Wearable molecularly imprinted polymer sweat testosterone sensor for noninvasive auxiliary early-stage polycystic ovary syndrome at rest.

A wireless, wearable, battery-free multi-sensory system is essential for continuous, non-invasive real-time monitoring of multiple physiological parameters, enabling seamless, discreet healthcare. The main bottleneck in developing such systems lies in achieving low power consumption to enable battery-free operation, while maintaining reliable, high-frequency data acquisition and efficient wireless communication with a skin-impedance-matched antenna within a compact, wearable form factor. To overcome this, we integrate energy-harvesting technologies with high-precision multiple sensors and a flexible, skin-compatible antenna system into a single platform, enabling battery-free operation with efficient data transmission and reception. Our multi-sensory system experimentally demonstrates successful skin-mountable monitoring of ECG, SpO 2 , and temperature at a sampling rate of 70 Hz, with data wirelessly transmitted via Bluetooth Low Energy, all powered by a radio-frequency energy-harvesting antenna. Beyond personal health tracking, this technology also holds great potential for remote patient monitoring in chronic disease management, empowering healthcare providers with continuous access to real-time patient data for timely and uninterrupted data acquisition. Typically, health monitoring systems depend on separate hardware for each physiological signal—such as electrocardiogram, pulse oximetry, and temperature—which requires bulky setups with complex wiring, limiting their practicality for wearable and continuous use. These limitations significantly hinder proactive and long-term monitoring beyond clinical settings. Here, a fully integrated, skin-mountable multisensory patch designed for chest application is demonstrated. The system simultaneously acquires electrocardiogram (ECG), pulse oximetry, and temperature signals, powered sequentially via a battery-free near-field communication (NFC) antenna. Furthermore, high-frequency, noise-free data transmission is achieved through a skin-impedance-matched flexible Bluetooth antenna, ensuring seamless communication without compromising user comfort. This compact, wireless system makes it possible to monitor vital physiological parameters remotely and in real time, helping with early diagnosis, ongoing care, and preventive health tracking outside clinical environments. Fig. | Conceptual illustration of a battery-free, skin-mountable wearable patch. The system enables simultaneous energy harvesting and data transmission through an integrated flexible NFC and Bluetooth antenna. • Integration of Electrocardiogram, pulse oximetry, and temperature sensing into a single flexible and skin-conformal patch for comprehensive physiological monitoring. • Battery-free operation through sequential powering enabled by an embedded NFC antenna for wireless energy harvesting. • Flexible Bluetooth antenna matched to skin impedance for robust and noise-free wireless transmission in real-time. • Optimized system for short-range wireless data transfer (1–10 m), enabling real-time smartphone visualization and cloud connectivity. • Demonstration of consistent signal quality across ECG, SpO₂, and temperature, benchmarked against commercial devices.

A portable multiplexed electrochemical biosensor for lactate and pH monitoring in calf saliva.

Beamforming technology featuring broad bandwidth, fast beam switching speed and multi-user access capability plays a pivotal role in the next-generation wireless communication systems. Here, we report a fully-connected broadband microwave photonic multi-beamforming architecture based on silicon optical true-time delay lines (OTTDLs). Unlike conventional partially-connected schemes, the fully-connected network allows each radio frequency beam to be synthesized by all antenna elements, enhancing beamforming gain and multi-beam scalability. Experimental measurements demonstrate squint-free beam steering across 13 directions with deflection angles exceeding ±50.0° and a fast beam reconfiguration speed of 60 ns. Compared with partially-connected schemes, our architecture achieves stronger received signals, delivering a 2.9 dB gain at 13.1 GHz for an identical 8-element antenna array. A 64-QAM downlink signal with 400 MHz bandwidth achieves an error vector magnitude (EVM) of 7.6% over 20-m outdoor wireless transmission. These results provide a scalable solution for broadband microwave photonic multi-beamforming and support future 5 G and 6 G wireless networks.

