, right-click, and double-click) are demonstrated, representing the traditional input patterns of the computer mouse. Multiscale programming of material properties can further achieve excellent and tailored device performances, offering more opportunities for the design of a broad range of flexible electronics.

Multifunctional Graphene Microstructures Inspired by Honeycomb for Ultrahigh Performance Electromagnetic Interference Shielding and Wearable Applications.

High-performance electromagnetic interference (EMI) shielding materials with ultralow density, excellent flexibility, and good mechanical properties are highly desirable for aerospace and wearable electronics. Herein, honeycomb porous graphene (HPG) fabricated by laser scribing technology is reported for EMI shielding and wearable applications. Due to the honeycomb structure, the HPG exhibits an EMI shielding effectiveness (SE) up to 45 dB at a thickness of 48.3 µm. The single-piece HPG exhibits an ultrahigh absolute shielding effectiveness (SSE/t) of 240 123 dB cm2/g with an ultralow density of 0.0388 g/cm3, which is significantly superior to the reported materials such as carbon-based, MXene, and metal materials. Furthermore, MXene and AgNWs are employed to cover the honeycomb holes of the HPG to enhance surface reflection; thus, the SSE/t of the HPG/AgNWs composite membrane can reach up to 292 754 dB cm2/g. More importantly, the HPG exhibits excellent mechanical stability and durability in cyclic stretching and bending, which can be used to monitor weak physiological signals such as pulse, respiration, and laryngeal movement of humans. Therefore, the lightweight and flexible HPG exhibits excellent EMI shielding performance and mechanical properties, along with its low cost and ease of mass production, which is promising for practical applications in EMI shielding and wearable electronics.

Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis.

Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stretchability, and induces interface mismatch. In addition, the substrate prevents the evaporation of sweat and is harmful to skin health. In this work, we have enabled the substrate-free laser scribed graphene (SFG) electronic skin (e-skin) with multifunctions. Compared with the e-skin with the substrate, the SFG has good gas permeability, low impedance, and flexibility. Only assisted using water, the SFG can be transferred to almost any objects including silicon and human skin and it can even be suspended. Many through-holes like stomas in leaf can be formed in the SFG, which make it breathable. After designing the pattern, the gauge factor (GF) of graphene electronic skin (GES) can be designed as the strain sensor. Physiological signals such as respiration, human motion, and electrocardiogram (ECG) can be detected. Moreover, the suspended SFG detect vibrations with high sensitivity. Due to the substrate-free structure, the impedance between SFG e-skin and the human body decreases greatly. Finally, an ECG detecting system has been designed based on the GES, which can monitor the body condition in real time. To analyze the ECG signals automatically, a convolutional neural network (CNN) was built and trained successfully. This work has high potential in the field of health telemonitoring.

Graphene-Based Thermoacoustic Sound Source.

Thermoacoustic (TA) effect has been discovered for more than 130 years. However, limited by the material characteristics, the performance of a TA sound source could not be compared with magnetoelectric and piezoelectric loudspeakers. Recently, graphene, a two-dimensional material with the lowest heat capacity per unit area, was discovered to have a good TA performance. Compared with a traditional sound source, graphene TA sound sources (GTASSs) have many advantages, such as small volume, no diaphragm vibration, wide frequency range, high transparency, good flexibility, and high sound pressure level (SPL). Therefore, graphene has a great potential as a next-generation sound source. Photoacoustic (PA) imaging can also be applied to the diagnosis and treatment of diseases using the photothermo-acoustic (PTA) effect. Therefore, in this review, we will introduce the history of TA devices. Then, the theory and simulation model of TA will be analyzed in detail. After that, we will talk about the graphene synthesis method. To improve the performance of GTASSs, many strategies such as lowering the thickness and using porous or suspended structures will be introduced. With a good PTA effect and large specific area, graphene PA imaging and drug delivery is a promising prospect in cancer treatment. Finally, the challenges and prospects of GTASSs will be discussed.

Graphene-based wearable sensors.

