Piezoelectric Dynamics of Arterial Pulse for Wearable Continuous Blood Pressure Monitoring

Advancements in Bio-Integrated Flexible Electronics for Hemodynamic Monitoring in Cardiovascular Healthcare

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, highlighting the urgent need for effective monitoring and prevention strategies. The rapid advancement of flexible sensing technology and the development of conformal sensors have attracted significant attention due to their potential for continuous, real-time assessment of cardiovascular health over extended periods. This review outlines recent advancements in bio-integrated flexible electronics designed for hemodynamic monitoring and broader CVD healthcare applications. It introduces key physiological indicators relevant to hemodynamics, including heart rate, blood pressure, blood flow velocity, and cardiac output. Next, it discusses flexible bio-integrated electronics engineering strategies, such as working principles and configuration designs. Various non-invasive and invasive bio-integrated devices for monitoring these hemodynamic indicators are then presented. Additionally, the review highlights the role of artificial intelligence algorithms and their practical applications in bio-integrated electronics for hemodynamic detection. Finally, it proposes future directions and addresses potential challenges in the field.

Wearable Mechanoluminescent Triboelectric Sensors for Real-Time Monitoring of Nighttime Sports Activities

Smart clothing that integrates active luminescence and motion monitoring holds significant importance for enhancing safety during nighttime activities. In this study, by combining mechanoluminescent materials (ZnS/Cu) with triboelectric nanogenerators, an intelligent yoga pant that actively emits light and senses joint movements during physical activities has been fabricated. The incorporation of silver fiber electrodes ensures breathability throughout the mechanoluminescent triboelectric sensor (MTS), contributing to the high comfort of wearable smart clothing. The doping of ZnS/Cu with organic silicone rubber enhances the dielectric constant of the triboelectric layer, thereby effectively enhancing the output signal of the MTS. Moreover, the mechanoluminescent materials convert the tension applied during joint flexion into dynamically varying light, alerting passing vehicles and safeguarding users during nighttime activities. An in-depth investigation was conducted on the relationship between the content of luminescent materials and the device's light intensity and output voltage under the same stretching conditions. The integration of a wearable signal acquisition system ensures real-time output of the electrical signals from the MTS during running, enabling online real-time monitoring of motion indicators such as joint bending angles and step counts. These findings provide feasible insights for the development of breathable, active luminescent smart clothing.

Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation

With advances in materials science and medical technology, wearable sensors have become crucial tools for the early diagnosis and continuous monitoring of numerous cardiovascular diseases, including arrhythmias, hypertension and coronary artery disease. These devices employ various sensing mechanisms, such as mechanoelectric, optoelectronic, ultrasonic and electrophysiological methods, to measure vital biosignals, including pulse rate, blood pressure and changes in heart rhythm. In this Review, we provide a comprehensive overview of the current state of wearable cardiovascular sensors, focusing particularly on those that measure blood pressure. We explore biosignal sensing principles, discuss blood pressure estimation methods (including machine learning algorithms) and summarize the latest advances in cuffless wearable blood pressure sensors. Finally, we highlight the challenges of and offer insights into potential pathways for the practical application of cuffless wearable blood pressure sensors in the medical field from both technical and clinical perspectives.

Recent Progress in Flexible Piezoelectric Tactile Sensors: Materials, Structures, Fabrication, and Application

Flexible tactile sensors are widely used in aerospace, medical and health monitoring, electronic skin, human-computer interaction, and other fields due to their unique advantages, thus becoming a research hotspot. The goal is to develop a flexible tactile sensor characterized by outstanding sensitivity, extensive detection range and linearity, elevated spatial resolution, and commendable adaptability. Among several strategies like capacitive, piezoresistive, and triboelectric tactile sensors, etc., we focus on piezoelectric tactile sensors because of their self-powered nature, high sensitivity, and quick response time. These sensors can respond to a wide range of dynamic mechanical stimuli and turn them into measurable electrical signals. This makes it possible to accurately detect objects, including their shapes and textures, and for them to sense touch in real time. This work encapsulates current advancements in flexible piezoelectric tactile sensors, focusing on enhanced material properties, optimized structural design, improved fabrication techniques, and broadened application domains. We outline the challenges facing piezoelectric tactile sensors to provide inspiration and guidance for their future development.

Advanced Morphological and Material Engineering for High-Performance Interfacial Iontronic Pressure Sensors

High-performance flexible pressure sensors are crucial for applications such as wearable electronics, interactive systems, and healthcare technologies. Among these, iontronic pressure sensors have garnered particular attention due to their superior sensitivity, enabled by the giant capacitance variation of the electric double layer (EDL) at the ionic-electronic interface under deformation. Key advancements, such as incorporating microstructures into ionic layers and employing diverse materials, have significantly improved sensor properties like sensitivity, accuracy, stability, and response time. This review highlights advancements in flexible EDL pressure sensors, focusing on structural designs and material engineering. These strategies are tailored to optimize key metrics such as sensitivity, detection limit, linearity, stability, response speed, hysteresis, transparency, wearability, selectivity, and multifunctionality. Key fabrication techniques, including micropatterning and externally assisted methods, are reviewed, along with strategies for sensor comparison and guidelines for selecting appropriate sensors. Emerging applications in healthcare, environmental and aerodynamic sensing, human-machine interaction, robotics, and machine learning-assisted intelligent sensing are explored. Finally, this review discusses the challenges and future directions for advancing EDL-based pressure sensors.

Artificial Intelligence-Enabled Novel Atrial Fibrillation Diagnosis System Using 3D Pulse Perception Flexible Pressure Sensor Array

Atrial fibrillation (AF) as one of the most common cardiovascular diseases has attracted great attention due to its high disability and mortality rate. Thus, a timely and effective recognition method for AF is of great importance for diagnosing and preventing it. Herein, we proposed a novel intelligent sensing and recognition system for AF which combined Traditional Chinese Medicine (TCM), flexible wearable electronic devices, and artificial intelligence. Experiment and simulation synergistically verified that the flexible pressure sensor arrays designed according to the TCM theory could synchronously obtain the 3D pulses at Cun, Guan, and Chi. Combined with a homemade signal acquisition system and the pulse signals labeled by doctors of cardiovascular diseases, the differences in the 3D pulse signals between ones with AF and without can be picked up clearly. Enabled the convolutional neural network (CNN) and the pulse database, the recognition model was formed with a recognition rate of up to 90%. As a proof of concept, the artificial intelligence-enabled novel atrial fibrillation diagnosis system has been used to detect patients with AF in hospitals, showing 80% recognition rate. This work provides a new strategy to precisely diagnose and remotely treat AF, as well as to accelerate the development of Modern Chinese Medicine treatment.

