Self-Powered and Self-Functional Cotton Sock Using Piezoelectric and Triboelectric Hybrid Mechanism for Healthcare and Sports Monitoring

A Piezoelectric Nanogenerator-Driven Dual-Mode Platform for Visualization and Impedance Sensing

Traditional visual biosensing platforms rely on color to display detection results, which can be influenced by individual visual abilities, equipment, parameters, and lighting conditions during photo capture. This limitation significantly impedes the advancement of next-generation portable electrochemical biosensors. Therefore, we propose a visual biosensing device that utilizes distance as an indicator, enabling the facile determination of the length of discoloration, which is inversely proportional to the concentration of the target analyte. The separation of the Signal Generation (SG) and Signal Output (SO) regions effectively mitigates potential interference from the sample color. Additionally, the SG region can be disassembled to facilitate electrochemical impedance spectroscopy (EIS) detection in laboratory settings, enabling dual-mode detection. Meanwhile, the utilization of piezoelectric nanogenerators (PENG) empowers the entire point-of-care testing (POCT) sensing device, effectively addressing the issue of a limited battery life. The biosensing device exhibited a satisfactory linear range (EIS mode, 5 pg/L to 5 mg/L; visual mode, 0.5 ng/L to 5 mg/L) and a low limit of detection (EIS mode, 2.3 pg/L; visual mode, 0.14 ng/L) with S/N = 3 for ochratoxin A (OTA) under optimized conditions. The self-powered and cost-effective dual-mode biosensing platform developed for OTA detection offers clear and easily interpretable results, demonstrating a high accuracy in laboratory settings.

Biomimetic Electronic Skin for Robots Aiming at Superior Dynamic-Static Perception and Material Cognition Based on Triboelectric-Piezoresistive Effects

Empowering robots with tactile perception and even thinking as well as judgment capabilities similar to those of humans is an inevitable path for the development of future robots. Here, we propose a biomimetic electronic skin (BES) that truly serves and applies to robots to achieve superior dynamic-static perception and material cognition functionalities. First, the microstructured triboelectric and piezoresistive layers are fabricated by a facile template method followed by selected self-polymerization treatment, enabling BES with high sensitivity and a wide detection range. Further, through laminated-independent triboelectric and piezoresistive parts for perceiving dynamic and static pressures simultaneously, the BES is capable of supporting the robot hand to monitor the entire process during object grasping. Most importantly, by further combining a neural network model, an intelligent cognition system is constructed for real-time cognition of the object material species via one touch of the robot hand under arbitrary pressures, which goes beyond the human cognition ability.

Advancements in Bio-inspired Self-Powered Wireless Sensors: Materials, Mechanisms, and Biomedical Applications

The rapid maturation of smart city ecosystems is intimately linked to advances in the Internet of Things (IoT) and self-powered sensing technologies. Central to this evolution are battery-less sensors that are critical for applications such as continuous health monitoring through blood metabolites and vital signs, the recognition of human activity for behavioral analysis, and the operational enhancement of humanoid robots. The focus on biosensors that exploit the human body for energy-spanning wearable, attachable, and implantable variants has intensified, driven by their broad applicability in areas from underwater exploration to biomedical assays and earthquake monitoring. The heart of these sensors lies in their diverse energy harvesting mechanisms, including biofuel cells, and piezoelectric, triboelectric, and pyroelectric nanogenerators. Notwithstanding the wealth of research, the literature still lacks a holistic review that integrates the design challenges and implementation intricacies of such sensors. Our review seeks to fill this gap by thoroughly evaluating energy harvesting strategies from both material and structural perspectives and assessing their roles in powering an array of sensors for myriad uses. This exploration offers a comprehensive outlook on the state of self-powered sensing devices, tackling the nuances of their deployment and highlighting their potential to revolutionize data gathering in autonomous systems. The intent of this review is to chart the current landscape and future prospects, providing a pivotal reference point for ongoing research and innovation in self-powered wireless sensing technologies.

Porous Conductive Textiles for Wearable Electronics

Over the years, researchers have made significant strides in the development of novel flexible/stretchable and conductive materials, enabling the creation of cutting-edge electronic devices for wearable applications. Among these, porous conductive textiles (PCTs) have emerged as an ideal material platform for wearable electronics, owing to their light weight, flexibility, permeability, and wearing comfort. This Review aims to present a comprehensive overview of the progress and state of the art of utilizing PCTs for the design and fabrication of a wide variety of wearable electronic devices and their integrated wearable systems. To begin with, we elucidate how PCTs revolutionize the form factors of wearable electronics. We then discuss the preparation strategies of PCTs, in terms of the raw materials, fabrication processes, and key properties. Afterward, we provide detailed illustrations of how PCTs are used as basic building blocks to design and fabricate a wide variety of intrinsically flexible or stretchable devices, including sensors, actuators, therapeutic devices, energy-harvesting and storage devices, and displays. We further describe the techniques and strategies for wearable electronic systems either by hybridizing conventional off-the-shelf rigid electronic components with PCTs or by integrating multiple fibrous devices made of PCTs. Subsequently, we highlight some important wearable application scenarios in healthcare, sports and training, converging technologies, and professional specialists. At the end of the Review, we discuss the challenges and perspectives on future research directions and give overall conclusions. As the demand for more personalized and interconnected devices continues to grow, PCT-based wearables hold immense potential to redefine the landscape of wearable technology and reshape the way we live, work, and play.

Flexible Iron-On Sensor Embedded in Smart Sock for Gait Event Detection

Portable and wearable electronics for biomechanical data collection have become a growing part of everyday life. As smart technology improves and integrates into our lives, some devices remain ineffective, expensive, or difficult to access. We propose a washable iron-on textile pressure sensor for biometric data acquisition. Biometric data, such as human gait, are a powerful tool for the monitoring and diagnosis of ambulance and physical activity. To demonstrate this, our washable iron-on device is embedded into a sock and compared to gold standard force plate data. Biomechanical testing showed that our embedded sensor displayed a high aptitude for gait event detection, successfully identifying over 96% of heel strike and toe-off gait events. Our device demonstrates excellent attributes for further investigations into low-cost, washable, and highly versatile iron-on textiles for specialized biometric analysis.

Novel Sandwich-Structured Flexible Composite Films with Enhanced Piezoelectric Performance

Piezoelectric poly(vinylidene fluoride) (PVDF) and its copolymers have been widely investigated for applications in wearable electric devices and sensing systems, owing to their intrinsic piezoelectricity and superior flexibility. However, their weak piezoelectricity poses major challenges for practical applications. To overcome these challenges, we propose a two-step synthesis approach to fabricate sandwich-structured piezoelectric films (BaTiO3@PDA/PVDF/BaTiO3@PDA) with significantly enhanced ferroelectric and piezoelectric properties. As compared to pristine PVDF films or conventional 0-3 composite films, a maximum polarization (Pmax) of 11.24 μC/cm2, a remanent polarization (Pr) of 5.83 μC/cm2, and an enhanced piezoelectric coefficient (d33 ∼ 14.6 pC/N) were achieved. Simulation and experimental results have demonstrated that the sandwich structure enhances the ability of composite films to withstand higher poling electric fields in comparison with 0-3 composites. The sandwich-structured piezoelectric films are further integrated into a wireless sensor system with a high force sensitivity of 288 mV/N, demonstrating great potential for movement monitoring applications. This facile approach shows great promise for the large-scale production of composite films with remarkable flexibility, ferroelectricity, and piezoelectricity for wearable sensing devices.