The human body is a "delicate machine" full of sensors such as the fingers, nose, and mouth. In addition, numerous physiological signals are being created every moment, which can reflect the condition of the body. The quality and the quantity of the physiological signals are important for diagnoses and the execution of therapies. Due to the incompact interface between the sensors and the skin, the signals obtained by commercial rigid sensors do not bond well with the body; this decreases the quality of the signal. To increase the quantity of the data, it is important to detect physiological signals in real time during daily life. In recent years, there has been an obvious trend of applying graphene devices with excellent performance (flexibility, biocompatibility, and electronic characters) in wearable systems. In this review, we will first provide an introduction about the different methods of synthesis of graphene, and then techniques for graphene patterning will be outlined. Moreover, wearable graphene sensors to detect mechanical, electrophysiological, fluid, and gas signals will be introduced. Finally, the challenges and prospects of wearable graphene devices will be discussed. Wearable graphene sensors can improve the quality and quantity of the physiological signals and have great potential for health-care and telemedicine in the future.

Development of a portable setup using a miniaturized and high precision colorimeter for the estimation of phosphate in natural water.

In this work, a high integrated water detection system comprised a miniaturized and high precision homemade colorimeter, a microfluidic analysis module and a wireless module was reported. A reagent reaction based on the ammonium molybdate spectrophotometric method was recorded for the estimation of phosphate in natural water. A laser self-modulating module of 880 nm was used as the radiation source. A microfluidic chip was employed to fit the colorimeter with an optimized micro flow path for low liquid consumption and high precision detection. The wireless module consisted of two parts, using ZigBee and GSM modules to realize short and remote displaying and controlling. Applying a novel optimized algorithm, a wide linear response was obtained ranging from 0.02 up to 9.5 mg L-1. The optimization of colorimeterare mainly in the core detection part, allowing an improvement of the detection limit, achieving a result of 0.009 mg L-1. A low reagent consumption of 0.004 mg ascorbic acid and 0.011 mg ammonium molybdate for per determination was attained. Experimental results have also shown that the system could maintain good stability among broad room temperature changing from 17 °C to 35 °C with less energy consumption. The miniaturized colorimeter-based water detection system opens new avenue for operating in remote distance to get high precision measurements of phosphate in natural water.

Multifunctional Mechanical Sensors for Versatile Physiological Signal Detection.

Recently, flexible and wearable mechanical sensors have attracted great attention because of their potential applications in monitoring various physiological signals. However, conventional mechanical sensors rarely have both pressure and strain sensing abilities that can meet the demands of both subtle and large human motion detection. Besides, the mechanical sensors with tunable sensitivity or measuring range are also essential for their practical applications. Herein, the graphene ink dip-coating method with merits of time saving, low cost, and large scale was used to fabricate the foam-structured graphene sensors with both pressure and strain sensing performance. Because of high elasticity of styrene butadiene rubber (SBR) substrates and stacked graphene flakes, the tunable mechanical sensors exhibit a high gauge factor (GF) and large measuring range for specific human motion detection. The pressure sensor shows a GF of 2.02 kPa-1 with a pressure range up to 172 kPa, and the strain sensor displays a GF of 250 with a strain range up to 86%. On the one hand, various detections of subtle vital signals with small strain change were demonstrated by the pressure sensor because of its flexibility and high sensitivity. On another hand, the strain sensor with large strain change shows excellent ability to detect various large human motions including the bending of neck, finger, wrist, and knee. Interestingly, both the pressure sensor and strain sensor exhibit great capability for recognizing 26 letters written by hand. The working mechanism based on the contact area variation was also investigated by the morphology evolution and resistance model. We suppose that the foam-structured graphene mechanical sensors would be promising in wearable electronics for human healthcare and activity monitoring in the future.

Multilayer Graphene Epidermal Electronic Skin.

Due to its excellent flexibility, graphene has an important application prospect in epidermal electronic sensors. However, there are drawbacks in current devices, such as sensitivity, range, lamination, and artistry. In this work, we have demonstrated a multilayer graphene epidermal electronic skin based on laser scribing graphene, whose patterns are programmable. A process has been developed to remove the unreduced graphene oxide. This method makes the epidermal electronic skin not only transferable to butterflies, human bodies, and any other objects inseparably and elegantly, merely with the assistance of water, but also have better sensitivity and stability. Therefore, pattern electronic skin could attach to every object like artwork. When packed in Ecoflex, electronic skin exhibits excellent performance, including ultrahigh sensitivity (gauge factor up to 673), large strain range (as high as 10%), and long-term stability. Therefore, many subtle physiological signals can be detected based on epidermal electronic skin with a single graphene line. Electronic skin with multiple graphene lines is employed to detect large-range human motion. To provide a deeper understanding of the resistance variation mechanism, a physical model is established to explain the relationship between the crack directions and electrical characteristics. These results show that graphene epidermal electronic skin has huge potential in health care and intelligent systems.