Phonocardiography based pulse wave velocity system for non-occlusive assessment of arterial stiffness

Arterial stiffness is strongly associated with vascular aging and pathology and can be assessed in many ways. Existing devices for measuring central arterial stiffness, such as carotid-femoral pulse wave velocity (PWV), are limited by high costs and the need for specialized expertise, limiting widespread clinical adoption. This study introduces a semi- and non-occlusive PWV measurement system using phonocardiography (PCG) and plethysmography (PPG) and a single femoral pressure cuff, aiming to address these limitations. We conducted a study comparing a semi-occlusive (carotid-femoral PWV) and a non-occlusive (carotid-toe PWV) PCG-based PWV measurements across a cohort of 63 volunteers, as compared to literature reference PWV values. Results demonstrated strong correlations between our PCG-based PWV measures (PWVcarotid-femoral: 8.42 ± 3.99 m/s vs. PWVcarotid-toe: 10.62 ± 3.86 m/s) with age as a significant predictor (PWVcarotid-femoral: r 2 = 0.45; PWVcarotid-toe: r 2 = 0.28, p < 0.05). Ultrasound measured distensibility assessments confirmed the reliability of our PCG approach in reflecting central arterial stiffness dynamics, particularly at the aortic level. Test-retest reliability analyses yielded high intraclass correlation coefficients (0.75 ≤ ICC ≤ 90), indicating robust repeatability of our method. This study highlights the feasibility and accuracy of our low-cost, semi and non-occlusive PWV measurement systems to enhance accessibility in arterial stiffness assessments, potentially easing cardiovascular risk stratification.

Dual-Mode Textile Sensor Based on PEDOT:PSS/SWCNTs Composites for Pressure-Temperature Detection

As an innovative branch of electronics, intelligent electronic textiles (e-textiles) have broad prospects in applications such as e-skin, human-computer interaction, and smart homes. However, it is still a challenge to distinguish multiple stimuli in the same e-textile. Herein, we propose a dual-parameter smart e-textile that can detect human pulse and body temperature in real time, with high performance and no signal interference. The doping of SWCNTs in PEDOT:PSS improves the electrical conductivity and Seebeck coefficient of the prepared composites, which results in excellent pressure and temperature-sensing properties of the PEDOT:PSS/SWCNTs/CS@PET-textile (PSCP) sensor. The dual-mode sensor has high sensitivity (32.4 kPa-1), fast response time (~21 ms), and excellent durability (>2000 times) in pressure detection. Concurrently, this sensor maintains a high Seebeck coefficient of 25 μV/K in the 0-120 K temperature range with a tremendous linear relationship. Based on impressive dual-mode sensing characteristics and independent temperature-difference- and pressure-sensing mechanisms, smart e-textile sensors realize the real-time simultaneous monitoring of weak pulse signals and human body temperature, showing great potential in medical healthcare. In addition, the potential energy is excited by the temperature gradient between the human skin and the environment, which provides a novel idea for wearable self-powered devices.

Enhancing cardiovascular health monitoring: Simultaneous multi-artery cardiac markers recording with flexible and bio-compatible AlN piezoelectric sensors

Continuous monitoring of cardiovascular parameters like pulse wave velocity (PWV), blood pressure wave (BPW), stiffness index (SI), reflection index (RI), mean arterial pressure (MAP), and cardio-ankle vascular index (CAVI) has significant clinical importance for the early diagnosis of cardiovascular diseases (CVDs). Standard approaches, including echocardiography, impedance cardiography, or hemodynamic monitoring, are hindered by expensive and bulky apparatus and accessibility only in specialized facilities. Moreover, noninvasive techniques like sphygmomanometry, electrocardiography, and arterial tonometry often lack accuracy due to external electrical interferences, artifacts produced by unreliable electrode contacts, misreading from placement errors, or failure in detecting transient issues and trends. Here, we report a bio-compatible, flexible, noninvasive, low-cost piezoelectric sensor for continuous and real-time cardiovascular monitoring. The sensor, utilizing a thin aluminum nitride film on a flexible Kapton substrate, is used to extract heart rate, blood pressure waves, pulse wave velocities, and cardio-ankle vascular index from four arterial pulse sites: carotid, brachial, radial, and posterior tibial arteries. This simultaneous recording, for the first time in the same experiment, allows to provide a comprehensive cardiovascular patient's health profile. In a test with a 28-year-old male subject, the sensor yielded the SI = 7.1 ± 0.2 m/s, RI = 54.4 ± 0.5 %, MAP = 86.2 ± 1.5 mmHg, CAVI = 7.8 ± 0.2, and seven PWVs from the combination of the four different arterial positions, in good agreement with the typical values reported in the literature. These findings make the proposed technology a powerful tool to facilitate personalized medical diagnosis in preventing CVDs.

Traditional Chinese Medicine (TCM)-Inspired Fully Printed Soft Pressure Sensor Array with Self-Adaptive Pressurization for Highly Reliable Individualized Long-Term Pulse Diagnostics

Reliable, non-invasive, continuous monitoring of pulse and blood pressure is essential for the prevention and diagnosis of cardiovascular diseases. However, the pulse wave varies drastically among individuals or even over time in the same individual, presenting significant challenges for the existing pulse sensing systems. Inspired by pulse diagnosis methods in traditional Chinese medicine (TCM), this work reports a self-adaptive pressure sensing platform (PSP) that combines the fully printed flexible pressure sensor array with an adaptive wristband-style pressure system can identify the optimal pulse signal. Besides the detected pulse rate/width/length, "Cun, Guan, Chi" position, and "floating, moderate, sinking" pulse features, the PSP combined with a machine learning-based linear regression model can also accurately predict blood pressure such as systolic, diastolic, and mean arterial pressure values. The developed diagnostic platform is demonstrated for highly reliable long-term monitoring and analysis of pulse and blood pressure across multiple human subjects over time. The design concept and proof-of-the-concept demonstrations also pave the way for the future developments of flexible sensing devices/systems for adaptive individualized monitoring in the complex practical environments for personalized medicine, along with the support for the development of digital TCM.

High piezoelectric property with exceptional stability in self-poled ferroelectric films

Ferroelectric films are highly sought-after in micro-electro-mechanical systems, particularly with the trend towards miniaturization. However, their tendency to depolarize and degradation in piezoelectric properties when exposed to packaging procedures at temperatures exceeding 260 °C remains a significant challenge. Here, we reveal the prerequisites for self-poling and leverage these insights to achieve unprecedented macroscopic performance through a two-step approach involving texture construction and hierarchical heterogeneity engineering. The significant [001] texture and fine Zr/Ti heterogeneity, facilitated by a PbO-TiO2 buffer, enable a piezoelectric charge coefficient of 550 pC/N in self-poled Pb(Zr0.52Ti0.48)O3 film. This material demonstrates impressive resilience to elevated temperatures up to 300 °C, experiencing less than a 16% degradation in performance. Our approach can be extended to other ferroelectric systems, offering an innovative solution for high-temperature packaging and harsh environments in practical electro-mechanical applications.

High‐Resolution Carbon‐Based Tactile Sensor Array for Dynamic Pulse Imaging

With the development of modern medicine, the importance of continuous and reliable pulse wave monitoring has increased significantly in physiological evaluation and disease diagnosis. Among them, the 3D reconstruction of the pulse wave is indispensable, and needs rely on ultra‐high resolution sensor arrays, that is, high spatial resolution, temporal resolution, and force resolution. Herein, a flexible high‐density 32 × 32 tactile sensor array based on pressure‐sensitive tunneling mechanism is develpoed. Conformal graphene nanowalls (GNWs) pattern arrays are deposited on micro‐pyramidal structural Si substrate via mask‐assisted plasma enhanced chemical vapor deposition (PECVD) method and are adopted as pressure‐sensitive electrode, exhibiting a spatial resolution of 64 dots/cm2, high sensitivity (222.36 kPa−1) and short response time (2 ms). More importantly, HfO2 tunneling layer can effectively suppress noise current, which made it sense weak pressure signals with 1/1000 force resolution and SNR of 36.32 dB. By leveraging its high‐resolution array, more holistic pulse signals are acquired and the 3D shape of the pulse wave are successfully replicated. This work shows high‐resolution sensors have significant promise for applications in remote intelligent diagnostics.