A global bibliometric and visualized analysis of gait analysis and artificial intelligence research from 1992 to 2022

Gait is an important basic function of human beings and an integral part of life. Many mental and physical abnormalities can cause noticeable differences in a person's gait. Abnormal gait can lead to serious consequences such as falls, limited mobility and reduced life satisfaction. Gait analysis, which includes joint kinematics, kinetics, and dynamic Electromyography (EMG) data, is now recognized as a clinically useful tool that can provide both quantifiable and qualitative information on performance to aid in treatment planning and evaluate its outcome. With the assistance of new artificial intelligence (AI) technology, the traditional medical environment has undergone great changes. AI has the potential to reshape medicine, making gait analysis more accurate, efficient and accessible. In this study, we analyzed basic information about gait analysis and AI articles that met inclusion criteria in the WoS Core Collection database from 1992-2022, and the VosViewer software was used for web visualization and keyword analysis. Through bibliometric and visual analysis, this article systematically introduces the research status of gait analysis and AI. We introduce the application of artificial intelligence in clinical gait analysis, which affects the identification and management of gait abnormalities found in various diseases. Machine learning (ML) and artificial neural networks (ANNs) are the most often utilized AI methods in gait analysis. By comparing the predictive capability of different AI algorithms in published studies, we evaluate their potential for gait analysis in different situations. Furthermore, the current challenges and future directions of gait analysis and AI research are discussed, which will also provide valuable reference information for investors in this field.

Machine Learning-Enabled Intelligent Gesture Recognition and Communication System Using Printed Strain Sensors

Gesture contains abundant and complicated information in daily life; as a consequence, gesture recognition attracts a wide range of application prospects and academic values as an important way of achieving human-machine interactions (HMIs). Here, we report an intelligent system consisting of a smart glove made by printed CNT-graphene/PDMS strain sensors. The smart glove shows excellent fitness, comfort, and lightness for human hands. Inspired by machine learning strategies, several objects and gestures can be well classified and implemented by a customized artificial neural network. Several data sets of different sign language gestures and object-grabbing gestures were established, and the result shows that the intelligent system can achieve an average accuracy of 97% and up to 99.4% for a number of gesture groups. Moreover, a robot hand is connected to this system, which is able to react to the motion of human hands with certain gestures where simple sign communication is achieved. These features provide a feasible practical application scheme for gesture recognition in HMIs.

Smart Floor Mats for a Health Monitoring System Based on Textile Pressure Sensing: Development and Usability Study

BACKGROUND

The rise in single-person households has resulted in social problems like loneliness and isolation, commonly known as "death by loneliness." Various factors contribute to this increase, including a desire for independent living and communication challenges within families due to societal changes. Older individuals living alone are particularly susceptible to loneliness and isolation due to limited family communication and a lack of social activities. Addressing these issues is crucial, and proactive solutions are needed. It is important to explore diverse measures to tackle the challenges of single-person households and prevent deaths due to loneliness in our society.

OBJECTIVE

Non-face-to-face health care service systems have gained widespread interest owing to the rapid development of smart home technology. Particularly, a health monitoring system must be developed to manage patients' health status and send alerts for dangerous situations based on their activity. Therefore, in this study, we present a novel health monitoring system based on the auto-mapping method, which uses real-time position sensing mats.

METHODS

The smart floor mats are operated as piezo-resistive devices, which are composed of a carbon nanotube-based conductive textile, electrodes, main processor circuit, and a mat. The developed smart floor system acquires real-time position information using a multiconnection method between the modules based on the auto-mapping algorithm, which automatically creates a spatial map. The auto-mapping algorithm allows the user to freely set various activity areas through floor mapping. Then, the monitoring system was evaluated in a room with an area of 41.3 m2, which is embedded with the manufactured floor mats and monitoring application.

RESULTS

This monitoring system automatically acquires information on the total number, location, and direction of the mats and creates a spatial map. The position sensing mats can be easily configured with a simple structure by using a carbon nanotube-based piezo-resistive textile. The mats detect the activity in real time and record location information since they are connected through auto-mapping technology.

CONCLUSIONS

This system allows for the analysis of patients' behavior patterns and the management of health care on the web by providing important basic information for activity patterns in the monitoring system. The proposed smart floor system can serve as the foundation for smart home applications in the future, which include health care, intelligent automation, and home security, owing to its advantages of low cost, large area, and high reliability.

Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare

Sensors enable the detection of physiological indicators and pathological markers to assist in the diagnosis, treatment, and long-term monitoring of diseases, in addition to playing an essential role in the observation and evaluation of physiological activities. The development of modern medical activities cannot be separated from the precise detection, reliable acquisition, and intelligent analysis of human body information. Therefore, sensors have become the core of new-generation health technologies along with the Internet of Things (IoTs) and artificial intelligence (AI). Previous research on the sensing of human information has conferred many superior properties on sensors, of which biocompatibility is one of the most important. Recently, biocompatible biosensors have developed rapidly to provide the possibility for the long-term and in-situ monitoring of physiological information. In this review, we summarize the ideal features and engineering realization strategies of three different types of biocompatible biosensors, including wearable, ingestible, and implantable sensors from the level of sensor designing and application. Additionally, the detection targets of the biosensors are further divided into vital life parameters (e.g., body temperature, heart rate, blood pressure, and respiratory rate), biochemical indicators, as well as physical and physiological parameters based on the clinical needs. In this review, starting from the emerging concept of next-generation diagnostics and healthcare technologies, we discuss how biocompatible sensors revolutionize the state-of-art healthcare system unprecedentedly, as well as the challenges and opportunities faced in the future development of biocompatible health sensors.

Response Surface Methodology Analysis of Energy Harvesting System over Pathway Tiles

This paper presents an experimental analysis of the optimization of PZT-based tiles for energy harvesting. The hardware (actual experiment), PZT-based tiles, were developed using 6 × 6 piezoelectric (PZT-lead zirconate titanate) sensors of 40 mm in diameter on a hard cardboard sheet (300 × 300 mm²). Our experimental analysis of the designed tiles obtained an optimized power of 3.626 mW (85 kg or 0.83 kN using 36 sensors) for one footstep and 0.9 mW for 30 footsteps at high tapping frequency. Theoretical analysis was conducted with software (Design-Expert) using the response surface methodology (RSM) for optimized PZT tiles, obtaining a power of 6784.155 mW at 150 kg or 1.47 kN weight using 34 sensors. This software helped to formulate the mathematical equation for the most suitable PZT tile model for power optimization. It used the quadratic model to provide adjusted and predicted R2 values of 0.9916 and 0.9650, respectively. The values were less than 0.2 apart, which indicates a high correlation between the actual and predicted values. The outcome of the various experiments can help with the selection of input factors for optimized power during pavement design.

