Piezoelectric Dynamics of Arterial Pulse for Wearable Continuous Blood Pressure Monitoring

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.

Printable Graphene-Sustainable Elastomer-Based Cross Talk Free Sensor for Point of Care Diagnostics

Developing sensors for monitoring physiological parameters such as temperature and strain for point of care (POC) diagnostics is critical for better care of the patients. Various commercial sensors are available to get the job done; however, challenges like the structural rigidity of such sensors confine their usage. As an alternative, flexible sensors have been looked upon recently. In most cases, flexible sensors cannot discriminate the signals from different stimuli. While there have been reports on the printable sensors providing cross-talk-free solutions, research related to developing sensors from a sustainable source providing discriminability between signals is not well-explored. Herein, we report the development of a stencil printable composition made of graphene and epoxidized natural rubber. The stencil printability index was vetted using rheological studies. Post usage, the developed sensor was dissolved in an organic solvent at room temperature. This, along with the choice of a sustainable elastomer, warrants the minimization of electronic waste and carbon footprint. The developed material demonstrated good conformability with the skin and could perceive and decouple the signals from temperature and strain without inducing any crosstalks. Using a representative volume element model, a comparison between experimental findings and computation studies was made. The developed sensors demonstrated gauge factors of -506 and 407 in the bending strain regimes of 0-0.04% and 0.04%-0.09%, respectively, while the temperature sensitivity was noted to be -0.96%/°C. The printed sensors demonstrated a multifunctional sensing behavior for monitoring various active physiological parameters ranging from temperature, strain, pulse, and breathing to auditory responses. Using a Bluetooth module, various parameters like temperature and strain could be monitored seamlessly in a smart-phone. The current development would be crucial to open new avenues to fabricate crosstalk-free sensors from sustainable sources for POC diagnostics.

Human thermal sensation algorithm modelization via physiological thermoregulatory responses based on dynamic thermal environment tests on males

BACKGROUND AND OBJECTIVES

Thermal conditions are changeable in cabin space, where occupants could suffer consecutive self-thermoregulation to such changing thermal stresses. Thermal environment management is expected to be purposefully auto-adjustable for the environment by recognizing individual real-time thermal sensations. Current thermal sensation evaluation models are developed for virtual simulations rather than for realistic scenarios, challenging to evaluate human thermal sensation in the field surveys.

METHODS

The study constructs a human thermal sensation model via human physiological responses to evaluate the human thermal sensation in the actual vehicle environment. The thermal sensation model forms with exponential functions to clarify the relationship between thermal sensation and pulse rate and blood pressure, which successfully expresses the approximately linear trend around neutral sensation and compensates for the end-points bias. The study set up experimental cases to determine the parameter states in the thermal sensation model. Firstly, subjective thermal sensation scoring was performed by combing with an established seven-point-scale questionnaire survey system for human thermal sensation. Wearable sensors are then applied to measure the human physiological response, including blood pressure BP, pulse rate PR and blood oxygen saturation SpO₂.

RESULTS

The subjects revealed significantly higher pulse rates (positively correlated) and lower blood pressure (negatively correlated) in the warm chamber than in the cool chamber. The defined parameter change rate effectively reveals the trend of human thermal sensation and avoids the inconsistency of raw physiological response levels. The change rate in PR and MAP between the thermal sensation in cold -3 and hot +3 is about a 10% difference.

CONCLUSIONS

Based on the thermal sensation model algorithm, model parameters were fitted by the subjects' thermal sensation voting and the change rate of their physiological responses. With the coefficient of determination (R²) of the regression over 0.8, the proposed thermal sensation model can be employed for human thermal sensation evaluation. The physiological thermoregulatory responses effectively indicate the thermal state of the human body and can be used in thermal environments in conjunction with human smart wearable devices.

Transcranial Ultrasound Imaging With Decomposition Descent Learning-Based Full Waveform Inversion

Noninvasive brain diagnosis is extremely important because of its efficiency, low cost, and painless nature in the prediction of stroke, cerebral hemorrhage, and other brain research. At present, achieving full 3-D quantitative ultrasonic imaging of the human brain is a cutting-edge challenge due to the complex structures of the human brain and the strong scattering caused by the skulls. In this article, we achieved quantitative ultrasonic imaging of inside-brain anomalies with our proposed method, the decomposition descent learning-based full waveform inversion (DDL-FWI). The proposed method adopts a linear residual decomposing technique to greatly alleviate the computation burden in fast inversion tomography (FIT) with enhanced convergence guaranteed by residual functions. Testing results in both simulation and laboratory experiments demonstrated that our method can achieve high-quality quantitative imaging of brain soft tissues and skulls even starting from homogeneous water background in 2-D, and this method is capable of reconstructing both complex brain tissues and clots in 2-D and 3-D cases using either clean or noisy signals, with a robust 3-D clot resolution as small as 18 mm and 2-D reconstruction speed in 11.20 s. Combined with advanced ultrasonic hardware, DDL-FWI can be easily trained and used for brain imaging efficiently that frees patients from harmful influences from traditional imaging techniques, e.g., ionization radiations from X-ray computed tomography (CT).