Flexible Temperature Sensor with High Reproducibility and Wireless Closed-Loop System for Decoupled Multimodal Health Monitoring and Personalized Thermoregulation

Temperature and pulse waves are two fundamental indicators of body health. Specifically, thermoresistive flexible temperature sensors are one of the most applied sensors. However, they suffer from poor reproducibility of resistivity; and decoupling temperature from pressure/strain is still challenging. Besides, autonomous thermoregulation by wearable sensory systems is in high demand, but conventional commercial apparatuses are cumbersome and not suitable for long-term portable use. Here, a material-design strategy is developed to overcome the problem of poor reproducibility of resistivity by tuning the thermal expansion coefficient to nearly zero, precluding the detriment caused by shape expansion/shrinkage with temperature variation and achieving high reproducibility. The strategy also obtains more reliable sensitivity and higher stability, and the designed thermoresistive fiber has strain-insensitive sensing performance and fast response/recovery time. A smart textile woven by the thermoresistive fiber can decouple temperature and pulse without crosstalk; and a flexible wireless closed-loop system comprising the smart textile, a heating textile, a flexible diminutive control patch, and a smartphone is designed and constructed to monitor health status in real-time and autonomously regulate body temperature. This work offers a new route to circumvent temperature-sensitive effects for flexible sensors and new insights for personalized thermoregulation.

Flexible piezoelectric materials and strain sensors for wearable electronics and artificial intelligence applications

With the rapid development of artificial intelligence, the applications of flexible piezoelectric sensors in health monitoring and human-machine interaction have attracted increasing attention. Recent advances in flexible materials and fabrication technologies have promoted practical applications of wearable devices, enabling their assembly in various forms such as ultra-thin films, electronic skins and electronic tattoos. These piezoelectric sensors meet the requirements of high integration, miniaturization and low power consumption, while simultaneously maintaining their unique sensing performance advantages. This review provides a comprehensive overview of cutting-edge research studies on enhanced wearable piezoelectric sensors. Promising piezoelectric polymer materials are highlighted, including polyvinylidene fluoride and conductive hydrogels. Material engineering strategies for improving sensitivity, cycle life, biocompatibility, and processability are summarized and discussed focusing on filler doping, fabrication techniques optimization, and microstructure engineering. Additionally, this review presents representative application cases of smart piezoelectric sensors in health monitoring and human-machine interaction. Finally, critical challenges and promising principles concerning advanced manufacture, biological safety and function integration are discussed to shed light on future directions in the field of piezoelectrics.

Ambient energy harvesters in wearable electronics: fundamentals, methodologies, and applications

In recent years, wearable sensor devices with exceptional portability and the ability to continuously monitor physiological signals in real time have played increasingly prominent roles in the fields of disease diagnosis and health management. This transformation has been largely facilitated by materials science and micro/nano-processing technologies. However, as this technology continues to evolve, the demand for multifunctionality and flexibility in wearable devices has become increasingly urgent, thereby highlighting the problem of stable and sustainable miniaturized power supplies. Here, we comprehensively review the current mainstream energy technologies for powering wearable sensors, including batteries, supercapacitors, solar cells, biofuel cells, thermoelectric generators, radio frequency energy harvesters, and kinetic energy harvesters, as well as hybrid power systems that integrate multiple energy conversion modes. In addition, we consider the energy conversion mechanisms, fundamental characteristics, and typical application cases of these energy sources across various fields. In particular, we focus on the crucial roles of different materials, such as nanomaterials and nano-processing techniques, for enhancing the performance of devices. Finally, the challenges that affect power supplies for wearable electronic products and their future developmental trends are discussed in order to provide valuable references and insights for researchers in related fields.

A Flexible Skin Bionic Thermally Comfortable Wearable for Machine Learning-Facilitated Ultrasensitive Sensing

Tremendous popularity is observed for multifunctional flexible electronics with appealing applications in intelligent electronic skins, human-machine interfaces, and healthcare sensing. However, the reported sensing electronics, mostly can hardly provide ultrasensitive sensing sensitivity, wider sensing range, and robust cycling stability simultaneously, and are limited of efficient heat conduction out from the contacted skin interface after wearing flexible electronics on human skin to satisfy thermal comfort of human skin. Inspired from the ultrasensitive tactile perception microstructure (epidermis/spinosum/signal transmission) of human skin, a flexible comfortably wearable ultrasensitive electronics is hereby prepared from thermal conductive boron nitride nanosheets-incorporated polyurethane elastomer matrix with MXene nanosheets-coated surface microdomes as epidermis/spinosum layers assembled with interdigitated electrode as sensing signal transmission layer. It demonstrates appealing sensing performance with ultrasensitive sensitivity (≈288.95 kPa-1), up to 300 kPa sensing range, and up to 20 000 sensing cycles from obvious contact area variation between microdome microstructures and the contact electrode under external compression. Furthermore, the bioinspired electronics present advanced thermal management by timely efficient thermal dissipation out from the contacted skin surface to meet human skin thermal comfort with the incorporated thermal conductive boron nitride nanosheets. Thus, it is vitally promising in wearable artificial electronic skins, intelligent human-interactive sensing, and personal health management.

Electronic Skin for Health Monitoring Systems: Properties, Functions, and Applications

Electronic skin (e-skin), a skin-like wearable electronic device, holds great promise in the fields of telemedicine and personalized healthcare because of its good flexibility, biocompatibility, skin conformability, and sensing performance. E-skin can monitor various health indicators of the human body in real time and over the long term, including physical indicators (exercise, respiration, blood pressure, etc.) and chemical indicators (saliva, sweat, urine, etc.). In recent years, the development of various materials, analysis, and manufacturing technologies has promoted significant development of e-skin, laying the foundation for the application of next-generation wearable medical technologies and devices. Herein, the properties required for e-skin health monitoring devices to achieve long-term and precise monitoring and summarize several detectable indicators in the health monitoring field are discussed. Subsequently, the applications of integrated e-skin health monitoring systems are reviewed. Finally, current challenges and future development directions in this field are discussed. This review is expected to generate great interest and inspiration for the development and improvement of e-skin and health monitoring systems.

Biodegradable Ferroelectric Molecular Plastic Crystal HOCH2(CF2)7CH2OH Structurally Inspired by Polyvinylidene Fluoride

Ferroelectric materials, traditionally comprising inorganic ceramics and polymers, are commonly used in medical implantable devices. However, their nondegradable nature often necessitates secondary surgeries for removal. In contrast, ferroelectric molecular crystals have the advantages of easy solution processing, lightweight, and good biocompatibility, which are promising candidates for transient (short-term) implantable devices. Despite these benefits, the discovered biodegradable ferroelectric materials remain limited due to the absence of efficient design strategies. Here, inspired by the polar structure of polyvinylidene fluoride (PVDF), a ferroelectric molecular crystal 1H,1H,9H,9H-perfluoro-1,9-nonanediol (PFND), which undergoes a cubic-to-monoclinic ferroelectric plastic phase transition at 339 K, is discovered. This transition is facilitated by a 2D hydrogen bond network formed through O-H···O interactions among the oriented PFND molecules, which is crucial for the manifestation of ferroelectric properties. In this sense, by reducing the number of -CF2- groups from ≈5 000 in PVDF to seven in PFND, it is demonstrated that this ferroelectric compound only needs simple solution processing while maintaining excellent biosafety, biocompatibility, and biodegradability. This work illuminates the path toward the development of new biodegradable ferroelectric molecular crystals, offering promising avenues for biomedical applications.