Flexible Textile-Based Sweat Sensors for Wearable Applications

The current physical health care system has gradually evolved into a form of virtual hospitals communicating with sensors, which can not only save time but can also diagnose a patient's physical condition in real time. Textile-based wearable sensors have recently been identified as detection platforms with high potential. They are developed for the real-time noninvasive detection of human physiological information to comprehensively analyze the health status of the human body. Sweat comprises various chemical compositions, which can be used as biomarkers to reflect the relevant information of the human physiology, thus providing references for health conditions. Combined together, textile-based sweat sensors are more flexible and comfortable than other conventional sensors, making them easily integrated into the wearable field. In this short review, the research progress of textile-based flexible sweat sensors was reviewed. Three mechanisms commonly used for textile-based sweat sensors were firstly contrasted with an introduction to their materials and preparation processes. The components of textile-based sweat sensors, which mainly consist of a sweat transportation channel and collector, a signal-selection unit, sensing elements and sensor integration and communication technologies, were reviewed. The applications of textile-based sweat sensors with different mechanisms were also presented. Finally, the existing problems and challenges of sweat sensors were summarized, which may contribute to promote their further development.

Recent Advances in Self-Powered Wearable Sensors Based on Piezoelectric and Triboelectric Nanogenerators

Early clinical diagnosis and treatment of disease rely heavily on measuring the many various types of medical information that are scattered throughout the body. Continuous and accurate monitoring of the human body is required in order to identify abnormal medical signals and to locate the factors that contribute to their occurrence in a timely manner. In order to fulfill this requirement, a variety of battery-free and self-powered methods of information collecting have been developed. For the purpose of a health monitoring system, this paper presents smart wearable sensors that are based on triboelectric nanogenerators (TENG) and piezoelectric nanogenerators (PENG), as well as hybrid nanogenerators that combine piezoelectric and triboelectric nanogenerators (PTNG). Following the presentation of the PENG and TENG principles, a summary and discussion of the most current developments in self-powered medical information sensors with a variety of purposes, structural designs, and electric performances follows. Wearable sensors that generate their own electricity are crucial not only for the proper development of children and patients with unique conditions, but for the purpose of maintaining checks on the wellbeing of the elderly and those who have recently recovered from illness, and for administering any necessary medical care. This work sought to do two things at once: provide perspectives for health monitoring, and open up new avenues for the analysis of long-distance biological movement status.

Triboelectric and Piezoelectric Nanogenerators for Self-Powered Healthcare Monitoring Devices: Operating Principles, Challenges, and Perspectives

The internet of medical things (IoMT) is used for the acquisition, processing, transmission, and storage of medical data of patients. The medical information of each patient can be monitored by hospitals, family members, or medical centers, providing real-time data on the health condition of patients. However, the IoMT requires monitoring healthcare devices with features such as being lightweight, having a long lifetime, wearability, flexibility, safe behavior, and a stable electrical performance. For the continuous monitoring of the medical signals of patients, these devices need energy sources with a long lifetime and stable response. For this challenge, conventional batteries have disadvantages due to their limited-service time, considerable weight, and toxic materials. A replacement alternative to conventional batteries can be achieved for piezoelectric and triboelectric nanogenerators. These nanogenerators can convert green energy from various environmental sources (e.g., biomechanical energy, wind, and mechanical vibrations) into electrical energy. Generally, these nanogenerators have simple transduction mechanisms, uncomplicated manufacturing processes, are lightweight, have a long lifetime, and provide high output electrical performance. Thus, the piezoelectric and triboelectric nanogenerators could power future medical devices that monitor and process vital signs of patients. Herein, we review the working principle, materials, fabrication processes, and signal processing components of piezoelectric and triboelectric nanogenerators with potential medical applications. In addition, we discuss the main components and output electrical performance of various nanogenerators applied to the medical sector. Finally, the challenges and perspectives of the design, materials and fabrication process, signal processing, and reliability of nanogenerators are included.

3D designed battery-free wireless origami pressure sensor

A pressure monitoring structure is a very useful element for a wearable device for health monitoring and sports biomechanics. While pressure sensors have been studied extensively, battery-free functions working in wireless detection have not been studied much. Here, we report a 3D-structured origami-based architecture sensor for wireless pressure monitoring. We developed an architectured platform for wireless pressure sensing through inductor-capacitor (LC) sensors and a monopole antenna. A personalized smart insole with Miura-ori origami designs has been 3D printed together with conductive 3D printed sensors seamlessly. Wireless monitoring of resonant frequency and intensity changes of LC sensors have been demonstrated to monitor foot pressure for different postures. The sensitivity of the wireless pressure sensor is tunable from 15.7 to 2.1 MHz/kPa in the pressure ranges from 0 to 9 kPa and from 10 to 40 kPa, respectively. The proposed wireless pressure-sensing platform can be utilized for various applications such as orthotics, prosthetics, and sports gear.

Bipolar Electrochemical Stimulation Using Conducting Polymers for Wireless Electroceuticals and Future Directions

Electrochemistry has become a powerful strategy to modulate cellular behavior and biological activity by manipulating electrical signals. Subsequent electrical stimulus-responsive conducting polymers (CPs) have advanced traditional wired electrochemical stimulation (ES) systems and developed wireless cell stimulation systems due to their electroconductivity, biocompatibility, stability, and flexibility. Bipolar electrochemistry (BPE), i.e., wireless electrochemistry, offers an effective pathway to modify wired ES systems into a desirable contactless mode, turning out a potential technique to offer fundamental insights into neural cell stimulation and neural network formation. This review commences with a brief discussion of the BPE technique and also the advantages of a bipolar electrochemical stimulation (BPES) system compared to traditional wired ES systems and other wireless ES systems. Then, the BPES system is elucidated through four aspects: the benefits of BPES, the key factors to establish BPES platforms for cell stimulation, the limits/barriers to overcome for current rigid materials in particular metals-based systems, and a brief overview of the concept proved by CPs-based systems. Furthermore, how to refine the existing BPES system from materials/devices modification that combine CP compositions with 3D fabrication/bioprinting technologies is elaborately discussed as well. Finally, the review ends together with future research directions, picturing the potential of BPES system in biomedical applications.

Biomechanics beyond the lab: Remote technology for osteoarthritis patient data-A scoping review

The objective of this project is to produce a review of available and validated technologies suitable for gathering biomechanical and functional research data in patients with osteoarthritis (OA), outside of a traditionally fixed laboratory setting. A scoping review was conducted using defined search terms across three databases (Scopus, Ovid MEDLINE, and PEDro), and additional sources of information from grey literature were added. One author carried out an initial title and abstract review, and two authors independently completed full-text screenings. Out of the total 5,164 articles screened, 75 were included based on inclusion criteria covering a range of technologies in articles published from 2015. These were subsequently categorised by technology type, parameters measured, level of remoteness, and a separate table of commercially available systems. The results concluded that from the growing number of available and emerging technologies, there is a well-established range in use and further in development. Of particular note are the wide-ranging available inertial measurement unit systems and the breadth of technology available to record basic gait spatiotemporal measures with highly beneficial and informative functional outputs. With the majority of technologies categorised as suitable for part-remote use, the number of technologies that are usable and fully remote is rare and they usually employ smartphone software to enable this. With many systems being developed for camera-based technology, such technology is likely to increase in usability and availability as computational models are being developed with increased sensitivities to recognise patterns of movement, enabling data collection in the wider environment and reducing costs and creating a better understanding of OA patient biomechanical and functional movement data.