Effective management of prenatal nutrient concentrations, such as those associated with folate, is critical for the health of the prospective mother and child, but quantifying them currently requires frequent blood tests and specialized laboratories. Human sweat is a non-invasive alternative to blood that is well suited for point-of-care biosensing. Here we present a skin-interfaced microcapsule that enables collection and storage of pristine, microlitre volumes of sweat and supports an efficient interface to a portable lab-on-a-disc platform for folate quantification. This platform automates an entire enzyme-linked immunoassay sequence for measuring folate in sweat, including incubation, washing, mixing and detection, and facilitates wireless data transmission. A series of tests in human participants reveal a dose-response relationship between oral intake of folate supplements and sweat folate levels, with a strong correlation in levels between sweat and serum. In addition, daily tracking of sweat folate concentrations shows clear differences between control periods without supplementation and daily intake periods. This technology creates possibilities for the routine use of sweat for precise point-of-care assessment of prenatal nutrient bioavailability.

To assess the feasibility, patient tolerance, and accuracy of a wireless Bluetooth pulse oximeter sensor system on horses for an extended period. A prospective, case-control, unblinded study involved 7 horses at risk of hypoxemia and 7 healthy controls. A wireless Bluetooth transmission sensor was attached to their nostril for a prolonged period. Sensor retention time, patient tolerance, and sensor performance in capturing valid monitoring points were recorded. During the monitoring, 4 samples of arterial blood were collected, and paired measurements (SaO2) and estimations (SpO2) of oxygen hemoglobin saturation were performed. Bland-Altman analysis was used for accuracy assessment. Data are presented as median values and ranges. Monitoring time varied between 28 and 492 minutes (median, 356 minutes), with 11 of 14 horses maintaining the sensor at the end of the observation period. The sensor was well tolerated, and valid captured data were recorded 84.66% to 100% of the time (mean, 98.17%). Forty-nine paired SaO2/SpO2 readings were analyzed, showing that the pulse oximeter overestimated SaO2 (bias, 1.16%; precision, 1.83%). Calculated accuracy root mean square was 2.15%. The Bluetooth pulse oximetry monitoring is well tolerated, easily maintained, and shows good agreement with SaO2 measurements in nonhypoxemic horses. Further studies are needed to assess its performance under circumstances of decreased blood oxygenation. Wireless Bluetooth pulse oximetry can be used in conscious, nonhypoxemic horses at risk of a desaturation event requiring continuous/prolonged oxygenation monitoring as an accurate alternative to blood gas analysis.

The energy hole problem is a significant challenge in wireless sensor networks (WSN) that use multi-hop routing protocols. Nodes near the base station (BS) typically experience higher energy consumption due to higher data traffic, resulting in faster network energy depletion and creating an energy hole near the BS. To address this issue, the paper proposes a solution involving a mobile data collector (MDC) in an unequal grid cluster. The number and size of the clusters are determined based on the radio energy model's threshold transmission value, which provides balanced data traffic distribution in the network. The cluster head (CH) is elected based on the node's distance from the cluster centroid and its residual energy. Additionally, the frequency of CH rotation is optimized through an energy-efficient CH change mechanism. The inclusion of an MDC enables data collection from the CHs along the vertical boundaries, effectively reducing the occurrence of energy holes and extending the network's overall lifespan. Simulation results demonstrate the superior performance of our protocol compared to similar existing schemes. Our proposed work was simulated using OMNeT++, and the results indicate that it achieves approximately 21% less energy consumption than similar existing works.

HighlightsWhat are the main findings?A magnetically repulsive cushion triboelectric nanogenerator enables self-powered vibration sensing under weak excitation.The combined magnetic cushioning and microstructured strip electrodes improve contact–separation stability, output performance, and signal reliability.What are the implications of the main findings?The proposed MRCT provides a low-power sensing strategy for rotor vibration monitoring without an external power supply.A CNN-GRU model enables laboratory-scale recognition of predefined rotor imbalance states, achieving over 98% accuracy under the present dataset.The MRCT also shows distinguishable time- and frequency-domain responses under a shaft-misalignment-related abnormal vibration condition.Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact–separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network–gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2× rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary.

In this work, a self-powered vibration sensing system is proposed, based on a spatial magnetic field energy harvester, a duty-cycled circuit module, a piezoresistive graphene-based vibration sensor, and a wireless communication unit. The energy harvester is capable of generating an output power of 729 μW under a magnetic field excitation of 0.11 mT at 50 Hz. The duty-cycled circuit module enables closed-loop self-powered operation of the sensing system by efficient power storage and periodic measurement, and LoRa wireless transmission. The graphene-based sensor exhibits stable low-frequency vibration responses and good linearity and can capture composite vibration signals containing 4 Hz and 50 Hz components. These results indicate the potential of the proposed system for future transmission-line vibration sensing applications.

