Prognosis of Cardiovascular Conditions Noninvasively Using Printable Elastomeric Electronic Skin

Advanced Healthcare Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Lack of timely prognosis cardiovascular condition (CVC) is resulting in increased mortality across the globe. Currently, available techniques are confined to medical facilities and need intervention specialists. Frequently, this impedes treatment, driven by socioeconomic factors. Consequently, disease transcends toward incurable complications. In such a scenario, point-of-care diagnostic tools can help with at an early stage. Albeit there available, it imperative develop affordably uncomplicated manufacturing should have simple readout analysis modules for monitoring CVC. Accordingly, solvent-free stencil printable liquid elastomer-carbon nanotube electronic skin-based strain sensor, capable accurately detecting pulse (at different positions) other parameters like augmentation index stiffness artery related CVC, reported. The Poincare plot, derived from recorded data, measures heart rate variability, key indicator linked mortality. Thanks staggering linearity, gauge factor 234.26, fast response time 85 ms (measured data), cyclic stability (over 500 cycles), assist ease detection vital parameters. Furthermore, sensor patch demonstrates its capability acquire waves under real-time conditions using cuff-based pressure applications.

Language: Английский

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Maple leaf-based triboelectric nanogenerator for efficient energy harvesting and precision monitoring in ping-pong training

AIP Advances, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 1, 2025

Triboelectric technology, with its renewable, low-cost, and eco-friendly advantages, offers new possibilities for intelligent motion-sensing equipment sports monitoring. We propose a maple leaf-based triboelectric nanogenerator (ML-TENG) green mechanical energy harvesting detecting table tennis corner kicks. The ML-TENG operates in contact-separation mode achieves peak power output of 63.38 W/m3 at an optimal load 50 MΩ. experimental results show transfer charge (Qsc) 35 nC, short-circuit current (Isc) 9 μA, open-circuit voltage (Voc) V. Tested ping-pong paddle, the generates consistent even under high-frequency impacts, demonstrating sensitivity to both strong weak forces. This ready-to-use design requires minimal preparation, highlighting technology’s potential improving monitoring accuracy enabling real-time athletic performance analysis.

Language: Английский

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Multi-hydrogen bond induced double crosslinked network based on WPU/BC/MWCNTs for high ductility and reliable electronic skin for multimodal health monitoring

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 160134 - 160134

Published: Feb. 1, 2025

Language: Английский

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Self-powered sensing for health monitoring and robotics

Soft Science, Journal Year: 2025, Volume and Issue: 5(1)

Published: Feb. 14, 2025

Self-powered sensing technology plays a key role in autonomous and portable systems, with applications health monitoring robotics. These sensors, which do not rely on external power sources, offer stable, continuous data acquisition for real-time complex interactions. For instance, triboelectric nanogenerators have enabled self-powered wearable sensors to monitor vital signs such as heart beat rate respiration by converting body movement into electrical energy, eliminating the need batteries. Despite their advantages, challenges remain large-scale manufacturing, miniaturization, multifunctional integration. Overcoming these may require innovative advances novel materials, intelligent algorithms, integration strategies. This perspective summarizes recent existing technologies robotics applications, provides an outlook future development.

Language: Английский

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Wearable Capacitive Pressure Sensors Based on Porous Sponge Dielectric Materials for Gait Analysis and Identity Recognition

Advanced Materials Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 15, 2025

Abstract Gait often reveals valuable information about personal movements in daily life, and traditional gait monitoring relies on inertial sensors, which are limited by high manufacturing costs, inconvenient operation, complex analysis methods. This study proposes a simple cost‐effective method to manufacture wearable capacitive sensor, can efficiently detect different signals. The sensor is made polyurethane sponge with deposited activated carbon (C@PU sponge) as the dielectric layer, it has sensitivity pretty good stability. further integrated into an insole for detecting collecting signals of foot pressure during human movement. To overcome limitations methods, convolutional neural network model based residual networks designed nine activities recognition accuracy 98.15%. Furthermore, optimized using genetic algorithm, able effectively identify eight participants 98.75%. These results indicate that smart insoles sensors show application prospects identity recognition, expected be widely used life future.