Nondestructive Wafer Level MEMS Piezoelectric Device Thickness Detection

This paper introduces a novel nondestructive wafer scale thin film thickness measurement method by detecting the reflected picosecond ultrasonic wave transmitting between different interfacial layers. Unlike other traditional approaches used for thickness inspection, this method is highly efficient in wafer scale, and even works for opaque material. As a demonstration, we took scandium doped aluminum nitride (AlScN) thin film and related piezoelectric stacking layers (e.g. Molybedenum/AlScN/Molybdenum) as the case study to explain the advantages of this approach. In our experiments, a laser with a wavelength of 515 nm was used to first measure the thickness of (1) a single Molybdenum (Mo) electrode layer in the range of 100-300 nm, and (2) a single AlScN piezoelectric layer in the range of 600-1000 nm. Then, (3) the combined stacking layers were measured. Finally, (4) the thickness of a standard piezoelectric composite structure (Mo/AlScN/Mo) was characterized based on the conclusions and derivation extracted from the aforementioned sets of experiments. This type of standard piezoelectric composite has been widely adopted in a variety of Micro-electromechanical systems (MEMS) devices such as the Piezoelectric Micromachined Ultrasonic Transducer (PMUT), the Film Bulk Acoustic Resonator (FBAR), the Surface Acoustic Wave (SAW) and more. A comparison between measurement data from both in-line and off-line (using Scanning Electron Microscope) methods was conducted. The result from such in situ 8-inch wafer scale measurements was in a good agreement with the SEM data.

Kinetic energy harvesting based sensing and IoT systems: A review

The rapid advance of the Internet of Things (IoT) has attracted growing interest in academia and industry toward pervasive sensing and everlasting IoT. As the IoT nodes exponentially increase, replacing and recharging their batteries proves an incredible waste of labor and resources. Kinetic energy harvesting (KEH), converting the wasted ambient kinetic energy into usable electrical energy, is an emerging research field where various working mechanisms and designs have been developed for improved performance. Leveraging the KEH technologies, many motion-powered sensors, where changes in the external environment are directly converted into corresponding self-generated electrical signals, are developed and prove promising for multiple self-sensing applications. Furthermore, some recent studies focus on utilizing the generated energy to power a whole IoT sensing system. These systems comprehensively consider the mechanical, electrical, and cyber parts, which lead a further step to truly self-sustaining and maintenance-free IoT systems. Here, this review starts with a brief introduction of KEH from the ambient environment and human motion. Furthermore, the cutting-edge KEH-based sensors are reviewed in detail. Subsequently, divided into two aspects, KEH-based battery-free sensing systems toward IoT are highlighted. Moreover, there are remarks in every chapter for summarizing. The concept of self-powered sensing is clarified, and advanced studies of KEH-based sensing in different fields are introduced. It is expected that this review can provide valuable references for future pervasive sensing and ubiquitous IoT.

Effect of the Geometrical Structure on the Superhydrophobicity and Self-Cleaning Properties of Plasma-Treated Polyvinylidene Fluoride Fabrics

The purpose of this study is to develop superhydrophobic polyvinylidene fluoride (PVDF) fabrics to increase their water repellency and self-cleaning properties and to investigate the effects of the inherent fabric roughness on these properties. A PVDF fabric, composed entirely of electrospun PVDF filament yarns, and two PVDF/polyester (PET) fabrics with different weave densities are used. After treatment with O₂ plasma for 12 min and CF₄ plasma for 4 min, superhydrophobicity is achieved in all fabrics, resulting in an increase in water repellency and self-cleaning efficiency. The PVDF fabric with the lowest shedding angle exhibits the most pronounced droplet rebound behavior and the highest self-cleaning efficiency. Increases in surface inclination angle and droplet volume and a decrease in the drop fall height all contribute to conditions more favorable for water droplet repellency. The self-cleaning efficiencies of the plasma-treated PVDF fabric and high-density PVDF/PET fabric are higher for hydrophilic dust, in contrast to those of the untreated ones. The findings of this study are expected to enable the design of weaving or nano-structuring conditions that enhance the water repellency and self-cleaning properties of PVDF fabrics, for the development of stable energy-harvesting smart textiles.

Ultrahigh Performance Triboelectric Nanogenerator Enabled by Charge Transmission in Interfacial Lubrication and Potential Decentralization Design

Triboelectric nanogenerator (TENG) is a promising strategy for harvesting low frequency mechanical energy. However, the bottlenecks of limited electric output by air/dielectric breakdown and poor durability by material abrasion seriously restrict its further improvement. Herein, we propose a liquid lubrication promoted sliding mode TENG to address both issues. Liquid lubrication greatly reduces interface material abrasion, and its high breakdown strength and charge transmission effect further enhance device charge density. Besides, the potential decentralization design by the voltage balance bar effectively suppresses the dielectric breakdown. In this way, the average power density up to 87.26 W·m-2·Hz-1, energy conversion efficiency of 48%, and retention output of 90% after 500,000 operation cycles are achieved, which is the highest average power density and durability currently. Finally, a cell phone is charged to turn on by a palm-sized TENG device at 2 Hz within 25 s. This work has a significance for the commercialization of TENG-based self-powered systems.

Flexible Forearm Triboelectric Sensors for Parkinson's Disease Diagnosing and Monitoring

Existing approaches that assess and monitor the severity of Parkinson's Disease (PD) focus on the integration of wearable devices based on inertial sensors (accelerometers, gyroscopes) and electromyographic (EMG) transducers. Nevertheless, some of these sensors are bulky and lack comfortability. This manuscript presents triboelectric nanogenerators (TENGs) as an alternative stretchable sensor solution enabling PD monitoring systems. The prototype has been developed using a triboelectric sensor based on Ecoflex™ and PEDOT:PSS that is placed on the forearm. The movement of the skin above the forearm muscles and tendons correlates with the extension and flexion of fingers and hands. This way, the small gap of 0.5 cm between the polymer layers is displaced, generating voltage due to the triboelectric contact. Signals from preliminary experiments can discriminate different dynamics of emulated tremor and bradykinesia in hands and fingers. A modified version of the TS is integrated with a printed circuit board (PCB) in a single package with signal conditioning and wireless data transmission. The sensor platforms have demonstrated a good sensitivity to PD symptoms like bradykinesia and tremor based on the Unified Parkinson's Disease Rating Scale (MDS:UPDRS).

Recent Advances on Capacitive Proximity Sensors: From Design and Materials to Creative Applications

Capacitive proximity sensors (CPSs) have recently been a focus of increased attention because of their widespread applications, simplicity of design, low cost, and low power consumption. This mini review article provides a comprehensive overview of various applications of CPSs, as well as current advancements in CPS construction approaches. We begin by outlining the major technologies utilized in proximity sensing, highlighting their characteristics and applications, and discussing their advantages and disadvantages, with a heavy emphasis on capacitive sensors. Evaluating various nanocomposites for proximity sensing and corresponding detecting approaches ranging from physical to chemical detection are emphasized. The matrix and active ingredients used in such sensors, as well as the measured ranges, will also be discussed. A good understanding of CPSs is not only essential for resolving issues, but is also one of the primary forces propelling CPS technology ahead. We aim to examine the impediments and possible solutions to the development of CPSs. Furthermore, we illustrate how nanocomposite fusion may be used to improve the detection range and accuracy of a CPS while also broadening the application scenarios. Finally, the impact of conductance on sensor performance and other variables that impact the sensitivity distribution of CPSs are presented.