Recent Advances in Materials, Devices and Algorithms Toward Wearable Continuous Blood Pressure Monitoring

Continuous blood pressure (BP) tracking provides valuable insights into the health condition and functionality of the heart, arteries, and overall circulatory system of humans. The rapid development in flexible and wearable electronics has significantly accelerated the advancement of wearable BP monitoring technologies. However, several persistent challenges, including limited sensing capabilities and stability of flexible sensors, poor interfacial stability between sensors and skin, and low accuracy in BP estimation, have hindered the progress in wearable BP monitoring. To address these challenges, comprehensive innovations in materials design, device development, system optimization, and modeling have been pursued to improve the overall performance of wearable BP monitoring systems. In this review, we highlight the latest advancements in flexible and wearable systems toward continuous noninvasive BP tracking with a primary focus on materials development, device design, system integration, and theoretical algorithms. Existing challenges, potential solutions, and further research directions are also discussed to provide theoretical and technical guidance for the development of future wearable systems in continuous ambulatory BP measurement with enhanced sensing capability, robustness, and long-term accuracy.

Wireless Technologies in Flexible and Wearable Sensing: From Materials Design, System Integration to Applications

Wireless and wearable sensors attract considerable interest in personalized healthcare by providing a unique approach for remote, noncontact, and continuous monitoring of various health-related signals without interference with daily life. Recent advances in wireless technologies and wearable sensors have promoted practical applications due to their significantly improved characteristics, such as reduction in size and thickness, enhancement in flexibility and stretchability, and improved conformability to the human body. Currently, most researches focus on active materials and structural designs for wearable sensors, with just a few exceptions reflecting on the technologies for wireless data transmission. This review provides a comprehensive overview of the state-of-the-art wireless technologies and related studies on empowering wearable sensors. The emerging functional nanomaterials utilized for designing unique wireless modules are highlighted, which include metals, carbons, and MXenes. Additionally, the review outlines the system-level integration of wireless modules with flexible sensors, spanning from novel design strategies for enhanced conformability to efficient transmitting data wirelessly. Furthermore, the review introduces representative applications for remote and noninvasive monitoring of physiological signals through on-skin and implantable wireless flexible sensing systems. Finally, the challenges, perspectives, and unprecedented opportunities for wireless and wearable sensors are discussed.

Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise

(1) Background: The objective of this study was to predict the vascular health status of elderly women during exercise using pulse wave data and Temporal Convolutional Neural Networks (TCN); (2) Methods: A total of 492 healthy elderly women aged 60-75 years were recruited for the study. The study utilized a cross-sectional design. Vascular endothelial function was assessed non-invasively using Flow-Mediated Dilation (FMD). Pulse wave characteristics were quantified using photoplethysmography (PPG) sensors, and motion-induced noise in the PPG signals was mitigated through the application of a recursive least squares (RLS) adaptive filtering algorithm. A fixed-load cycling exercise protocol was employed. A TCN was constructed to classify flow-mediated dilation (FMD) into "optimal", "impaired", and "at risk" levels; (3) Results: TCN achieved an average accuracy of 79.3%, 84.8%, and 83.2% in predicting FMD at the "optimal", "impaired", and "at risk" levels, respectively. The results of the analysis of variance (ANOVA) comparison demonstrated that the accuracy of the TCN in predicting FMD at the impaired and at-risk levels was significantly higher than that of Long Short-Term Memory (LSTM) networks and Random Forest algorithms; (4) Conclusions: The use of pulse wave data during exercise combined with the TCN for predicting the vascular health status of elderly women demonstrated high accuracy, particularly in predicting impaired and at-risk FMD levels. This indicates that the integration of exercise pulse wave data with TCN can serve as an effective tool for the assessment and monitoring of the vascular health of elderly women.

Electrostatic Smart Textiles for Braille-To-Speech Translation

A wearable Braille-to-speech translation system is of great importance for providing auditory feedback in assisting blind people and people with speech impairment. However, previous reported Braille-to-speech translation systems still need to be improved in terms of comfortability or integration. Here, a Braille-to-speech translation system that uses dual-functional electrostatic transducers which are made of fabric-based materials and can be integrated into textiles is reported. Based on electrostatic induction, the electrostatic transducer can either serve as a tactile sensor or a loudspeaker with the same design. The proposed electrostatic transducers have excellent output performances, mechanical robustness, and working stability. By combining the devices with machine learning algorithms, it is possible to translate the Braille alphabet and 40 commonly used words (extensible) into speech with an accuracy of 99.09% and 97.08%, respectively. This work demonstrates a new approach for further developments of advanced assistive technology toward improving the lives of disabled people.

Hierarchical Piezoelectric Composites for Noninvasive Continuous Cardiovascular Monitoring

Continuous monitoring of blood pressure (BP) and multiparametric analysis of cardiac functions are crucial for the early diagnosis and therapy of cardiovascular diseases. However, existing monitoring approaches often suffer from bulky and intrusive apparatus, cumbersome testing procedures, and challenging data processing, hampering their applications in continuous monitoring. Here, a heterogeneously hierarchical piezoelectric composite is introduced for wearable continuous BP and cardiac function monitoring, overcoming the rigidity of ceramic and the insensitivity of polymer. By optimizing the hierarchical structure and components of the composite, the developed piezoelectric sensor delivers impressive performances, ensuring continuous and accurate monitoring of BP at Grade A level. Furthermore, the hemodynamic parameters are extracted from the detected signals, such as local pulse wave velocity, cardiac output, and stroke volume, all of which are in alignment with clinical results. Finally, the all-day tracking of cardiac function parameters validates the reliability and stability of the developed sensor, highlighting its potential for personalized healthcare systems, particularly in early diagnosis and timely intervention of cardiovascular disease.

Sweat permeable and ultrahigh strength 3D PVDF piezoelectric nanoyarn fabric strain sensor

Commercial wearable piezoelectric sensors possess excellent anti-interference stability due to their electronic packaging. However, this packaging renders them barely breathable and compromises human comfort. To address this issue, we develop a PVDF piezoelectric nanoyarns with an ultrahigh strength of 313.3 MPa, weaving them with different yarns to form three-dimensional piezoelectric fabric (3DPF) sensor using the advanced 3D textile technology. The tensile strength (46.0 MPa) of 3DPF exhibits the highest among the reported flexible piezoelectric sensors. The 3DPF features anti-gravity unidirectional liquid transport that allows sweat to move from the inner layer near to the skin to the outer layer in 4 s, resulting in a comfortable and dry environment for the user. It should be noted that sweating does not weaken the piezoelectric properties of 3DPF, but rather enhances. Additionally, the durability and comfortability of 3DPF are similar to those of the commercial cotton T-shirts. This work provides a strategy for developing comfortable flexible wearable electronic devices.

