Intelligent, Flexible Artificial Throats with Sound Emitting, Detecting, and Recognizing Abilities.

In recent years, there has been a notable rise in the number of patients afflicted with laryngeal diseases, including cancer, trauma, and other ailments leading to voice loss. Currently, the market is witnessing a pressing demand for medical and healthcare products designed to assist individuals with voice defects, prompting the invention of the artificial throat (AT). This user-friendly device eliminates the need for complex procedures like phonation reconstruction surgery. Therefore, in this review, we will initially give a careful introduction to the intelligent AT, which can act not only as a sound sensor but also as a thin-film sound emitter. Then, the sensing principle to detect sound will be discussed carefully, including capacitive, piezoelectric, electromagnetic, and piezoresistive components employed in the realm of sound sensing. Following this, the development of thermoacoustic theory and different materials made of sound emitters will also be analyzed. After that, various algorithms utilized by the intelligent AT for speech pattern recognition will be reviewed, including some classical algorithms and neural network algorithms. Finally, the outlook, challenge, and conclusion of the intelligent AT will be stated. The intelligent AT presents clear advantages for patients with voice impairments, demonstrating significant social values.

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.

An Ultra-Sensitive and Multifunctional Electronic Skin with Synergetic Network of Graphene and CNT.

Electronic skin (e-skin) has attracted tremendous interest due to its diverse potential applications, including in physiological signal detection, health monitoring, and artificial throats. However, the major drawbacks of traditional e-skin are the weak adhesion of substrates, incompatibility between sensitivity and stretchability, and its single function. These shortcomings limit the application of e-skin and increase the complexity of its multifunctional integration. Herein, the synergistic network of crosslinked SWCNTs within and between multilayered graphene layers was directly drip coated onto the PU thin film with self-adhesion to fabricate versatile e-skin. The excellent mechanical properties of prepared e-skin arise from the sufficient conductive paths guaranteed by SWCNTs in small and large deformation under various strains. The prepared e-skin exhibits a low detection limit, as small as 0.5% strain, and compatibility between sensitivity and stretchability with a gauge factor (GF) of 964 at a strain of 0-30%, and 2743 at a strain of 30-60%. In physiological signals detection application, the e-skin demonstrates the detection of subtle motions, such as artery pulse and blinking, as well as large body motions, such as knee joint bending, elbow movement, and neck movement. In artificial throat application, the e-skin integrates sound recognition and sound emitting and shows clear and distinct responses between different throat muscle movements and different words for sound signal acquisition and recognition, in conjunction with superior sound emission performance with a sound spectrum response of 71 dB (f = 12.5 kHz). Overall, the presented comprehensive study of novel materials, structures, properties, and mechanisms offers promising potential in physiological signals detection and artificial throat applications.

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.

Graphene-Based Multifunctional Textile for Sensing and Actuating.

Textiles are materials that are extensively used in everyday life; textile-based sensors can, therefore, be regarded as ideal devices for a health monitor. However, previously reported textile sensors have limited prospects due to their single function or incompatibility. Traditional textile sensors generally focus on signal detection, which has not been able to be combined with an actuator to provide real-time health status feedback. Thus, to date, there are no well-established health monitoring systems based on intelligent textiles. Herein, we present a wearable batch-prepared graphene-based textile based on laser-scribing and thermal-transfer technology. Integrated with four functions of strain sensing, pressure sensing, physiological electrical sensing, and sound emitting, the GT is able to detect human body signals and transduce them to sound signals when the user is in an abnormal physical state. Moreover, the GT has high linearity for both strain and pressure sensing; the coefficients of determination exceed 99.3% and 98.2%, respectively. The performance of the device remains stable up to a pressure of 1000 kPa. The response time of the GT possession reaches as low as 85 ms at 4.2 Pa pressure. Therefore, due to their diversified functions and good performance, the research on GT is expected to extend to the fields of health monitoring, sports monitoring, and so forth.