Advanced Implantable Biomedical Devices Enabled by Triboelectric Nanogenerators

Implantable biomedical devices (IMDs) play essential roles in healthcare. Subject to the limited battery life, IMDs cannot achieve long-term in situ monitoring, diagnosis, and treatment. The proposal and rapid development of triboelectric nanogenerators free IMDs from the shackles of batteries and spawn a self-powered healthcare system. This review aims to overview the development of IMDs based on triboelectric nanogenerators, divided into self-powered biosensors, in vivo energy harvesting devices, and direct electrical stimulation therapy devices. Meanwhile, future challenges and opportunities are discussed according to the development requirements of current-level self-powered IMDs to enhance output performance, develop advanced triboelectric nanogenerators with multifunctional materials, and self-driven close-looped diagnosis and treatment systems.

Progress of Advanced Devices and Internet of Things Systems as Enabling Technologies for Smart Homes and Health Care

In the Internet of Things (IoT) era, various devices (e.g., sensors, actuators, energy harvesters, etc.) and systems have been developed toward the realization of smart homes/buildings and personal health care. These advanced devices can be categorized into ambient devices and wearable devices based on their usage scenarios, to enable motion tracking, health monitoring, daily care, home automation, fall detection, intelligent interaction, assistance, living convenience, and security in smart homes. With the rapidly increasing number of such advanced devices and IoT systems, achieving fully self-sustained and multimodal intelligent systems is becoming more and more important to realize a sustainable and all-in-one smart home platform. Hence, in this Review, we systematically present the recent progress of the development of advanced materials, fabrication techniques, devices, and systems for enabling smart home and health care applications. First, advanced polymer, fiber, and fabric materials as well as their respective fabrication techniques for large-scale manufacturing are discussed. After that, functional devices classified into ambient devices (at home ambiance such as door, floor, table, chair, bed, toilet, window, wall, etc.) and wearable devices (on body parts such as finger, wrist, arm, throat, face, back, etc.) are presented for diverse monitoring and auxiliary applications. Next, the current developments of self-sustained systems and intelligent systems are reviewed in detail, indicating two promising research directions in this field. Last, conclusions and outlook pinpointed on the existing challenges and opportunities are provided for the research community to consider.

Synergistic Enhancement Properties of a Flexible Integrated PAN/PVDF Piezoelectric Sensor for Human Posture Recognition

The flexible pressure sensor has attracted much attention due to its wearable and conformal advantage. All the same, enhancing its electrical and structural properties is still a huge challenge. Herein, a flexible integrated pressure sensor (FIPS) composed of a solid silicone rubber matrix, composited with piezoelectric powers of polyacrylonitrile/Polyvinylidene fluoride (PAN/PVDF) and conductive silver-coated glass microspheres is first proposed. Specifically, the mass ratio of the PAN/PVDF and the rubber is up to 4:5 after mechanical mixing. The output voltage of the sensor with composite PAN/PVDF reaches 49 V, which is 2.57 and 3.06 times that with the single components, PAN and PVDF, respectively. In the range from 0 to 800 kPa, its linearity of voltage and current are all close to 0.986. Meanwhile, the sensor retains high voltage and current sensitivities of 42 mV/kPa and 0.174 nA/kPa, respectively. Furthermore, the minimum response time is 43 ms at a frequency range of 1-2.5 Hz in different postures, and the stability is verified over 10,000 cycles. In practical measurements, the designed FIPS showed excellent recognition abilities for various gaits and different bending degrees of fingers. This work provides a novel strategy to improve the flexible pressure sensor, and demonstrates an attractive potential in terms of human health and motion monitoring.

A Biodegradable and Recyclable Piezoelectric Sensor Based on a Molecular Ferroelectric Embedded in a Bacterial Cellulose Hydrogel

Currently, various electronic devices make our life more and more safe, healthy, and comfortable, but at the same time, they produce a large amount of nondegradable and nonrecyclable electronic waste that threatens our environment. In this work, we explore an environmentally friendly and flexible mechanical sensor that is biodegradable and recyclable. The sensor consists of a bacterial cellulose (BC) hydrogel as the matrix and imidazolium perchlorate (ImClO₄) molecular ferroelectric as the functional element, the hybrid of which possesses a high sensitivity of 4 mV kPa^-1 and a wide operational range from 0.2 to 31.25 kPa, outperforming those of most devices based on conventional functional biomaterials. Moreover, the BC hydrogel can be fully degraded into glucose and oligosaccharides, while ImClO₄ can be recyclable and reused for the same devices, leaving no environmentally hazardous electronic waste.

Self-Powered and Flexible Triboelectric Sensors with Oblique Morphology towards Smart Swallowing Rehabilitation Monitoring System

With aging, disability of the body can easily occur because the function of the body is degraded. Especially, swallowing disorder is regarded as a crucial issue because patients cannot obtain the nutrients from food by swallowing it. Hence, the rehabilitation of swallowing disorder is urgently required. However, the conventional device for swallowing rehabilitation has shown some limitations due to its external power source and internal circuit. Herein, a self-powered triboelectric nanogenerator for swallowing rehabilitation (TSR) is proposed. To increase the electrical output and pressure sensitivity of the TSR, the tilted reactive ion etching is conducted and the electrical output and pressure sensitivity are increased by 206% and 370%, respectively. The effect of the tilted reactive ion etching into the electrical output generated from the TSR is systematically analyzed. When the tongue is pressing, licking, and holding the TSR, each motion is successfully detected through the proposed TSR. Based on these results, the smart swallowing rehabilitation monitoring system (SSRMS) is implemented as the application and the SSRMS could successfully detect the pressing by the tongue. Considering these results, the SSRMS can be expected to be utilized as a promising smart swallowing rehabilitation monitoring system in near future.

Facile Approach to Enhance Electrical and Thermal Performance of Conducting Polymer PEDOT:PSS Films via Hot Pressing

This paper studies the impact of hot pressing on the electrical and thermal performance of thick (thickness >5 μm) conducting polymer poly(3,4-ethylene dioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films after acid treatment. Thick conducting polymer films usually exhibit low electrical and thermal conductivities similar to bulk polymer because charge and heat carriers are easily scattered by the irregular arrangement of crystalline domains inside the polymer. In this work, the in-plane electrical conductivity of thick hot-pressed PEDOT:PSS film exceeded 1500 S/cm, and 50% enhancement was obtained in comparison with its non-hot-pressed counterparts. Its in-plane thermal conductivity reached as high as 1.11 W/mK (improved by almost 100% compared to acid-treated PEDOT:PSS films), which is comparable to that of some commercial thermal pads. Such electrical and thermal enhancement via the hot-pressing process is attributed to the optimized morphology and microstructures, which provide short paths for thermal and electrical transportation. We have also demonstrated that the hot-pressed PEDOT:PSS films could be potentially utilized as a flexible conductor and heat spreader for application in flexible electronics and thermal management, respectively. This study not only offers a new insight into the process-property relationship for conducting polymers but also further enables the use of PEDOT:PSS films with simultaneously improved electrical and thermal performance in practical applications, such as thermal management for organic electrodes in batteries, flexible electronics, soft robotics, and bioelectronics.