Low-cost embedded system for spectral power distribution reconstruction for controlled environmental agriculture using a multispectral sensor and cloud-based deep learning.

Battery-free radio systems utilizing wireless power transfer (WPT) further facilitate the miniaturization of neural implants. However, simultaneous monitoring of multiple neuronal activities is required to obtain high-fidelity neural signals. Consequently, the integration of numerous channels on a single chip and the wireless transmission of massive multi-channel data pose significant challenges for implantable battery-free neural interfaces. This work introduces dual overlapped on-chip antennas to eliminate the need for a battery in the neural implants and enable high-data-rate backscatter for transmitting the massive data acquired simultaneously from 72 channels. Additionally, an orthogonal coding and sampling technique is employed to reduce both power consumption and area per channel. Fabricated in a 65 nm CMOS process, the proposed chip integrates 72 neural recording channels within a 2 mm × 2 mm area and achieves a backscatter data rate of 18 Mbps.

The self-stacking of the MXene material can diminish its interlayer spacing and active surface area, thereby diminishing the sensitivity and response speed of pressure sensors. Here, we introduce a high-performance flexible tactile sensor utilizing a composite of MXene, polystyrene (PS) microspheres, and bacterial cellulose (BC). PS microspheres are integrated within the MXene nanosheet layers to mitigate the self-stacking. By employing an innovative point-to-point conductive network design, the self-aggregation issue of MXene materials is effectively mitigated, leading to the formation of dynamic point-contact structures among PS microspheres. This configuration notably enhances detection sensitivity within the low-pressure range to 568.8 kPa-1 (20-200 Pa). Furthermore, the incorporation of BC enhances the interfacial bonding strength through hydrogen bonding, thereby enhancing sensor stability. The sensor exhibits a rapid response time of 29 ms, a wide detection range of up to 0-50 kPa, a low limit of detection of 2 Pa, and consistent signal stability over 20,000 cycles. It has demonstrated the capability to monitor a broad spectrum of physiological activities, including joint movements, facial microexpressions, and radial pulse. Integration with wireless transmission technology enables remote health monitoring, flexible touch keyboard functionality, and human-computer interaction. Additionally, the electromyography (EMG) skin sensor based on the MXene/PS/BC (MPB) composite film accurately distinguishes muscle movements, gestures, acoustic vibrations, and facial microexpressions by detecting surface EMG signals. This comprehensive approach offers a comprehensive solution for wearable medical devices that combine high sensitivity with practicality.

Developing multifunctional tactile sensors that combine multimodal perception with structural simplicity remains challenging for embodied perception. Inspired by trichoid sensilla on wasp antennae, we present a dual-modal bioinspired trichoid tactile sensor (BTTS) that integrates both piezoresistive and triboelectric effects. The BTTS consists of vertically aligned rough-substrate laser-induced graphene fibers (RLIGFs) formed on a laser-pretreated polyimide substrate, creating a hierarchical bionic architecture with staggered microstructures. This design produces distinguishable electrical signals when contacting objects of different shapes and material types. A BTTS-based wireless wearable system (BWWS) is further developed for multichannel real-time tactile signal acquisition and wireless transmission. Machine-learning-assisted fusion and classification of BWWS signals enable simultaneous recognition of object shape and material type, achieving 95.6% accuracy across eight objects. Owing to its simple structure, rapid fabrication, and low cost, the proposed BTTS shows strong potential for embodied perception, humanoid robotics, and wearable devices.

Continuous respiratory monitoring remains one of the most critical yet unmet needs in personal and clinical healthcare. To overcome the limitations of cumbersome systems and motion-prone wearables, we present a moisture-gated bio-semiconductor-based electronic tattoo (BSET) that enables imperceptible, skin-conformable, and wireless respiratory monitoring by leveraging the hydration-sensitive ionic-electronic conductivity of melanin and the skin-compatibility of silk. Fabricated from a silk fibroin-melanin nanofiber bio-composite, the BSET is ultrathin at 18 μm and highly breathable, achieving a water vapor transmission rate exceeding 3000 g·m-2·d-1. By detecting exhaled moisture directly on the philtrum, the sensor exhibits a rapid response time of 1 s and a recovery time between 2 and 10 s. A direct-spun nanofiber-based wiring strategy ensures robust integration, accommodating a 10 mm displacement under 10.4 MPa of stress without failure. Driven by a compact 3 g circuit with 20 mW of power consumption, the system supports continuous wireless data transmission for over 7.3 h. During vigorous exercise and sleep, the BSET reliably monitored respiratory dynamics, identifying 10-20 s apnea events and enabling multiparameter analysis of breathing frequency and exhalation intensity. This lightweight system establishes a scalable and clinically relevant solution for continuous respiratory surveillance.

