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Optically Modulated Split Ring Resonator sensor for Optical Density Analysis of Liquid Analytes in Microwave Regime

IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2025年第3期73卷 1610-1618页

作者： Sourkouhi, Zahra Sarpanah Balasubramanian, Vishal Zarifi, Mohammad Hossein Univ British Columbia Sch Engn Kelowna BC V1V 1V7 Canada

Conventional optical sensors are insensitive to the variations in the dielectric properties of materials, while typical microwave sensors are insensitive to the variations in the material's optical properties. This work presents a photoresponsive microwave split ring resonator (SRR) sensor designed for the simultaneous analysis and characterization of both the dielectric and optical properties of the liquid analytes. Through the integration of a light-sensitive element (photoresistor) into the SRR, the proposed method enables the microwave sensor to characterize the optical density of the liquid analyte while distinguishing the dielectric properties of the sample. In the designed system, optical illumination with blue light ( lambda = 460 nm) and red light (lambda = 630 nm) affects the conductivity of the photoresistor integrated with the microwave SRR, depending on the optical density of the liquid analyte, thus affecting the sensor's S- 21 response. The developed system demonstrates a sensitivity of - 0.57 dB per log(10)(Colorant 10 (Colorant Volume) for red-light illumination passing through blue-colored samples and - 0.17 dB per log10(Colorant 10 (Colorant Volume) for the blue-light illumination in red-colored liquids. The presented system promises potential application in industries, including chemical, biological, pharmaceutical, and food processing.

关键词： Optical sensors Optical variables measurement Optical ring resonators Liquids Microwave theory and techniques Dielectrics Biomedical optical imaging Microwave measurement Optical modulation Optical device fabrication Color detection colorimetric analysis contactless measurement optical density optical modulation sensor fusion split ring resonator (SRR)

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High-response humidity sensor based on silicon microbridge with edge-constrained sandwich sensing structure

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sensors AND ACTUATORS B-CHEMICAL 2024年 413卷

作者： Yu, Xiang Chen, Xiangdong Ding, Xing Tang, Kun Liu, Fang Lu, Jiaqi Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 610031 Peoples R China

Silicon microbridge structures have attracted the attention of researchers in humidity sensing area owing to their small size and ease of integration with the integrated circuit (IC). However, the preparation of silicon microbridge humidity sensors with high response are still a challenge. This paper proposed a silicon microbridge humidity sensor based on an edge-constrained sandwich sensing structure, in which a graphene oxide core layer with small area was covered on the surface of the silicon bridge by a larger area of Nafion film. Due to the constraint of the peripheral edge, the swelling deformations of this sandwich structure in the vertical direction were effectively magnified during humidity detection. Hence, the proposed humidity sensor exhibited a higher humidity sensitivity (109.97 mu V/%RH) compared to the silicon microbridge sensors with general sandwich sensing structure or monolayer sensing film. Meanwhile, the novel sensor also demonstrated a small humidity hysteresis and good linearity in humidity range of 11.3 - 97.3%.

关键词： Edge-constrained sandwich sensing structure Silicon microbridge Humidity sensor High sensitivity Nafion/Graphene oxide films

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Indium oxide thick-films decorated with PdO and PtO2 particles for oxygen detection in humid environments

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PHYSICA SCRIPTA 2024年第12期99卷 125028-125028页

作者： Sari, Wangi P. Rifai, Achmad P. Smith, Peter Agbroko, Samuel O. Covington, James Univ Gadjah Mada Dept Mech & Ind Engn Yogyakarta Indonesia McGowan Sensor Labs Ltd Abingdon OX14 3DB England Univ Warwick Sch Engn Coventry CV4 7AL England

Thick film indium oxide chemiresistive sensors decorated with PdO and PtO2 particles were investigated for oxygen detection under humid conditions (tested ranging from 20%-80% RH) across a temperature range of 50 degrees C to 400 degrees C. The PtO2-decorated In2O3 sensors demonstrated a significantly higher response to oxygen, showing a 500% increase at 200 degrees C compared to the PdO-decorated sensors (response values of 41 and 8, respectively). Tests in dry air were conducted to assess the effect of humidity on sensor performance, revealing a maximum response of 74 for PtO2-In2O3 at 400 degrees C, more than three times higher than the response of 22 for PdO-In2O3. Selectivity tests confirmed that the sensors responded more strongly to oxygen than to interfering gases. The integration of an active carbon cloth (ACC) filter effectively reduced interferences from isobutylene and ethylene, enhancing sensor's selectivity. A comparison of both sensors demonstrated that PtO2-decorated In2O3 has greater potential as an alternative to existing Pb-based electrochemical oxygen sensors, particularly in humid environments.