Ultrasensitive Detection of COVID-19 Causative Virus (SARS-CoV-2) Spike Protein Using Laser Induced Graphene Field-Effect Transistor.

COVID-19 is a highly contagious human infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the war with the virus is still underway. Since no specific drugs have been made available yet and there is an imbalance between supply and demand for vaccines, early diagnosis and isolation are essential to control the outbreak. Current nucleic acid testing methods require high sample quality and laboratory conditions, which cannot meet flexible applications. Here, we report a laser-induced graphene field-effect transistor (LIG-FET) for detecting SARS-CoV-2. The FET was manufactured by different reduction degree LIG, with an oyster reef-like porous graphene channel to enrich the binding point between the virus protein and sensing area. After immobilizing specific antibodies in the channel, the FET can detect the SARS-CoV-2 spike protein in 15 min at a concentration of 1 pg/mL in phosphate-buffered saline (PBS) and 1 ng/mL in human serum. In addition, the sensor shows great specificity to the spike protein of SARS-CoV-2. Our sensors can realize fast production for COVID-19 rapid testing, as each LIG-FET can be fabricated by a laser platform in seconds. It is the first time that LIG has realized a virus sensing FET without any sample pretreatment or labeling, which paves the way for low-cost and rapid detection of COVID-19.

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.

Triode-Mimicking Graphene Pressure Sensor with Positive Resistance Variation for Physiology and Motion Monitoring.

The flexible pressure sensor is one of the essential components of the wearable device, which is a critical solution to the applications of artificial intelligence and human-computer interactions in the future. Due to its simple manufacturing process and measurement methods, research related to piezoresistive mechanical sensors is booming, and those sensors are already widely used in industry. However, existing pressure sensors are almost all based on negative resistance variations, making it difficult to reach a balance between the sensitivity and the detection range. Here, we demonstrated a low-cost flexible pressure sensor with a positive resistance-pressure response based on laser scribing graphene. The sensor can be customized and modulated to achieve both an ultrahigh sensitivity and a broad detection range. Furthermore, the device possesses the signal amplification property like a mechanical triode under the external pressure bias. Based on its amplification ability, varieties of physiological signals and human movements have been detected using our devices; then, an integrated gait monitoring system has been realized. The reported positive graphene pressure sensor has outstanding capability, showing a wide application range such as intelligent perception, an interactive device, and real-time health/motion monitoring.

Highly Transparent and Sensitive Graphene Sensors for Continuous and Non-invasive Intraocular Pressure Monitoring.

Intraocular pressure (IOP) is the prime indicator for the diagnosis and treatment of glaucoma. IOP has circadian rhythm changes and is dependent on body gestures; therefore, a single measurement in the clinic can be misleading for diagnosis. Herein, few-layer graphene is utilized to develop non-invasive sensors with high transparency, sensitivity, linearity, and biocompatibility for 24 h continuous IOP monitoring. The graphene Wheatstone bridge consisting of two strain gauges and two compensating resistors is designed to improve the sensitivity and accuracy of IOP measurement. Testing results on a silicone eyeball indicate that the output voltage of the sensor is proportional to the IOP fluctuation. Under the various ranges and speeds of IOP fluctuation, the sensor exhibits excellent performance of dynamic cycles and step responses with an average sensitivity of 150 µV/mmHg. With the linear relationship, the average relative error between the calibrated IOP and the standard pressure is maintained at about 5%. More than 100 cycles and interval time measurements illustrate that the sensor possesses significant stability, durability, and reliability. Furthermore, a wireless system is designed for the sensor to realize IOP monitoring using a mobile phone. This sensor, with the average transparency of 85% and its ease of fabrication, as well as its portability for continuous IOP monitoring, brings new promise to the diagnosis and treatment of glaucoma.

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.

Flexible Two-Dimensional Ti3C2 MXene Films as Thermoacoustic Devices.