PurposeTo present a novel eyeglass-coupled perilimbal antenna for retinal prostheses and evaluate preclinical biocompatibility and ocular surface effects using a refined, graft-assisted implantation technique.MethodsThe structural, mechanical, and functional properties of the antenna were assessed, including buffering systems for tissue resilience. Coupling between the eyeglass-rim–mounted emitter and perilimbal receiver was optimized through finite-element electromagnetic simulation and validated in electrolyte solution. A preclinical study was performed in 11 eyes of six Lanyu minipigs, in which antennas were implanted using a refined surgical technique and covered with amniotic membrane, porcine small intestinal submucosa, or pericardium graft. Postoperative evaluations over 6 months included serial external eye photography, anterior segment optical coherence tomography (AS-OCT), tear secretion testing, tear cytokine profiling, and conjunctival impression cytology.ResultsAll eyes showed stable healing without exposure, infection, or granulation. ASOCT revealed no significant change in perilimbal conjunctival thickness (400.5 ± 89.6 µm baseline vs. 399.4 ± 158.2 µm at 6 months; P = 0.612). Coverage materials thinned significantly (360.7 ± 119.5 µm at 1 month vs. 71.4 ± 103.0 µm at 6 months; P = 0.018) without adverse ocular effects. Transient postoperative elevations of tear cytokines (IL-1β, IL-8, IL-6) normalized over time. Tear production, conjunctival redness, and goblet cell density returned to baseline levels.ConclusionsThe eyeglass-coupled perilimbal antenna enabled efficient transmission with preserved ocular surface integrity. Graft-assisted implantation ensured stability and biocompatibility, serving as a safe interface for retinal prostheses.Translational RelevanceA novel perilimbal antenna design enables efficient wireless transmission and biocompatible integration for next-generation retinal prostheses.

To meet the demand for high-capacity indoor wireless access in future 6G systems, we propose and experimentally demonstrate a photonics-aided D-band wireless transmission scheme operating at 138 GHz. At the transmitter, two external-cavity lasers together with an I/Q modulator are used to generate a modulated D-band carrier. At the receiver, homodyne down-conversion is employed to directly recover the received signal to baseband, thereby relaxing the requirements on ultra-wideband analog components and high-speed sampling hardware. A 20 m indoor line-of-sight wireless link is established to transmit a 56-Gbaud-rate OFDM-QPSK signal. The transmitted and received spectra, received constellations and bit-error-rate (BER) performance are functions of optical power at different symbol rates, and the channel amplitude and phase responses are systematically analyzed. The results show that broadband D-band signal generation, transmission, and recovery can be stably achieved in the proposed system. After receiver-side digital signal processing (DSP), clear QPSK constellations are obtained. BER measurements reveal an optimal optical-power operating range, and the 32-GBaud OFDM signal outperforms the 56-Gbaud-rate signal because its narrower occupied bandwidth makes it less sensitive to frequency-selective distortion. For 56-Gbaud-rate OFDM transmission, the BER approaches the 20% low-density parity-check forward-error-correction threshold at an optical power of approximately −1 dBm. Further analysis indicates that the current link performance is mainly limited by frequency-selective amplitude and phase distortions under bandwidth-constrained conditions, together with slight nonlinear effects at high power. These results verify the feasibility of a photonics-aided D-band wireless architecture with homodyne reception for medium-range, high-symbol-rate indoor transmission and provide an experimental basis for future 6G sub-THz wireless links.