关键词： indium oxide oxygen detection chemiresistive sensor PdO PtO2 thick film ACC filter

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Soft and Integrable Multimodal Artificial Mechanoreceptors Toward Human sensor of Skin

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ADVANCED FUNCTIONAL MATERIALS 2025年第13期35卷

作者： Seo, Seunghwan Na, Hyun-Min Kim, Jin-Yup Kim, Dokyun Kim, Daekyum Chun, Kyoung-Yong Han, Chang-Soo Korea Univ Sch Mech Engn Seoul 02841 South Korea Korea Univ Somatosensory Mol Biomimet Res Ctr Seoul 02841 South Korea Korea Univ Sch Smart Mobil Seoul 02841 South Korea

Herein, the development and characterization of three distinct artificial mechanoreceptor sensors meticulously engineered is reported to emulate human skin. By mimicking the morphology, structure, and response characteristics (including preferential sensitivity, adaptation profile, and frequency response) of biological mechanoreceptors, artificial Meissner, Merkel, and Ruffini sensors capable of detecting pressure, shear, and tensile deformations with high fidelity are successfully fabricated. In situ experiments, designed to mimic physiological conditions, demonstrate that the integrated sensor array, mimicking human fingertips, can accurately discriminate seven Braille characters, five distinct surface textures, a grating with ridges, and four-step delivery stages of an object. Furthermore, a woolen glove incorporating 15 multimodal sensors are developed, which exhibits enhanced classification capabilities for eight objects of varying sizes and surface roughness. Notably, the trimodal sensor integration demonstrates superior recognition speed and precision compared to uni- or bimodal configurations, while also improving tactile identification intuition. This biomimetic mechanoreceptor sensor system demonstrates comprehensive and synergistic recognition of diverse stimuli and objects, potentially overcoming technological limitations in applications requiring human-like tactile perception, such as advanced prosthetics, robotics, and immersive augmented and virtual reality interfaces.

关键词： artificial mechanoreceptor multimodal perception tactile sensor

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Compact and Fully Integrated LED Quantum sensor Based on NV Centers in Diamond

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sensors 2024年第3期24卷 743页

作者： Pogorzelski, Jens Horsthemke, Ludwig Homrighausen, Jonas Stiegekoetter, Dennis Gregor, Markus Gloesekoetter, Peter Munster Univ Appl Sci Dept Elect Engn & Comp Sci Stegerwaldstr 39 D-48565 Steinfurt Germany Munster Univ Appl Sci Dept Engn Phys Stegerwaldstr 39 D-48565 Steinfurt Germany

Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in diamond nano or microcrystals is a promising technology for sensitive, integrated magnetic-field sensors. Currently, this technology is still cost-intensive and mainly found in research. Here we propose one of the smallest fully integrated quantum sensors to date based on nitrogen vacancy (NV) centers in diamond microcrystals. It is an extremely cost-effective device that integrates a pump light source, photodiode, microwave antenna, filtering and fluorescence detection. Thus, the sensor offers an all-electric interface without the need to adjust or connect optical components. A sensitivity of 28.32nT/Hz and a theoretical shot noise limited sensitivity of 2.87 nT/Hz is reached. Since only generally available parts were used, the sensor can be easily produced in a small series. The form factor of (6.9 x 3.9 x 15.9) mm3 combined with the integration level is the smallest fully integrated NV-based sensor proposed so far. With a power consumption of around 0.1W, this sensor becomes interesting for a wide range of stationary and handheld systems. This development paves the way for the wide usage of quantum magnetometers in non-laboratory environments and technical applications.