A Self-Powered Wearable Motion Sensor for Monitoring Volleyball Skill and Building Big Sports Data

A novel self-powered wearable motion sensor for monitoring the spiking gesture of volleyball athletes has been manufactured from piezoelectric PVDF film. The PVDF film can convert body mechanical energy into electricity through the piezoelectric effect, and the flexible device can be conformably attached on the hand or arm. The sensor can work independently without power supply and actively output piezoelectric signals as the sports information. The sensor can detect the tiny and fine motion of spiking movement in playing volleyball, reflecting the skill. Additionally, the sensor can also real-time monitor the pulse changes and language during a volleyball match. The self-powered sensors can link to a wireless transmitter for uploading the sports information and building big sports data. This work can provoke a new direction for real-time sports monitoring and promote the development of big sports data.

Insole-Based Systems for Health Monitoring: Current Solutions and Research Challenges

Wearable health monitoring devices allow for measuring physiological parameters without restricting individuals' daily activities, providing information that is reflective of an individual's health and well-being. However, these systems need to be accurate, power-efficient, unobtrusive and simple to use to enable a reliable, convenient, automatic and ubiquitous means of long-term health monitoring. One such system can be embedded in an insole to obtain physiological data from the plantar aspect of the foot that can be analyzed to gain insight into an individual's health. This manuscript provides a comprehensive review of insole-based sensor systems that measure a variety of parameters useful for overall health monitoring, with a focus on insole-based PPD measurement systems developed in recent years. Existing solutions are reviewed, and several open issues are presented and discussed. The concept of a fully integrated insole-based health monitoring system and considerations for future work are described. By developing a system that is capable of measuring parameters such as PPD, gait characteristics, foot temperature and heart rate, a holistic understanding of an individual's health and well-being can be obtained without interrupting day-to-day activities. The proposed device can have a multitude of applications, such as for pathology detection, tracking medical conditions and analyzing gait characteristics.

Magnetic capsulate triboelectric nanogenerators

Triboelectric nanogenerators have received significant research attention in recent years. Structural design plays a critical role in improving the energy harvesting performance of triboelectric nanogenerators. Here, we develop the magnetic capsulate triboelectric nanogenerators (MC-TENG) for energy harvesting under undesirable mechanical excitations. The capsulate TENG are designed to be driven by an oscillation-triggered magnetic force in a holding frame to generate electrical power due to the principle of the freestanding triboelectrification. Experimental and numerical studies are conducted to investigate the electrical performance of MC-TENG under cyclic loading in three energy harvesting modes. The results indicate that the energy harvesting performance of the MC-TENG is significantly affected by the structure of the capsulate TENG. The copper MC-TENG systems are found to be the most effective design that generates the maximum mode of the voltage range is 4 V in the closed-circuit with the resistance of 10 GΩ. The proposed MC-TENG concept provides an effective method to harvest electrical energy from low-frequency and low-amplitude oscillations such as ocean wave.

An Integrated Self-Powered Real-Time Pedometer System with Ultrafast Response and High Accuracy

As accurate step counting is a critical indicator for exercise evaluation in daily life, pedometers give a quantitative prediction of steps and analyze the amount of exercise to regulate the exercise plan. However, the merchandized pedometers still suffer from limited battery life and low accuracy. In this work, an integrated self-powered real-time pedometer system has been demonstrated. The highly integrated system contains a porous triboelectric nanogenerator (P-TENG), a data acquisition and processing (DAQP) module, and a mobile phone APP. The P-TENG works as a pressure sensor that generates electrical signals synchronized with users' footsteps, and combining it with the analogue front-end (AFE) circuit yields an ultrafast response time of 8 ms. Moreover, the combination of a mini press-to-spin-type electromagnetic generator (EMG) and a supercapacitor enables a self-powered and self-sustained operation of the entire pedometer system. This work implements the regulation of TENG signals by electronic circuit design and proposes a highly integrated system. The improved reliability and practicality provide more possibilities for wearable self-powered electronic devices.

Artificial Intelligence-Enabled Caregiving Walking Stick Powered by Ultra-Low-Frequency Human Motion

The increasing population of the elderly and motion-impaired people brings a huge challenge to our social system. However, the walking stick as their essential tool has rarely been investigated into its potential capabilities beyond basic physical support, such as activity monitoring, tracing, and accident alert. Here, we report a walking stick powered by ultra-low-frequency human motion and equipped with deep-learning-enabled advanced sensing features to provide a healthcare-monitoring platform for motion-impaired users. A linear-to-rotary structure is designed to achieve highly efficient energy harvesting from the linear motion of a walking stick with ultralow frequency. Besides, two kinds of self-powered triboelectric sensors are proposed and integrated to extract the motion features of the walking stick. Augmented sensing functionalities with high accuracies have been enabled by deep-learning-based data analysis, including identity recognition, disability evaluation, and motion status distinguishing. Furthermore, a self-sustainable Internet of Things (IoT) system with global positioning system tracing and environmental temperature and humidity amenity sensing functions is obtained. Combined with the aforementioned functionalities, this walking stick is demonstrated in various usage scenarios as a caregiver for real-time well-being status and activity monitoring. The caregiving walking stick shows the potential of being an intelligent aid for motion-impaired users to help them live life with adequate autonomy and safety.

Machine-Learning-Aided Self-Powered Assistive Physical Therapy Devices

An expanding elderly population and people with disabilities pose considerable challenges to the current healthcare system. As a practical technology that integrates systems and services, assistive physical therapy devices are essential to maintain or to improve an individual's functioning and independence, thus promoting their well-being. Given technological advancements, core components of self-powered sensors and optimized machine-learning algorithms will play innovative roles in providing assistive services for unmet global needs. In this Perspective, we provide an overview of the latest developments in machine-learning-aided assistive physical therapy devices based on emerging self-powered sensing systems and a discussion of the challenges and opportunities in this field.

Electronic Textiles for Wearable Point-of-Care Systems

Traditional public health systems are suffering from limited, delayed, and inefficient medical services, especially when confronted with the pandemic and the aging population. Fusing traditional textiles with diagnostic, therapeutic, and protective medical devices can unlock electronic textiles (e-textiles) as point-of-care platform technologies on the human body, continuously monitoring vital signs and implementing round-the-clock treatment protocols in close proximity to the patient. This review comprehensively summarizes the research advances on e-textiles for wearable point-of-care systems. We start with a brief introduction to emphasize the significance of e-textiles in the current healthcare system. Then, we describe textile sensors for diagnosis, textile therapeutic devices for medical treatment, and textile protective devices for prevention, by highlighting their working mechanisms, representative materials, and clinical application scenarios. Afterward, we detail e-textiles' connection technologies as the gateway for real-time data transmission and processing in the context of 5G technologies and Internet of Things. Finally, we provide new insights into the remaining challenges and future directions in the field of e-textiles. Fueled by advances in chemistry and materials science, textile-based diagnostic devices, therapeutic devices, protective medical devices, and communication units are expected to interact synergistically to construct intelligent, wearable point-of-care textile platforms, ultimately illuminating the future of healthcare system in the Internet of Things era.

