Recent Progress of Tactile and Force Sensors for Human-Machine Interaction.

Human-Machine Interface (HMI) plays a key role in the interaction between people and machines, which allows people to easily and intuitively control the machine and immersively experience the virtual world of the meta-universe by virtual reality/augmented reality (VR/AR) technology. Currently, wearable skin-integrated tactile and force sensors are widely used in immersive human-machine interactions due to their ultra-thin, ultra-soft, conformal characteristics. In this paper, the recent progress of tactile and force sensors used in HMI are reviewed, including piezoresistive, capacitive, piezoelectric, triboelectric, and other sensors. Then, this paper discusses how to improve the performance of tactile and force sensors for HMI. Next, this paper summarizes the HMI for dexterous robotic manipulation and VR/AR applications. Finally, this paper summarizes and proposes the future development trend of HMI.

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.

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.

Designs and Applications for the Multimodal Flexible Hybrid Epidermal Electronic Systems.

Research on the flexible hybrid epidermal electronic system (FHEES) has attracted considerable attention due to its potential applications in human-machine interaction and healthcare. Through material and structural innovations, FHEES combines the advantages of traditional stiff electronic devices and flexible electronic technology, enabling it to be worn conformally on the skin while retaining complex system functionality. FHEESs use multimodal sensing to enhance the identification accuracy of the wearer's motion modes, intentions, or health status, thus realizing more comprehensive physiological signal acquisition. However, the heterogeneous integration of soft and stiff components makes balancing comfort and performance in designing and implementing multimodal FHEESs challenging. Herein, multimodal FHEESs are first introduced in 2 types based on their different system structure: all-in-one and assembled, reflecting totally different heterogeneous integration strategies. Characteristics and the key design issues (such as interconnect design, interface strategy, substrate selection, etc.) of the 2 multimodal FHEESs are emphasized. Besides, the applications and advantages of the 2 multimodal FHEESs in recent research have been presented, with a focus on the control and medical fields. Finally, the prospects and challenges of the multimodal FHEES are discussed.

Recent Advances in Flexible Piezoresistive Arrays: Materials, Design, and Applications.

Spatial distribution perception has become an important trend for flexible pressure sensors, which endows wearable health devices, bionic robots, and human-machine interactive interfaces (HMI) with more precise tactile perception capabilities. Flexible pressure sensor arrays can monitor and extract abundant health information to assist in medical detection and diagnosis. Bionic robots and HMI with higher tactile perception abilities will maximize the freedom of human hands. Flexible arrays based on piezoresistive mechanisms have been extensively researched due to the high performance of pressure-sensing properties and simple readout principles. This review summarizes multiple considerations in the design of flexible piezoresistive arrays and recent advances in their development. First, frequently used piezoresistive materials and microstructures are introduced in which various strategies to improve sensor performance are presented. Second, pressure sensor arrays with spatial distribution perception capability are discussed emphatically. Crosstalk is a particular concern for sensor arrays, where mechanical and electrical sources of crosstalk issues and the corresponding solutions are highlighted. Third, several processing methods are also introduced, classified as printing, field-assisted and laser-assisted fabrication. Next, the representative application works of flexible piezoresistive arrays are provided, including human-interactive systems, healthcare devices, and some other scenarios. Finally, outlooks on the development of piezoresistive arrays are given.

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.

Breathable Electronic Skins for Daily Physiological Signal Monitoring.

With the aging of society and the increase in people's concern for personal health, long-term physiological signal monitoring in daily life is in demand. In recent years, electronic skin (e-skin) for daily health monitoring applications has achieved rapid development due to its advantages in high-quality physiological signals monitoring and suitability for system integrations. Among them, the breathable e-skin has developed rapidly in recent years because it adapts to the long-term and high-comfort wear requirements of monitoring physiological signals in daily life. In this review, the recent achievements of breathable e-skins for daily physiological monitoring are systematically introduced and discussed. By dividing them into breathable e-skin electrodes, breathable e-skin sensors, and breathable e-skin systems, we sort out their design ideas, manufacturing processes, performances, and applications and show their advantages in long-term physiological signal monitoring in daily life. In addition, the development directions and challenges of the breathable e-skin are discussed and prospected.

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 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.

A Low-Cost, Portable, and Wireless In-Shoe System Based on a Flexible Porous Graphene Pressure Sensor.

Monitoring gait patterns in daily life will provide a lot of biological information related to human health. At present, common gait pressure analysis systems, such as pressure platforms and in-shoe systems, adopt rigid sensors and are wired and uncomfortable. In this paper, a biomimetic porous graphene-SBR (styrene-butadiene rubber) pressure sensor (PGSPS) with high flexibility, sensitivity (1.05 kPa-1), and a wide measuring range (0-150 kPa) is designed and integrated into an insole system to collect, process, transmit, and display plantar pressure data for gait analysis in real-time via a smartphone. The system consists of 16 PGSPSs that were used to analyze different gait signals, including walking, running, and jumping, to verify its daily application range. After comparing the test results with a high-precision digital multimeter, the system is proven to be more portable and suitable for daily use, and the accuracy of the waveform meets the judgment requirements. The system can play an important role in monitoring the safety of the elderly, which is very helpful in today's society with an increasingly aging population. Furthermore, an intelligent gait diagnosis algorithm can be added to realize a smart gait monitoring system.

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.

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.

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.

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.