关键词： NV center diamond microcrystal magnetometry integrated quantum sensor

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sensor-Enhanced Deep Learning for ECG Arrhythmia Detection: Integrating Multiscale Convolutional and Self-Attentive GRU Networks

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IEEE sensors JOURNAL 2024年第17期24卷 28083-28093页

作者： Kondaveeti, Muralikrishna Sailaja, M. Jawaharlal Nehru Technol Univ Dept Elect & Commun Engn Kakinada 533003 Andhra Pradesh India

The real-time monitoring of electrical activities of the heart using a wearable electrocardiogram (ECG) sensor plays a vital role in providing real-time data and allows for the immediate detection of arrhythmia events for patients with high risk of cardiac diseases. This work presents an architecture that capitalizes on multiscale convolutional neural networks (CNNs) and gated recurrent units (GRUs), augmented with a self-attention mechanism, to thoroughly analyze both spatial and temporal aspects of ECG signals. This innovative integration enables the model to detect nuanced arrhythmic patterns effectively, thereby addressing the complex nature of ECG interpretation. The proposed model's performance is substantiated by its high diagnostic accuracy, reaching a peak accuracy of 99.63%, which is a marked improvement over the existing models. It is optimized for real-time analysis, featuring a significant reduction in computational complexity and memory usage, distinguishing it from other high-performing but computationally intensive frameworks. Moreover, this article delineates the signal lengths and datasets, ensuring a comprehensive validation against established benchmarks. The system demonstrates 98.39%, 99.63%, and 99.00% of precision, recall, and F1-scores, respectively. The work also elucidate the importance of sensor technology in enhancing diagnostic precision, detailing the role of sensor sensitivity and specificity in our system's overall efficacy.

关键词： Electrocardiography Arrhythmia sensors Accuracy Data models Medical services Deep learning Arrhythmia diagnosis electrocardiogram (ECG) sensor gated recurrent units (GRUs) multiscale feature extraction self-attention mechanisms

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integration of sensor-Based Technology in Mental Healthcare: A Systematic Scoping Review

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Journal of Technology in Behavioral Science 2025年第1期10卷 201-217页

作者： Bosch, R. Noordzij, M.L. Westerhof, G.J. Bohlmeijer, E.T. Forensic Psychiatric Department ‘GGNet De Boog’ Warnsveld Netherlands Department of Psychology Health and Technology University of Twente Drienerlolaan 5 Enschede 7522 NB Netherlands GGNet Scelta Apeldoorn Netherlands Henriette Hartsen Clinic Tactus Zutphen Netherlands

sensor-based technologies can collect objective and real-time data on physiological, behavioral, and contextual factors related to mental disorders. This not only holds potential for mental healthcare but also comes with challenges, such as handling large amounts of data and supporting the integration of sensors in clinical practice. This systematic scoping review aims to provide an overview of studies explicitly addressing the integration of sensor-based technology in mental healthcare by reporting on the way that therapists and patients work with sensors. In addition, we explore barriers and facilitators for the integration of sensor-based technology in clinical practice. Four databases were searched on April 5, 2023. Studies on sensor-based technology integrated in mental healthcare were included. A total of 14 studies were included. In these studies, a variety of sensor-based technologies were used. All studies were conducted between 2016 and 2022. Most studies showed that sensor-based technologies are accepted by patients and that their use is associated with symptom reduction. However, most studies did not systematically report on barriers and facilitators and mainly focused on the technology itself rather than on the broader context of its intended use. Also, sensor-based technologies are not yet embedded in clinical protocols. From the current review, we can conclude that sensor-based technologies are sufficiently accepted and feasible, and that sensors are promising for enhancing clinical outcomes. However, sensors are not properly integrated in treatment protocols yet. Therefore, we propose a next phase in research on sensor-based technology in mental healthcare treatment. This next phase asks for a multifaceted approach consisting of (1) embedding sensor-based technology in treatment protocols in co-creation with patients and clinicians, (2) examining the feasibility of these interventions together with small-scale evidence studies, and (3) systematically

关键词： Implementation Mental health Scoping review sensor-based technology

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Robust Distribution-Aware Ensemble Learning for Multi-sensor Systems

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sensors 2025年第3期25卷 831-831页

作者： Goodarzi, Payman Schauer, Julian Schuetze, Andreas Saarland Univ Lab Measurement Technol D-66123 Saarbrucken Germany