Language: Английский

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Recent Research Trends for Developing Highly Sensitive, Flexible Organic Field-Effect Transistor-Based Gas Sensors

ACS Applied Polymer Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Language: Английский

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3D Integrated Physicochemical‐Sensing Electronic Skin

Small, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

Abstract The integration of physical and chemical signal sensing is great significance to bridge the gap between electronic skin (e‐skin) natural skin. However, existing method integrating units in two dimensions not conducive development e‐skin multifunctionality miniaturization. Herein, a new three‐dimensional (3D) integrated physicochemical‐sensing (TDPSES) developed by piezoresistive unit, biochemical electrode, microfluidic system 3D superposition mode. For pressure sensing, TDPSES demonstrates an ultra‐high sensitivity 208.6 kPa −1 0–15 excellent stability 8000 cycles. glucose sweat, has 3.925 µA m detection limit 29.1 µ . Meanwhile, can only continuously detect biological fluids, but also self‐monitor its fluid‐driving behavior, demonstrating intelligent characteristics. Furthermore, applied monitor variety physiological signals such as pulse, voice, multifunctional capabilities application potential health care. In conclusion, implementation provides idea for constructing miniaturized e‐skin, which helps narrow

Language: Английский

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Synthesis of UV-Filtering, Self-Healing, and Self-Adhesion Multifunctional Ionogel for Multimodal Sensation Ionic Skins by Electron Beam Irradiation

ACS Materials Letters, Journal Year: 2025, Volume and Issue: unknown, P. 1250 - 1259

Published: March 4, 2025

As an ion-conductive material, multifunctional ionogels are crucial for the development of i-skin materials. However, current designs face significant challenges in simultaneously achieving mechanical properties, along with self-healing capabilities, multimodal sensing, and high sensory precision. In this work, we propose a strategy situ electron beam irradiation-induced copolymerization highly soluble acrylic acid (AA) poor-solubility 4-allyloxy-2-hydroxybenzophenone (AHBP) to prepare phase-separated ionogels. AHBP not only enables tunable transparency by adjusting degree phase separation but also improves properties ionogel modulating soft/hard domains caused solvent-rich polymer-rich phases. Additionally, efficiently absorbs UV light through conformational changes. Combined its excellent conductivity, thermal stability, outstanding self-adhesive ionogel-based demonstrates sensing capabilities strain, temperature, pressure, showing great potential applications wearable strain sensors multisignal arrays.

Language: Английский

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Deep-Learning-Based Analysis of Electronic Skin Sensing Data

Sensors, Journal Year: 2025, Volume and Issue: 25(5), P. 1615 - 1615

Published: March 6, 2025

E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricate signals real-time responses. Recently, deep learning techniques, such as convolutional neural network, recurrent transformer methods, provide effective solutions automatically extract data features recognize significantly improving data. Deep not only capable handling multimodal but also response personalized predictions in dynamic environments. Nevertheless, problems insufficient annotation high demand for computational resources still limit application e-skin. Optimizing algorithms, efficiency, exploring hardware-algorithm co-designing will be key future development. This review aims present techniques applied inspiration subsequent researchers. We first summarize sources characteristics models applicable their applications analysis. Additionally, we discuss use e-skin, particularly health monitoring human-machine interactions, explore current challenges development directions.

Language: Английский

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Advancing Sports Cardiology: Integrating Artificial Intelligence with Wearable Devices for Cardiovascular Health Management

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Sports cardiology focuses on athletes' cardiovascular health, yet sudden cardiac death remains a significant concern despite preventative measures. Prolonged physical activity leads to notable adaptations, known as the athlete's heart, which can resemble certain pathological conditions, complicating accurate diagnoses and potentially leading serious consequences such unnecessary exclusion from sports or missed treatment opportunities. Wearable devices, including smartwatches smart glasses, have become prevalent for monitoring health metrics, offering potential clinical applications cardiologists. These gadgets are capable of spotting exercise-induced arrhythmias, uncovering hidden heart problems, crucial information training recovery, minimize exercise-related incidents enhance care. However, concerns about data accuracy actionable value obtained persist. A major challenge lies in integration artificial intelligence with wearables, research gaps remain regarding their ability provide real-time, reliable, clinically relevant insights. Combining wearable devices improve how is managed used cardiology. Artificial intelligence, particularly machine learning, classify, predict, draw inferences collected by revolutionizing patient usage. Despite intelligence's proven effectiveness managing chronic limited its application cardiology, creates critical gap that needs be addressed. This review examines commercially available wearables exploring integrated into technology advance field.

Language: Английский

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