A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections

Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health assessments, with the precise forecasting of continuous blood pressure assuming a critical role in both preventing and treating cardiovascular diseases. This study proposes a novel continuous non-invasive blood pressure prediction model, DSRUnet, based on deep sparse residual U-net combined with improved SE skip connections, which aim to enhance the accuracy of using photoplethysmography (PPG) signals for continuous blood pressure prediction. The model first introduces a sparse residual connection approach for path contraction and expansion, facilitating richer information fusion and feature expansion to better capture subtle variations in the original PPG signals, thereby enhancing the network's representational capacity and predictive performance and mitigating potential degradation in the network performance. Furthermore, an enhanced SE-GRU module was embedded in the skip connections to model and weight global information using an attention mechanism, capturing the temporal features of the PPG pulse signals through GRU layers to improve the quality of the transferred feature information and reduce redundant feature learning. Finally, a deep supervision mechanism was incorporated into the decoder module to guide the lower-level network to learn effective feature representations, alleviating the problem of gradient vanishing and facilitating effective training of the network. The proposed DSRUnet model was trained and tested on the publicly available UCI-BP dataset, with the average absolute errors for predicting systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) being 3.36 ± 6.61 mmHg, 2.35 ± 4.54 mmHg, and 2.21 ± 4.36 mmHg, respectively, meeting the standards set by the Association for the Advancement of Medical Instrumentation (AAMI), and achieving Grade A according to the British Hypertension Society (BHS) Standard for SBP and DBP predictions. Through ablation experiments and comparisons with other state-of-the-art methods, the effectiveness of DSRUnet in blood pressure prediction tasks, particularly for SBP, which generally yields poor prediction results, was significantly higher. The experimental results demonstrate that the DSRUnet model can accurately utilize PPG signals for real-time continuous blood pressure prediction and obtain high-quality and high-precision blood pressure prediction waveforms. Due to its non-invasiveness, continuity, and clinical relevance, the model may have significant implications for clinical applications in hospitals and research on wearable devices in daily life.

Recent developments in wearable piezoelectric energy harvesters

Wearable piezoelectric energy harvesters (WPEHs) have gained popularity and made significant development in recent decades. The harvester is logically built by the movement patterns of various portions of the human body to harvest the movement energy and immediately convert it into usable electrical energy. To directly power different microelectronic devices on the human body, a self-powered device that does not require an additional power supply is being created. This Review provides an in-depth review of WPEHs, explaining the fundamental concepts of piezoelectric technology and the materials employed in numerous widely used piezoelectric components. The harvesters are classed according to the movement characteristics of several portions of a person's body, such as pulses, joints, skin, and shoes (feet). Each technique is introduced, followed by extensive analysis. Some harvesters are compared, and the benefits and drawbacks of each technique are discussed. Finally, this Review presents future goals and objectives for WPEH improvement, and it will aid researchers in understanding WPEH to the point of more efficient wireless energy delivery to wearable electronic components.

E-Tattoos: Toward Functional but Imperceptible Interfacing with Human Skin

The human body continuously emits physiological and psychological information from head to toe. Wearable electronics capable of noninvasively and accurately digitizing this information without compromising user comfort or mobility have the potential to revolutionize telemedicine, mobile health, and both human-machine or human-metaverse interactions. However, state-of-the-art wearable electronics face limitations regarding wearability and functionality due to the mechanical incompatibility between conventional rigid, planar electronics and soft, curvy human skin surfaces. E-Tattoos, a unique type of wearable electronics, are defined by their ultrathin and skin-soft characteristics, which enable noninvasive and comfortable lamination on human skin surfaces without causing obstruction or even mechanical perception. This review article offers an exhaustive exploration of e-tattoos, accounting for their materials, structures, manufacturing processes, properties, functionalities, applications, and remaining challenges. We begin by summarizing the properties of human skin and their effects on signal transmission across the e-tattoo-skin interface. Following this is a discussion of the materials, structural designs, manufacturing, and skin attachment processes of e-tattoos. We classify e-tattoo functionalities into electrical, mechanical, optical, thermal, and chemical sensing, as well as wound healing and other treatments. After discussing energy harvesting and storage capabilities, we outline strategies for the system integration of wireless e-tattoos. In the end, we offer personal perspectives on the remaining challenges and future opportunities in the field.

High Signal to Noise Ratio Piezoelectric Thin Film Sensor Based on Elastomer Amplification for Ambulatory Blood Pressure Monitoring

Continuous pulse wave detection can be used for monitoring and diagnosing cardiovascular diseases, and research on pulse sensing based on piezoelectric thin films is one of the hot spots. Usually, piezoelectric thin films do not come into direct contact with the skin and need to be connected through a layer of an elastic medium. Most views think that the main function of this layer of elastic medium is to increase the adhesion between the sensor component and the skin, but there is little discussion about the impact of the elastic medium on pulse vibration transmission. Here, we conducted a detailed study on the effects of Young's modulus and the thickness of elastic media on pulse sensing signals. The results show that the waveform amplitude of the piezoelectric sensing signal decreases with the increase of Young's modulus and thickness of the elastic medium. Then, we constructed a theoretical model of the influence of elastic media on pulse wave propagation. The amplitude of the pulse wave signal detected by the optimized sensor was increased to 480%. Our research shows that by regulating Young's modulus and thickness of elastic media, pulse wave signals can undergo a similar amplification effect, which has an important theoretical reference value for achieving ambulatory blood pressure monitoring based on high-quality pulse waves.

Flexible temperature-pressure dual sensor based on 3D spiral thermoelectric Bi2Te3 films

Dual-parameter pressure-temperature sensors are widely employed in personal health monitoring and robots to detect external signals. Herein, we develop a flexible composite dual-parameter pressure-temperature sensor based on three-dimensional (3D) spiral thermoelectric Bi2Te3 films. The film has a (000l) texture and good flexibility, exhibiting a maximum Seebeck coefficient of -181 μV K-1 and piezoresistance gauge factor of approximately -9.2. The device demonstrates a record-high temperature-sensing performance with a high sensing sensitivity (-426.4 μV K-1) and rapid response time (~0.95 s), which are better than those observed in most previous studies. In addition, owing to the piezoresistive effect in the Bi2Te3 film, the 3D-spiral deviceexhibits significant pressure-response properties with a pressure-sensing sensitivity of 120 Pa-1. This innovative approach achieves high-performance dual-parameter sensing using one kind of material with high flexibility, providing insight into the design and fabrication of many applications, such as e-skin.

Multifunctional, Degradable Wearable Sensors Prepared with an Initiator and Crosslinker-Free Method

The present zwitterionic hydrogel-based wearable sensor exhibits various limitations, such as limited degradation capacity, unavoidable toxicity resulting from initiators, and poor mechanical properties that cannot satisfy practical demands. Herein, we present an initiator and crosslinker-free approach to prepare polyethylene glycol (PEG)@poly[2-(methacryloyloxy)ethyl] dimethyl-(3-sulfopropyl) (PSBMA) interpenetrating polymer network (IPN) hydrogels that are self-polymerized via sunlight-induced and non-covalent crosslinking through electrostatic interaction and hydrogen bonding among polymer chains. The PEG@PSBMA IPN hydrogel possesses tissue-like softness, superior stretchability (∼2344.6% elongation), enhanced fracture strength (∼39.5 kPa), excellent biocompatibility, antibacterial property, reliable adhesion, and ionic conductivity. Furthermore, the sensor based on the IPN hydrogel demonstrates good sensitivity and cyclic stability, enabling effective real-time monitoring of human body activities. Moreover, it is worth noting that the excellent degradability in the saline solution within 8 h makes the prepared hydrogel-based wearable sensor free from the electronic device contamination. We believe that the proposed strategy for preparing physical zwitterionic hydrogels will pave the way for fabricating eco-friendly wearable devices.