Recent Advances in Self-Powered Piezoelectric and Triboelectric Sensors: From Material and Structure Design to Frontier Applications of Artificial Intelligence

The development of artificial intelligence and the Internet of things has motivated extensive research on self-powered flexible sensors. The conventional sensor must be powered by a battery device, while innovative self-powered sensors can provide power for the sensing device. Self-powered flexible sensors can have higher mobility, wider distribution, and even wireless operation, while solving the problem of the limited life of the battery so that it can be continuously operated and widely utilized. In recent years, the studies on piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs) have mainly concentrated on self-powered flexible sensors. Self-powered flexible sensors based on PENGs and TENGs have been reported as sensing devices in many application fields, such as human health monitoring, environmental monitoring, wearable devices, electronic skin, human–machine interfaces, robots, and intelligent transportation and cities. This review summarizes the development process of the sensor in terms of material design and structural optimization, as well as introduces its frontier applications in related fields. We also look forward to the development prospects and future of self-powered flexible sensors.

Artificial Intelligence of Things (AIoT) Enabled Floor Monitoring System for Smart Home Applications

To enable smart homes and relative applications, the floor monitoring system with embedded triboelectric sensors has been proven as an effective paradigm to capture the ample sensory information from our daily activities, without the camera-associated privacy concerns. Yet the inherent limitations of triboelectric sensors such as high susceptibility to humidity and long-term stability remain a great challenge to develop a reliable floor monitoring system. Here we develop a robust and smart floor monitoring system through the synergistic integration of highly reliable triboelectric coding mats and deep-learning-assisted data analytics. Two quaternary coding electrodes are configured, and their outputs are normalized with respect to a reference electrode, leading to highly stable detection that is not affected by the ambient parameters and operation manners. Besides, due to the universal electrode pattern design, all the floor mats can be screen-printed with only one mask, rendering higher facileness and cost-effectiveness. Then a distinctive coding can be implemented to each floor mat through external wiring, which permits the parallel-array connection to minimize the output terminals and system complexity. Further integrating with deep-learning-assisted data analytics, a smart floor monitoring system is realized for various smart home monitoring and interactions, including position/trajectory tracking, identity recognition, and automatic controls. Hence, the developed low-cost, large-area, reliable, and smart floor monitoring system shows a promising advancement of floor sensing technology in smart home applications.

An Ultra-Sensitive Multi-Functional Optical Micro/Nanofiber Based on Stretchable Encapsulation

Stretchable optical fiber sensors (SOFSs), which are promising and ultra-sensitive next-generation sensors, have achieved prominent success in applications including health monitoring, robotics, and biological-electronic interfaces. Here, we report an ultra-sensitive multi-functional optical micro/nanofiber embedded with a flexible polydimethylsiloxane (PDMS) membrane, which is compatible with wearable optical sensors. Based on the effect of a strong evanescent field, the as-fabricated SOFS is highly sensitive to strain, achieving high sensitivity with a peak gauge factor of 450. In addition, considering the large negative thermo-optic coefficient of PDMS, temperature measurements in the range of 30 to 60 °C were realized, resulting in a 0.02 dBm/°C response. In addition, wide-range detection of humidity was demonstrated by a peak sensitivity of 0.5 dB/% RH, with less than 10% variation at each humidity stage. The robust sensing performance, together with the flexibility, enables the real-time monitoring of pulse, body temperature, and respiration. This as-fabricated SOFS provides significant potential for the practical application of wearable healthcare sensors.

Recent Progress in the Energy Harvesting Technology-From Self-Powered Sensors to Self-Sustained IoT, and New Applications

With the fast development of energy harvesting technology, micro-nano or scale-up energy harvesters have been proposed to allow sensors or internet of things (IoT) applications with self-powered or self-sustained capabilities. Facilitation within smart homes, manipulators in industries and monitoring systems in natural settings are all moving toward intellectually adaptable and energy-saving advances by converting distributed energies across diverse situations. The updated developments of major applications powered by improved energy harvesters are highlighted in this review. To begin, we study the evolution of energy harvesting technologies from fundamentals to various materials. Secondly, self-powered sensors and self-sustained IoT applications are discussed regarding current strategies for energy harvesting and sensing. Third, subdivided classifications investigate typical and new applications for smart homes, gas sensing, human monitoring, robotics, transportation, blue energy, aircraft, and aerospace. Lastly, the prospects of smart cities in the 5G era are discussed and summarized, along with research and application directions that have emerged.

Recent Progress in Self-Powered Sensors Based on Triboelectric Nanogenerators

The emergence of the Internet of Things (IoT) has subverted people's lives, causing the rapid development of sensor technologies. However, traditional sensor energy sources, like batteries, suffer from the pollution problem and the limited lifetime for powering widely implemented electronics or sensors. Therefore, it is essential to obtain self-powered sensors integrated with renewable energy harvesters. The triboelectric nanogenerator (TENG), which can convert the surrounding mechanical energy into electrical energy based on the surface triboelectrification effect, was born of this background. This paper systematically introduces the working principle of the TENG-based self-powered sensor, including the triboelectrification effect, Maxwell's displacement current, and quantitative analysis method. Meanwhile, this paper also reviews the recent application of TENG in different fields and summarizes the future development and current problems of TENG. We believe that there will be a rise of TENG-based self-powered sensors in the future.

Recent Advances on Conducting Polymers Based Nanogenerators for Energy Harvesting

With the rapid growth of numerous portable electronics, it is critical to develop high-performance, lightweight, and environmentally sustainable energy generation and power supply systems. The flexible nanogenerators, including piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG), are currently viable candidates for combination with personal devices and wireless sensors to achieve sustained energy for long-term working circumstances due to their great mechanical qualities, superior environmental adaptability, and outstanding energy-harvesting performance. Conductive materials for electrode as the critical component in nanogenerators, have been intensively investigated to optimize their performance and avoid high-cost and time-consuming manufacture processing. Recently, because of their low cost, large-scale production, simple synthesis procedures, and controlled electrical conductivity, conducting polymers (CPs) have been utilized in a wide range of scientific domains. CPs have also become increasingly significant in nanogenerators. In this review, we summarize the recent advances on CP-based PENG and TENG for biomechanical energy harvesting. A thorough overview of recent advancements and development of CP-based nanogenerators with various configurations are presented and prospects of scientific and technological challenges from performance to potential applications are discussed.