Biomechanical Sensing Systems for Cardiac Activity Monitoring

Cardiovascular disease is consistently ranked high among the causes of death on a global scale. Monitoring of cardiovascular signs throughout the course of a long period of time and in real time is necessary in order to discover anomalies and begin early intervention at the appropriate time. To this purpose, a significant amount of interest among researchers has been directed toward the creation of flexible sensors that may be worn or implanted and are capable of constant, immediate observation of a variety of main physiological indicators. The real-time readings of the heart and arteries' pressure fluctuations can be reflected directly by mechanical sensors, which are one of the many types of sensors. Potential benefits of mechanical sensors include excellent accuracy and considerable versatility. Capacitive, piezoresistive, piezoelectric, and triboelectric principles are the foundations of the four types of mechanical sensors that are discussed in this article as recent developments for the purpose of monitoring the cardiovascular system. The biomechanical systems that are present in the cardiovascular system are then detailed, along with their monitoring, and this includes blood and endocardial pressure, pulse wave, and heart rhythm. In conclusion, we examine the usefulness of the use of continuous health monitoring for the treatment of vascular disease and highlight the difficulties associated with its translation into clinical practice.

A Portable Sweat Sensor Based on Carbon Quantum Dots for Multiplex Detection of Cardiovascular Health Biomarkers

The future of personalized diagnostics and treatment of cardiovascular diseases lies in the use of portable sensors. Portable sensors can acquire biomarker information in biological fluids such as sweat, an approach that mitigates the shortcomings of conventional hospital-centered healthcare. Low sensitivity, selectivity, and specificity remain bottlenecks for the widespread use of portable sensors. Herein, we demonstrate a portable sensor that simultaneously detects Na⁺, ascorbic acid, and human neuropeptide Y in sweat, all useful biomarkers to index cardiovascular health. The portable sensor comprises a six-electrode system containing three working electrodes, two reference electrodes, and one counter electrode. The working electrodes were prepared by depositing sensing components on carbon quantum dot (CQD) electrodes. The sensing mechanisms were based on selective ion recognition, enzyme catalytic reaction, and immune response, which guarantees specificity to corresponding targets. The CQDs offer massive reactive sites and effectively reduce the interfacial impedance during the sensing reaction, thereby enhancing the three biomarkers' detection sensitivity. As evidence of portable sensor capability, we demonstrate herein its effective simultaneous detection of the three biomarkers in a real sweat from healthy volunteers during routine activities including exercise, extra ascorbic acid ingestion, and extra Na⁺ ingestion. As such, the sensor shows promise for real-time noninvasive personalized medical diagnostics and metabolic wellness management.

On-Skin Flexible Pressure Sensor with High Sensitivity for Portable Pulse Monitoring

Radial artery pulse pressure contains abundant cardiovascular physiological and pathological information, which plays an important role in clinical diagnosis of traditional Chinese medical science. However, many photoelectric sensors and pressure sensors will lose a large number of waveform features in monitoring pulse, which will make it difficult for doctors to precisely evaluate the patients' health. In this letter, we proposed an on-skin flexible pressure sensor for monitoring radial artery pulse. The sensor consists of the MXene (Ti₃C₂T_x)-coated nonwoven fabrics (n-WFs) sensitive layer and laser-engraved interdigital copper electrodes. Benefiting from substantially increased conductive paths between fibers and electrodes during normal compression, the sensor obtains high sensitivity (3.187 kPa^-1), fast response time (15 ms), low detection limit (11.1 Pa), and long-term durability (20,000 cycles). Furthermore, a flexible processing circuit was connected with the sensor mounted on wrist radial artery, achieving wirelessly precise monitoring of the pulse on smart phones in real time. Compared with the commercial flexible pressure sensor, our sensor successfully captures weak systolic peak precisely, showing its great clinical potential and commercial value.

Mechanical Sensors for Cardiovascular Monitoring: From Battery-Powered to Self-Powered

Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.

Recent Advances in Stretchable and Wearable Capacitive Electrophysiological Sensors for Long-Term Health Monitoring

Over the past several years, wearable electrophysiological sensors with stretchability have received significant research attention because of their capability to continuously monitor electrophysiological signals from the human body with minimal body motion artifacts, long-term tracking, and comfort for real-time health monitoring. Among the four different sensors, i.e., piezoresistive, piezoelectric, iontronic, and capacitive, capacitive sensors are the most advantageous owing to their reusability, high durability, device sterilization ability, and minimum leakage currents between the electrode and the body to reduce the health risk arising from any short circuit. This review focuses on the development of wearable, flexible capacitive sensors for monitoring electrophysiological conditions, including the electrode materials and configuration, the sensing mechanisms, and the fabrication strategies. In addition, several design strategies of flexible/stretchable electrodes, body-to-electrode signal transduction, and measurements have been critically evaluated. We have also highlighted the gaps and opportunities needed for enhancing the suitability and practical applicability of wearable capacitive sensors. Finally, the potential applications, research challenges, and future research directions on stretchable and wearable capacitive sensors are outlined in this review.