Detecting distribution and domain shifts is critical in decision-sensitive applications, such as industrial monitoring systems. This paper introduces a novel, robust multi-sensor ensemble framework that integrates principles of automated machine learning (AutoML) to address the challenges of domain shifts and variability in sensor data. By leveraging diverse model architectures, hyperparameters (HPs), and decision aggregation strategies, the proposed framework enhances adaptability to unnoticed distribution shifts. The method effectively handles tasks with various data properties, such as the number of sensors, data length, and information domains. Additionally, the integration of HP optimization and model selection significantly reduces the training cost of ensemble models. Extensive evaluations on five publicly available datasets demonstrate the effectiveness of the proposed framework in both targeted supervised tasks and unsupervised distribution shift detection. The proposed method significantly improves common evaluation metrics compared to single-model baselines. Across the selected datasets, the framework achieves near-perfect test accuracy for classification tasks, leveraging the AutoML approach. Additionally, it effectively identifies distribution shifts in the same scenarios, with an average AUROC of 90% and an FPR95 of 20%. This study represents a practical step toward a distribution-aware front-end approach for addressing challenges in industrial applications under real-world scenarios using AutoML, highlighting the novelty of the method.

关键词： prognostics and health management (PHM) sensor-based systems AutoML deep ensemble learning out-of-distribution (OOD) detection domain adaptation structural health monitoring condition monitoring anomaly detection

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High-sensitivity ocean temperature sensor using a reflective optical microfiber coupler and machine learning methods

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APPLIED OPTICS 2024年第34期63卷 8771-8779页

作者： Xu, Yan Chen, Yuren Cui, Chenghao Lv, Wenhao Liu, Xiaojuan Shandong Univ Technol Sch Phys & Optoelect Engn Zibo 255000 Peoples R China Natl Univ Def Technol Coll Sci Changsha 410073 Peoples R China

This paper proposes a novel seawater temperature sensor, to the best of our knowledge, that utilizes an optical microfiber coupler combined with a reflective silver mirror (OMCM). The sensor's sensitivity and durability are enhanced by encapsulating it in polydimethylsiloxane (PDMS). Additionally, a specially designed metal casing prevents the OMCM from responding to pressure, thus avoiding the challenge of multi-parameter demodulation and increasing its adaptability to harsh environments. The paper analyzes the advantages of the new sensor structure and evaluates its performance in terms of temperature sensitivity and compressive strength through experiments. Finally, the paper employs machine learning demodulation methods. Compared with traditional demodulation stantial reduction in the demodulation error. Specifically, the mean absolute percentage error (MAPE) relative to the full scale drops from 2.16% to 0.157%. This paper provides an effective solution for high-precision monitoring of the ocean environmental temperature. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Deep learning Fiber Bragg grating sensors Fiber optic sensors sensor performance Surface plasmon resonance Temperature sensors

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Amplifying Electron-Donor Signal of the "Water Gate" Enabled Low Detection Ability of a Field-Effect Transistor-Based Humidity sensor

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ANALYTICAL CHEMISTRY 2025年第5期97卷 2779-2785页

作者： Liu, Bohao Chen, Qingqing Hu, Jinyong Zhang, Yong Xiangtan Univ Sch Phys & Optoelect Xiangtan 411105 Peoples R China Xiangtan Univ Hunan Inst Adv Sensing & Informat Technol Xiangtan 411105 Peoples R China

Low humidity detection down to the parts per million level is urgently demanded in various industrial applications. The hardly detected tiny electrical signal variations caused by a very small amount of water adsorption are one of the intrinsic reasons that restrain the detection limit of the humidity sensors. Herein, a carbon-based field-effect transistor (FET) humidity sensor utilizing adsorbed water as the dual function of a sensing gate and analyte was proposed. Owing to the electron donor property of the "water gate" that can serve as a negative voltage exerted on the dielectric layer, the electrical conductivity of the FET's channel can be significantly modulated, therefore realizing signal amplification. The proposed sensor presents a detection limit of lower than 1% RH. Besides, the fabricated sensors show good batch consistency (response deviation of 0.5%), repeatability, long-term stability, and acceptable hysteresis (6.3% relative humidity (RH)) in humidity detection. We hope that our work can offer a novel strategy for the application and integration of low humidity detection from the device aspect rather than sensing materials synthesis.

关键词： Humidity sensors

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