Deep-learning enabled smart insole system aiming for multifunctional foot-healthcare applications

Real-time foot pressure monitoring using wearable smart systems, with comprehensive foot health monitoring and analysis, can enhance quality of life and prevent foot-related diseases. However, traditional smart insole solutions that rely on basic data analysis methods of manual feature extraction are limited to real-time plantar pressure mapping and gait analysis, failing to meet the diverse needs of users for comprehensive foot healthcare. To address this, we propose a deep learning-enabled smart insole system comprising a plantar pressure sensing insole, portable circuit board, deep learning and data analysis blocks, and software interface. The capacitive sensing insole can map both static and dynamic plantar pressure with a wide range over 500 kPa and excellent sensitivity. Statistical tools are used to analyze long-term foot pressure usage data, providing indicators for early prevention of foot diseases and key data labels for deep learning algorithms to uncover insights into the relationship between plantar pressure patterns and foot issues. Additionally, a segmentation method assisted deep learning model is implemented for exercise-fatigue recognition as a proof of concept, achieving a high classification accuracy of 95%. The system also demonstrates various foot healthcare applications, including daily activity statistics, exercise injury avoidance, and diabetic foot ulcer prevention.

Tough, Antifreezing, and Piezoelectric Organohydrogel as a Flexible Wearable Sensor for Human-Machine Interaction

Piezoelectric hydrogel sensors are becoming increasingly popular for wearable sensing applications due to their high sensitivity, self-powered performance, and simple preparation process. However, conventional piezoelectric hydrogels lack antifreezing properties and are thus confronted with the liability of rupture in low temperatures owing to the use of water as the dispersion medium. Herein, a kind of piezoelectric organohydrogel that integrates piezoelectricity, low-temperature tolerance, mechanical robustness, and stable electrical performance is reported by using poly(vinylidene fluoride) (PVDF), acrylonitrile (AN), acrylamide (AAm), p-styrenesulfonate (NaSS), glycerol, and zinc chloride. In detail, the dipolar interaction of the PVDF chain with the PAN chain facilitates the crystal phase transition of PVDF from the α to β phase, which endows the organohydrogels with a high piezoelectric constant d33 of 35 pC/N. In addition, the organohydrogels are highly ductile and can withstand significant tensile and compressive forces through the synergy of the dipolar interaction and amide hydrogen bonding. Besides, by incorporating glycerol and zinc chloride, the growth of ice crystals is inhibited, allowing the organohydrogels to maintain stable flexibility and sensitivity even at -20 °C. The real-time monitoring of the pulse signal for up to 2 min indicates that the gel sensor has stable sensitivity. It is believed that our organohydrogels will have good prospects in future wearable electronics.

Unconstrained Piezoelectric Vascular Electronics for Wireless Monitoring of Hemodynamics and Cardiovascular Health

The patient-centered healthcare requires timely disease diagnosis and prognostic assessment, calling for individualized physiological monitoring. To assess the postoperative hemodynamic status of patients, implantable blood flow monitoring devices are highly expected to deliver real time, long-term, sensitive, and reliable hemodynamic signals, which can accurately reflect multiple physiological conditions. Herein, an implantable and unconstrained vascular electronic system based on a piezoelectric sensor immobilized is presented by a "growable" sheath around continuously growing arterial vessels for real-timely and wirelessly monitoring of hemodynamics. The piezoelectric sensor made of circumferentially aligned polyvinylidene fluoride nanofibers around pulsating artery can sensitively perceive mechanical signals, and the growable sheath bioinspired by the structure and function of leaf sheath has elasticity and conformal shape adaptive to the dynamically growing arterial vessels to avoid growth constriction. With this integrated and smart design, long-term, wireless, and sensitive monitoring of hemodynamics are achieved and demonstrated in rats and rabbits. It provides a simple and versatile strategy for designing implantable sensors in a less invasive way.

Implantable Flexible Sensors for Health Monitoring

Flexible sensors, as a significant component of flexible electronics, have attracted great interest the realms of human-computer interaction and health monitoring due to their high conformability, adjustable sensitivity, and excellent durability. In comparison to wearable sensor-based in vitro health monitoring, the use of implantable flexible sensors (IFSs) for in vivo health monitoring offers more accurate and reliable vital sign information due to their ability to adapt and directly integrate with human tissue. IFSs show tremendous promise in the field of health monitoring, with unique advantages such as robust signal reading capabilities, lightweight design, flexibility, and biocompatibility. Herein, a review of IFSs for vital signs monitoring is detailly provided, highlighting the essential conditions for in vivo applications. As the prerequisites of IFSs, the stretchability and wireless self-powered properties of the sensor are discussed, with a special attention paid to the sensing materials which can maintain prominent biosafety (i.e., biocompatibility, biodegradability, bioresorbability). Furthermore, the applications of IFSs monitoring various parts of the body are described in detail, with a summary in brain monitoring, eye monitoring, and blood monitoring. Finally, the challenges as well as opportunities in the development of next-generation IFSs are presented.

Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring

A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since the correlations of pulse waveforms to BP are highly individualized due to the diversity of the patients' physiological characteristics, wearable sensors based on universal designs and algorithms often fail to derive BP accurately when applied on individual patients. Herein, a wearable triboelectric pulse sensor based on a biomimetic nanopillar layer was developed and coupled with Personalized Machine Learning (ML) to provide accurate and continuous monitoring of BP. Flexible conductive nanopillars as the triboelectric layer were fabricated through soft lithography replication of a cicada wing, which could effectively enhance the sensor's output performance to detect weak signal characteristics of pulse waveform for BP derivation. The sensors were coupled with a personalized Partial Least-Squares Regression (PLSR) ML to derive unknown BP based on individual pulse characteristics with reasonable accuracy, avoiding the issue of individual variability that was encountered by General PLSR ML or formula algorithms. The cuffless and intelligent design endow this ML-sensor as a highly promising platform for the care and treatments of hypertensive patients.

Applications of flexible electronics related to cardiocerebral vascular system

Ensuring accessible and high-quality healthcare worldwide requires field-deployable and affordable clinical diagnostic tools with high performance. In recent years, flexible electronics with wearable and implantable capabilities have garnered significant attention from researchers, which functioned as vital clinical diagnostic-assisted tools by real-time signal transmission from interested targets in vivo. As the most crucial and complex system of human body, cardiocerebral vascular system together with heart-brain network attracts researchers inputting profuse and indefatigable efforts on proper flexible electronics design and materials selection, trying to overcome the impassable gulf between vivid organisms and rigid inorganic units. This article reviews recent breakthroughs in flexible electronics specifically applied to cardiocerebral vascular system and heart-brain network. Relevant sensor types and working principles, electronics materials selection and treatment methods are expounded. Applications of flexible electronics related to these interested organs and systems are specially highlighted. Through precedent great working studies, we conclude their merits and point out some limitations in this emerging field, thus will help to pave the way for revolutionary flexible electronics and diagnosis assisted tools development.