Systems utilizing ultra-wideband (UWB) technology are best suited for low-power, high-data-rate wireless transmission. However, designing an antenna for UWB has proven to be a difficult issue. This manuscript proposed a Microstrip Patch Antenna (MPA) design using Hybrid Coati and Salmon Migration Optimization for UWB applications. Here, the liquid crystal polymer (LCP) substrate is utilized to lower the cost of the material, and to improve antenna performance, the proper geometric characteristics are used. Conversely, a novel optimization strategy is used in this manuscript for enhancing the antenna parameters, which is named Hybrid Coati Salmon Migration Optimization (Hyb-COA-SMOA). In the present work, the proposed antenna is designed and simulated using ANSYS HFSS, and the optimization is done using Python. The proposed antenna shows a return loss of around −20 dB, bandwidth of 1.51 GHz, and resonates at 10.6 GHz, indicating its suitability for high-frequency applications.

Centrifugal microfluidics has emerged as a promising platform for automated bioanalysis, such as nucleic acid testing and immunoassays. In particular, real-time centrifugal microfluidic PCR provides a highly effective solution for point-of-care molecular diagnostics in resource-limited settings. However, during the development of these systems, monitoring their operational state for evaluation or calibration is difficult due to the inherent conflicts among thermal, optical, and centrifugal interactions. To address this challenge, this study presents a wireless, in-situ calibration 'chip' with multiple functions for system calibration and evaluation by being operated in a way similar to a normal disk chip. The calibration 'chip' consists of multiple different structural layers, e.g., sensing, optical, fluidic and electrical layers, integrating multiple functions including temperature calibration, fluorescence signal simulation, dynamic fluid monitoring, and mechanical sensing. To allow the in-situ calibration 'chip' to reasonably fit the centrifugation platform, it is powered by embedded rechargeable batteries and meanwhile Bluetooth-based wireless data transmission is adopted. Experimental results demonstrate that the calibration 'chip' is capable of performing multiple different tasks based on comprehensive sensing and actuation mechanisms, which is helpful to conveniently perform in-situ monitoring of the centrifugal microfluidic system with an on hand 'tool'.

Sixth-generation (6 G) back-haul links will require terahertz (THz) carriers above 350 GHz to escape the congested 300 GHz band and support >100 Gbps data rates. Photonic THz transmitters have so far remained below 350 GHz because high-frequency photomixing suffers from phase noise and power limits. Here we demonstrate single-channel wireless transmission at 560 GHz using a fibre-packaged silicon-nitride soliton microcomb as a compact, low-phase-noise optical reference. A high numerical aperture, UV-bonded fibre interface sustains soliton operation for more than 24 hours with 1 W pump power. We phase-lock two distributed-feedback lasers (DFBs) to adjacent comb lines and photomix them in a uni-traveling-carrier photodiode, generating a 560 GHz carrier that bears in-phase and quadrature modulation. We achieve hard-decision forward-error-correction-qualified quadrature phase-shift keying and 16-quadrature amplitude modulation (16QAM) transmissions at 42 and 28 GBaud, respectively, attaining a record 112 Gbps data rate at 560 GHz. Relative to free-running DFBs, microcomb-locked photomixing cuts carrier linewidth and improves 16QAM error-vector magnitude. The results establish soliton microcombs as compact and scalable frequency references for >100 Gbps sub-THz links and chart a path toward compact 6 G back-haul radios.

Mosquito-borne diseases pose a major public health challenge and require effective, scalable surveillance to guide targeted interventions. Existing monitoring techniques, ranging from manual morphological identification to acoustic, optical, and spectroscopic sensing, remain constrained by environmental sensitivity, labor demands, and limited ground-truth validation. Here, we present a fully autonomous, field-deployable platform, called automated intelligent mosquito sentinel (AIMS), integrating distributed mosquito monitoring outposts (MMOs) and a centralized analysis center (AC) for scalable, non-invasive mosquito surveillance. AIMS employs an adaptive event-triggering mechanism, optimized through feature engineering of colour and texture pairs, to enable energy-efficient detection with zero missed events and a false-positive rate below 1%. At the analytical level, a hierarchical gated residual network performs multitask classification of taxonomy and sex with accuracies of 99.51% at species and 98.02% for sex, demonstrating interpretable, biologically meaningful attention patterns. The self-powered architecture, robust wireless data transmission, and large-scale field dataset underpin reliable operation across diverse ecological settings. Together, these results show that AIMS can support scalable and sustainable mosquito surveillance and may also be useful for broader entomological monitoring and public health applications.