Textile-Based Mechanical Sensors: A Review

Innovations related to textiles-based sensors have drawn great interest due to their outstanding merits of flexibility, comfort, low cost, and wearability. Textile-based sensors are often tied to certain parts of the human body to collect mechanical, physical, and chemical stimuli to identify and record human health and exercise. Until now, much research and review work has been carried out to summarize and promote the development of textile-based sensors. As a feature, we focus on textile-based mechanical sensors (TMSs), especially on their advantages and the way they achieve performance optimizations in this review. We first adopt a novel approach to introduce different kinds of TMSs by combining sensing mechanisms, textile structure, and novel fabricating strategies for implementing TMSs and focusing on critical performance criteria such as sensitivity, response range, response time, and stability. Next, we summarize their great advantages over other flexible sensors, and their potential applications in health monitoring, motion recognition, and human-machine interaction. Finally, we present the challenges and prospects to provide meaningful guidelines and directions for future research. The TMSs play an important role in promoting the development of the emerging Internet of Things, which can make health monitoring and everyday objects connect more smartly, conveniently, and comfortably efficiently in a wearable way in the coming years.

Design, Manufacture and Test of Piezoelectric Cantilever-Beam Energy Harvesters with Hollow Structures

This article presents a single-crystal piezoelectric energy harvester (PEH) with a trapezoidal hollow hole that can obtain high energy density at low frequency. Harvesters with a hollow structure were fabricated through a series of manufacturing processes such as thermocompression bonding, screen printing and laser cutting. Finite element analysis (FEA) and experimental results showed that using low modulus brass instead of stainless steel as the PEH substrate enhances the voltage output of the device, and the hollow design greatly increases the overall stress level and power density. In addition, the developed PEH with a trapezoidal hole obtained the best output performance; when the acceleration, resonance frequency and matched load resistance were 0.5 g, 56.3 Hz and 114 kΩ, respectively, the peak voltage was 17 V and the power density was 2.52 mW/cm³. Meanwhile, compared with the unhollowed device, the peak voltage and maximum power density of the proposed PEH were increased by 30.7% and 24.4%, respectively, and the resonance frequency was reduced by 7%. This study verified the feasibility of the optimized design through simulation and experimental comparison.

AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove

Sign language recognition, especially the sentence recognition, is of great significance for lowering the communication barrier between the hearing/speech impaired and the non-signers. The general glove solutions, which are employed to detect motions of our dexterous hands, only achieve recognizing discrete single gestures (i.e., numbers, letters, or words) instead of sentences, far from satisfying the meet of the signers' daily communication. Here, we propose an artificial intelligence enabled sign language recognition and communication system comprising sensing gloves, deep learning block, and virtual reality interface. Non-segmentation and segmentation assisted deep learning model achieves the recognition of 50 words and 20 sentences. Significantly, the segmentation approach splits entire sentence signals into word units. Then the deep learning model recognizes all word elements and reversely reconstructs and recognizes sentences. Furthermore, new/never-seen sentences created by new-order word elements recombination can be recognized with an average correct rate of 86.67%. Finally, the sign language recognition results are projected into virtual space and translated into text and audio, allowing the remote and bidirectional communication between signers and non-signers.

M13 Virus Triboelectricity and Energy Harvesting

Triboelectrification is a phenomenon that generates electric potential upon contact. Here, we report a viral particle capable of generating triboelectric potential. M13 bacteriophage is exploited to fabricate precisely defined chemical and physical structures. By genetically engineering the charged structures, we observe that more negatively charged phages can generate higher triboelectric potentials and can diffuse the electric charges faster than less negatively charged phages can. The computational results show that the glutamate-engineered phages lower the LUMO energy level so that they can easily accept electrons from other materials upon contact. A phage-based triboelectric nanogenerator is fabricated and it could produce ∼76 V and ∼5.1 μA, enough to power 30 light-emitting diodes upon a mechanical force application. Our biotechnological approach will be useful to understand the electrical behavior of biomaterials, harvest mechanical energy, and provide a novel modality to detect desired viruses in the future.

Progress on Self-Powered Wearable and Implantable Systems Driven by Nanogenerators

With the rapid development of the internet of things (IoT), sustainable self-powered wireless sensory systems and diverse wearable and implantable electronic devices have surged recently. Under such an opportunity, nanogenerators, which can convert continuous mechanical energy into usable electricity, have been regarded as one of the critical technologies for self-powered systems, based on the high sensitivity, flexibility, and biocompatibility of piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs). In this review, we have thoroughly analyzed the materials and structures of wearable and implantable PENGs and TENGs, aiming to make clear how to tailor a self-power system into specific applications. The advantages in TENG and PENG are taken to effectuate wearable and implantable human-oriented applications, such as self-charging power packages, physiological and kinematic monitoring, in vivo and in vitro healing, and electrical stimulation. This review comprehensively elucidates the recent advances and future outlook regarding the human body's self-powered systems.

Progress in micro/nano sensors and nanoenergy for future AIoT-based smart home applications

Self-sustainable sensing systems composed of micro/nano sensors and nano-energy harvesters contribute significantly to developing the internet of things (IoT) systems. As one of the most promising IoT applications, smart home relies on implementing wireless sensor networks with miniaturized and multi-functional sensors, and distributed, reliable, and sustainable power sources, namely energy harvesters with a variety of conversion mechanisms. To extend the capabilities of IoT in the smart home, a technology fusion of IoT and artificial intelligence (AI), called the artificial intelligence of things (AIoT), enables the detection, analysis, and decision-making functions with the aids of machine learning assisted algorithms to form a smart home based intelligent system. In this review, we introduce the conventional rigid microelectromechanical system (MEMS) based micro/nano sensors and energy harvesters, followed by presenting the advances in the wearable counterparts for better human interactions. We then discuss the viable integration approaches for micro/nano sensors and energy harvesters to form self-sustainable IoT systems. Whereafter, we emphasize the recent development of AIoT based systems and the corresponding applications enabled by the machine learning algorithms. Smart home based healthcare technology enabled by the integrated multi-functional sensing platform and bioelectronic medicine is also presented as an important future direction, as well as wearable photonics sensing system as a complement to the wearable electronics sensing system.

Intelligent Polymers, Fibers and Applications

Intelligent materials, also known as smart materials, are capable of reacting to various external stimuli or environmental changes by rearranging their structure at a molecular level and adapting functionality accordingly. The initial concept of the intelligence of a material originated from the natural biological system, following the sensing–reacting–learning mechanism. The dynamic and adaptive nature, along with the immediate responsiveness, of the polymer- and fiber-based smart materials have increased their global demand in both academia and industry. In this manuscript, the most recent progress in smart materials with various features is reviewed with a focus on their applications in diverse fields. Moreover, their performance and working mechanisms, based on different physical, chemical and biological stimuli, such as temperature, electric and magnetic field, deformation, pH and enzymes, are summarized. Finally, the study is concluded by highlighting the existing challenges and future opportunities in the field of intelligent materials.

Fully Fabric-Based Triboelectric Nanogenerators as Self-Powered Human-Machine Interactive Keyboards

Combination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things. This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator (F-TENG) with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication. The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves. A self-powered wearable keyboard (SPWK) is also fabricated by integrating large-area F-TENG sensor arrays, which not only can trace and record electrophysiological signals, but also can identify individuals' typing characteristics by means of the Haar wavelet. Based on these merits, the SPWK has promising applications in the realm of wearable electronics, self-powered sensors, cyber security, and artificial intelligences.