A highly sensitive flexible capacitive pressure sensor with hierarchical pyramid micro-structured PDMS-based dielectric layer for health monitoring

Herein, a flexible pressure sensor with high sensitivity was created using a dielectric layer featuring a hierarchical pyramid microstructure, both in simulation and fabrication. The capacitive pressure sensor comprises a hierarchically arranged dielectric layer made of polydimethylsiloxane (PDMS) with pyramid microstructures, positioned between copper electrodes at the top and bottom. The achievement of superior sensing performance is highly contingent upon the thickness of the dielectric layer, as indicated by both empirical findings and finite-element analysis. Specifically, the capacitive pressure sensor, featuring a dielectric layer thickness of 0.5 mm, exhibits a remarkable sensitivity of 0.77 kPa-1 within the pressure range below 1 kPa. It also demonstrates an impressive response time of 55 ms and recovery time of 42 ms, along with a low detection limit of 8 Pa. Furthermore, this sensor showcases exceptional stability and reproducibility with up to 1,000 cycles. Considering its exceptional achievements, the pressure sensor has been effectively utilized for monitoring physiological signals, sign language gestures, and vertical mechanical force exerted on objects. Additionally, a 5 × 5 sensor array was fabricated to accurately and precisely map the shape and position of objects. The pressure sensor with advanced performance shows broad potential in electronic skin applications.

Arteriosclerosis Assessment Based on Single-Point Fingertip Pulse Monitoring Using a Wearable Iontronic Sensor

Arteriosclerosis, which appears as a hardened and narrowed artery with plaque buildup, is the primary cause of various cardiovascular diseases such as stroke. Arteriosclerosis is often evaluated by clinically measuring the pulse wave velocity (PWV) using a two-point approach that requires bulky medical equipment and a skilled operator. Although wearable photoplethysmographic sensors for PWV monitoring are developed in recent years, likewise, this technique is often based on two-point measurement, and the signal can easily be interfered with by natural light. Herein, a single-point strategy is reported based on stable fingertip pulse monitoring using a flexible iontronic pressure sensor for heart-fingertip PWV (hfPWV) measurement. The iontronic sensor exhibits a high pressure-resolution on the order of 0.1 Pa over a wide linearity range, allowing the capture of characteristic peaks of fingertip pulse waves. The forward and reflected waves of the pulse are extracted and the time difference between the two waves is computed for hfPWV measurement using Hiroshi's method. Furthermore, a hfPWV-based model is established for arteriosclerosis evaluation with an accuracy comparable to that of existing clinical criteria, and the validity of the model is verified clinically. The work provides a reliable technique that can be used in wearable arteriosclerosis assessment systems.

Frontiers of Wearable Biosensors for Human Health Monitoring

Wearable biosensors offer noninvasive, real-time, and continuous monitoring of diverse human health data, making them invaluable for remote patient tracking, early diagnosis, and personalized medicine [...].

Recent development of piezoelectric biosensors for physiological signal detection and machine learning assisted cardiovascular disease diagnosis

As cardiovascular disease stands as a global primary cause of mortality, there has been an urgent need for continuous and real-time heart monitoring to effectively identify irregular heart rhythms and to offer timely patient alerts. However, conventional cardiac monitoring systems encounter challenges due to inflexible interfaces and discomfort during prolonged monitoring. In this review article, we address these issues by emphasizing the recent development of the flexible, wearable, and comfortable piezoelectric passive sensor assisted by machine learning technology for diagnosis. This innovative device not only harmonizes with the dynamic mechanical properties of human skin but also facilitates continuous and real-time collection of physiological signals. Addressing identified challenges and constraints, this review provides insights into recent advances in piezoelectric cardiac sensors, from devices to circuit systems. Furthermore, this review delves into the integration of machine learning technologies, showcasing their pivotal role in facilitating continuous and real-time assessment of cardiac status. The synergistic combination of flexible piezoelectric sensor design and machine learning holds substantial potential in automating the detection of cardiac irregularities with minimal human intervention. This transformative approach has the power to revolutionize patient care paradigms.

A Fully Self-Powered Wearable Leg Movement Sensing System for Human Health Monitoring

Energy-autonomous wearable human activity monitoring is imperative for daily healthcare, benefiting from long-term sustainable uses. Herein, a fully self-powered wearable system, enabling real-time monitoring and assessments of human multimodal health parameters including knee joint movement, metabolic energy, locomotion speed, and skin temperature, which are fully self-powered by highly-efficient flexible thermoelectric generators (f-TEGs) is proposed and developed. The wearable system is composed of f-TEGs, fabric strain sensors, ultra-low-power edge computing, and Bluetooth. The f-TEGs worn on the leg not only harvest energy from body heat and supply power sustainably for the whole monitoring system, but also serve as zero-power motion sensors to detect limb movement and skin temperature. The fabric strain sensor made by printing PEDOT: PSS on pre-stretched nylon fiber-wrapped rubber band enables high-fidelity and ultralow-power measurements on highly-dynamic knee movements. Edge computing is elaborately designed to estimate multimodal health parameters including time-varying metabolic energy in real-time, which are wirelessly transmitted via Bluetooth. The whole monitoring system is operated automatically and intelligently, works sustainably in both static and dynamic states, and is fully self-powered by the f-TEGs.

Health Monitoring via Heart, Breath, and Korotkoff Sounds by Wearable Piezoelectret Patches

Real-time monitoring of vital sounds from cardiovascular and respiratory systems via wearable devices together with modern data analysis schemes have the potential to reveal a variety of health conditions. Here, a flexible piezoelectret sensing system is developed to examine audio physiological signals in an unobtrusive manner, including heart, Korotkoff, and breath sounds. A customized electromagnetic shielding structure is designed for precision and high-fidelity measurements and several unique physiological sound patterns related to clinical applications are collected and analyzed. At the left chest location for the heart sounds, the S1 and S2 segments related to cardiac systole and diastole conditions, respectively, are successfully extracted and analyzed with good consistency from those of a commercial medical device. At the upper arm location, recorded Korotkoff sounds are used to characterize the systolic and diastolic blood pressure without a doctor or prior calibration. An Omron blood pressure monitor is used to validate these results. The breath sound detections from the lung/ trachea region are achieved a signal-to-noise ration comparable to those of a medical recorder, BIOPAC, with pattern classification capabilities for the diagnosis of viable respiratory diseases. Finally, a 6×6 sensor array is used to record heart sounds at different locations of the chest area simultaneously, including the Aortic, Pulmonic, Erb's point, Tricuspid, and Mitral regions in the form of mixed data resulting from the physiological activities of four heart valves. These signals are then separated by the independent component analysis algorithm and individual heart sound components from specific heart valves can reveal their instantaneous behaviors for the accurate diagnosis of heart diseases. The combination of these demonstrations illustrate a new class of wearable healthcare detection system for potentially advanced diagnostic schemes.

All-Polymer Piezoelectric Elastomer with High Stretchability, Low Hysteresis, Self-Adhesion, and UV-Blocking as Flexible Sensor

All-polymer piezoelectric elastomers that integrate self-powered, soft, and elastic performance are attractive in the fields of flexible wearable electronics and human-machine interfaces. However, a lack of adhesion and UV-blocking performances greatly hinders the potential applications of elastomers in these emerging fields. Here, a high-performance piezoelectric elastomer with piezoelectricity, mechanical robustness, self-adhesion, and UV-resistance was developed by using poly(vinylidene fluoride) (PVDF), acrylonitrile (AN), acrylamide (AAm), and oxidized tannic acid (OTA) (named PPO). In this design, the dipole-dipole interactions between the PVDF and PAN chains promoted the content of β-PVDF, endowing high piezoelectric coefficient (d33, 58 pC/N). Besides, high stretchability (∼500%), supercompressibility (∼98%), low Young's modulus (∼0.02 MPa), and remarkable elasticity (∼13.8% hysteresis ratio) were achieved simultaneously for the elastomers. Inspired by the mussel adhesion chemistry, the OTA containing abundant catechol and quinone groups provided high adhesion (93.26 kPa to wood) and an exceptional UV-blocking property (∼99.9%). In addition, the elastomers can produce a reliable electric signal output (Vocmax = 237 mV) and show a fast response (24 ms) when subjected to external force. Furthermore, the elastomer can be easily assembled as a wearable sensor for human physiological (body pulse and speech identification) monitoring and communication.