MXenes have attracted great attention for their potential applications in electrochemical and electronic devices due to their excellent characteristics. Traditional sound sources based on the thermoacoustic effect demonstrated that a conductor needs to have an extremely low heat capacity and high thermal conductivity. Hence, a thin MXene film with a low heat capacity per unit area (HCPUA) and special layered structure is emerging as a promising candidate to build loudspeakers. However, the use of MXenes in a sound source device has not been explored. Herein, we have successfully prepared sound source devices on an anodic aluminum oxide (AAO) and a flexible polyimide (PI) substrates by using the prepared Ti3C2 MXene nanoflakes. Due to the larger interlayer distance of MXene, the MXene-based sound source device has a higher sound pressure level (SPL) than that of graphene of the same thickness. High-quality Ti3C2 MXene nanoflakes were fabricated by selectively etching the Ti3AlC2 powder. The as-fabricated MXene sound source device on an AAO substrate exhibits a higher SPL of 68.2 dB (f = 15 kHz) and has a very stable sound spectrum output with frequency varying from 100 Hz to 20 kHz. A theoretical model has been built to explain the mechanism of the sound source device on an AAO substrate, matching well with the experimental results. Furthermore, the MXene sound source device based on a flexible PI substrate has been attached to the arms, back of the hand, and fingers, indicating an excellent acoustic wearability. Then, the MXene film is packaged successfully into a commercial earphone case and shows an excellent performance at high frequencies, which is very suitable for human audio equipment.

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.

A Wearable Skinlike Ultra-Sensitive Artificial Graphene Throat.

Most mute people cannot speak due to their vocal cord lesion. Herein, to assist mute people to "speak", we proposed a wearable skinlike ultrasensitive artificial graphene throat (WAGT) that integrated both sound/motion detection and sound emission in single device. In this work, the growth and patterning of graphene can be realized at the same time, and a thin poly(vinyl alcohol) film with laser-scribed graphene was obtained by a water-assisted transferring process. In virtue of the skinlike and low-resistant substrate, the WAGT has a high detection sensitivity (relative resistance changes up to 150% at 133 Ω) and an excellent sound-emitting ability (up to 75 dB at 0.38 W power and 2 mm distance). On the basis of the excellent mechanical-electrical performance of graphene structure, the sound detecting and emitting mechanisms of WAGT are realized and discussed. For sound detection, both the motion of larynx and vibration of vocal cord contribute to throat movements. For sound emission, a thermal acoustic model for WAGT was established to reveal the principle of sound emitting. More importantly, a homemade circuit board was fabricated to build a dual-mode system, combining the detection and emitting systems. Meanwhile, different human motions, such as strong and small throat movements, were also detected and transformed into different sounds like "OK" and "NO". Therefore, the implementation of these sound/motion detection acoustic systems enable graphene to achieve device-level applications to system-level applications, and those graphene acoustic systems are wearable for its miniaturization and light weight.

An efficient flexible graphene-based light-emitting device.

In recent years, flexible light-emitting devices (LEDs) have become the main focus in the field of display technology. Graphene, a two-dimensional layered material, has attracted great interest in LEDs due to its excellent properties. However, there are many problems such as efficiency, lifetime, and flexibility not well solved. Herein, we have successfully prepared a flexible LED using laser-induced reduced graphene oxide (LIRGO). The LIRGO LED achieves a luminescence lifetime of over 60 hours and a wall plug efficiency of up to 1.4% in a vacuum environment of 0.02 Pa. There are many small luminescent spots randomly distributed on 3.5 × 5 mm2 of LIRGO. LIRGO's luminous behavior can be controlled by modifying the supply voltage and laser reduction intensity. We also explore LIRGO's applications by testing it in different packages and customizable bulbs. Furthermore, as an interesting demo, the LIRGO device can be used to mimic constellations with visual shapes. This work demonstrates LIRGO's great potential in many fields, such as flexible and miniature light sources and displays.

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.