Wearable humidity sensor based on porous graphene network for respiration monitoring.

Respiration is as one of the most essential physiological signals, which can be used to monitor human healthcare and activities. Herein, we report a flexible, lightweight and highly conductive porous graphene network as the humidity sensor for respiration monitoring. To enhance the sensing performance, the graphene oxide (GO), poly (3, 4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT: PSS) and Ag colloids (AC) were used to modify the porous graphene. The humidity properties of porous based graphene networks have been investigated at different relative humidity (RH). The porous based graphene sensors exhibit excellent capability of monitoring different breathing patterns including mouse and nose respiration, normal and deep respiration. Besides, the signal variations before and after water intake was recorded by the sensor, which demonstrates the ability to monitor water loss during breathing period. Furthermore, the humidity sensor shows the ability to detect physiological activities including skin moisture, speaking and whistle rhythm, which could be a promising electronic for clinical respiration monitoring.

Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor.

There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions.

Fast and sensitive detection of Pb2+ in foods using disposable screen-printed electrode modified by reduced graphene oxide.

In this study, reduced graphene oxide (rGO) was electrochemically deposited on the surface of screen-printed carbon electrodes (SPCE) to prepare a disposable sensor for fast detection of Pb2+ in foods. The SEM images showed that the rGO was homogeneously deposited onto the electrode surface with a wrinkled nanostructure, which provided 2D bridges for electron transport and a larger active area for Pb2+ adsorption. Results showed that rGO modification enhanced the activity of the electrode surface, and significantly improved the electrochemical properties of SPCE. The rGO modified SPCE (rGO-SPCE) was applied to detect Pb2+ in standard aqueous solution, showing a sharp stripping peak and a relatively constant peak potential in square wave anodic stripping voltammetry (SWASV). The linear range for Pb2+ detection was 5~200 ppb (R2 = 0.9923) with a low detection limit of 1 ppb (S/N = 3). The interference of Cd2+ and Cu2+ at low concentrations was effectively avoided. Finally, the rGO-SPCE was used for determination of lead in real tap water, juice, preserved eggs and tea samples. Compared with results from graphite furnace atomic absorption spectroscopy (GFAAS), the results based on rGO-SPCE were both accurate and reliable, suggesting that the disposable sensor has great potential in application for fast, sensitive and low-cost detection of Pb2+ in foods.

O2 plasma-functionalized SWCNTs and PEDOT/PSS composite film assembled by dielectrophoresis for ultrasensitive trimethylamine gas sensor.

A novel gas sensor based on composite films of poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT/PSS) and single-walled carbon nanotubes (SWCNTs) was fabricated for the detection of fishy trimethylamine (TMA) vapor. The SWCNTs were functionalized by O2 plasma treatment to improve their solubility in the polymeric matrix, and alternative current dielectrophoresis was utilized for the first time to assemble the PEDOT/PSS-SWCNTs composite film to enhance the response to TMA molecules. The high resolution transmission electron microscopy (HR-TEM) images showed that the SWCNTs maintained their bulk structure after O2 plasma functionalization. The scanning electron microscopy (SEM) images of the composite film showed that the oxidized SWCNTs were orderly arranged and uniformly dispersed into the polymer by dielectrophoresis. Compositional analyses of SWCNTs by X-ray photoelectron spectroscopy (XPS) suggested that O2 plasma functionalization could remove amorphous carbon from the nanotube surface and introduce more hydrophilic oxygen-containing groups, leading to the improvement of SWCNTs solubility in the polymeric matrix. Gas sensitivities of the composite films largely relied on the treatment conditions. Compared to the raw or acid-treated SWCNTs-doped composite films, the film doped with SWCNTs modified by O2 plasma at 30 W for 3 min exhibited the most sensitive and stable response characteristics to ppb-level TMA gas.