Thin, soft, wearable system for continuous wireless monitoring of artery blood pressure

Continuous monitoring of arterial blood pressure (BP) outside of a clinical setting is crucial for preventing and diagnosing hypertension related diseases. However, current continuous BP monitoring instruments suffer from either bulky systems or poor user-device interfacial performance, hampering their applications in continuous BP monitoring. Here, we report a thin, soft, miniaturized system (TSMS) that combines a conformal piezoelectric sensor array, an active pressure adaptation unit, a signal processing module, and an advanced machine learning method, to allow real wearable, continuous wireless monitoring of ambulatory artery BP. By optimizing the materials selection, control/sampling strategy, and system integration, the TSMS exhibits improved interfacial performance while maintaining Grade A level measurement accuracy. Initial trials on 87 volunteers and clinical tracking of two hypertension individuals prove the capability of the TSMS as a reliable BP measurement product, and its feasibility and practical usability in precise BP control and personalized diagnosis schemes development.

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array

Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide applications for early diagnosis. Here, we developed an intelligent blood pressure and cardiac function monitoring system based on a conformal and flexible strain sensor array and deep learning neural networks. The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.

Wide Range Strain Distributions on the Electrode for Highly Sensitive Flexible Tactile Sensor with Low Hysteresis

Flexible piezoresistive tactile sensors are widely used in wearable electronic devices because of their ability to detect mechanical stimuli. However, achieving high sensitivity and low hysteresis over a broad detection range remains a challenge with current piezoresistive tactile sensors. To address these obstacles, we designed elastomeric micropyramid arrays with different heights to redistribute the strain on the electrode. Furthermore, we mixed single-walled carbon nanotubes in the elastomeric micropyramids to compensate for the conductivity loss caused by random cracks in the gold film and increase the adhesion strength between the gold film (deposited on the pyramid surface) and the elastomer. Thus, the energy loss of the sensor during deformation and hysteresis (∼2.52%) was effectively reduced. Therefore, under the synactic effects of the percolation effect, tunnel effect, and multistage strain distribution, the as-prepared sensor exhibited a high sensitivity (1.28 × 10⁶ kPa^-1) and a broad detection range (4.51-54837.06 Pa). The sensitivity was considerably higher than those of most flexible pressure sensors with a microstructure design. As a proof of concept, the sensors were successfully applied in the fields of health monitoring and human-machine interaction.

Smart Wearable Systems for Health Monitoring

Smart wearable systems for health monitoring are highly desired in personal wisdom medicine and telemedicine. These systems make the detecting, monitoring, and recording of biosignals portable, long-term, and comfortable. The development and optimization of wearable health-monitoring systems have focused on advanced materials and system integration, and the number of high-performance wearable systems has been gradually increasing in recent years. However, there are still many challenges in these fields, such as balancing the trade-off between flexibility/stretchability, sensing performance, and the robustness of systems. For this reason, more evolution is required to promote the development of wearable health-monitoring systems. In this regard, this review summarizes some representative achievements and recent progress of wearable systems for health monitoring. Meanwhile, a strategy overview is presented about selecting materials, integrating systems, and monitoring biosignals. The next generation of wearable systems for accurate, portable, continuous, and long-term health monitoring will offer more opportunities for disease diagnosis and treatment.

In-Memory Tactile Sensor with Tunable Steep-Slope Region for Low-Artifact and Real-Time Perception of Mechanical Signals

A tactile sensor needs to perceive static pressures and dynamic forces in real-time with high accuracy for early diagnosis of diseases and development of intelligent medical prosthetics. However, biomechanical and external mechanical signals are always aliased (including variable physiological and pathological events and motion artifacts), bringing great challenges to precise identification of the signals of interest (SOI). Although the existing signal segmentation methods can extract SOI and remove artifacts by blind source separation and/or additional filters, they may restrict the recognizable patterns of the device, and even cause signal distortion. Herein, an in-memory tactile sensor (IMT) with a dynamically adjustable steep-slope region (SSR) and nanocavity-induced nonvolatility (retention time >1000 s) is proposed on the basis of a machano-gated transistor, which directly transduces the tactile stimuli to various dope states of the channel. The programmable SSR endows the sensor with a critical window of responsiveness, realizing the perception of signals on demand. Owing to the nonvolatility of the sensor, the mapping of mechanical cues with high spatiotemporal accuracy and associative learning between two physical inputs are realized, contributing to the accurate assessment of the tissue health status and ultralow-power (about 25.1 μW) identification of an occasionally occurring tremor.

Capacitive Sensors with Hybrid Dielectric Structures and High Sensitivity over a Wide Pressure Range for Monitoring Biosignals

Various dielectrics with porous structures or high dielectric constants have been designed to improve the sensitivity of capacitive pressure sensors (CPSs), but this strategy has only been effective for the low-pressure range. Here, a hierarchical gradient hybrid dielectric, composed of low-permittivity (low-k) polydimethylsiloxane (PDMS) foam with low Young's modulus (low-E) and high-permittivity (high-k) MWCNT/PDMS foam with high Young's modulus (high-E), is designed to develop a CPS for monitoring biosignals over a wide force range. The foam-like structure with hybrid permittivity (low-k + high-k) is facilitated to improve the sensitivity, while the hierarchical structure with gradient Young's modulus (low-E + high-E) contributes to broadening the pressure sensing range. With the hierarchical gradient hybrid structure, the flexible pressure sensor achieves an enhanced sensitivity of 2.155 kPa^-1, a wide pressure range (up to 500 kPa), a minimum detection limit (50 Pa), and an excellent durability (>2500 cycles). As a demonstration, a venous thrombosis simulation and smart insole system are established to monitor venous blood clots and plantar pressures, respectively, which reveal potential applications in wearable medicine, sports health prediction, athlete training, and sports equipment design.

Flexible Capacitive Pressure Sensor Based on a Double-Sided Microstructure Porous Dielectric Layer

In the era of intelligent sensing, there is a huge demand for flexible pressure sensors. High sensitivity is the primary requirement for flexible pressure sensors, whereas pressure response range and resolution, which are also key parameters of sensors, are often ignored, resulting in limited applications of flexible pressure sensors. This paper reports a flexible capacitive pressure sensor based on a double-sided microstructure porous dielectric layer. First, a porous structure was developed in the polymer dielectric layer consisting of silicon rubber (SR)/NaCl/carbon black (CB) using the dissolution method, and then hemisphere microstructures were developed on both sides of the layer by adopting the template method. The synergistic effect of the hemispheric surface microstructure and porous internal structure improves the deformability of the dielectric layer, thus achieving high sensitivity (3.15 kPa^-1), wide response range (0-200 kPa), and high resolution (i.e., the minimum pressure detected was 27 Pa). The proposed sensing unit and its array have been demonstrated to be effective in large-area pressure sensing and object recognition. The flexible capacitive pressure sensor developed in this paper is highly promising in applications of robot skin and intelligent prosthetic hands.