Sensors最新文献

{"title":"A Pilot Study of the Feasibility of In-Ear EEG for Long-Term Temporal Lobe Brain Wave Monitoring.","authors":"Andy Ho Wing Chan, Ryan C Emadi, Andy Lin, Mark J Schroeder, Ravinderjit Singh, Riaz Shaik, Mary-Catherine George, Jack Gomberg, Onome Eka, Toni Kavanagh, Ji Yeoun Jenna Yoo, Joanna C Jen, Ali Tajer, Anuradha Singh, Mijail Serruya, Achintya K Bhowmik, Muhammad A Parvaz","doi":"10.3390/s26196343","DOIUrl":"https://doi.org/10.3390/s26196343","url":null,"abstract":"<p><p><b>Background:</b> Traditional scalp electroencephalography (EEG), though clinically validated, presents significant limitations, including lengthy setup, patient discomfort, and limited mobility. These factors hinder its utility for long-term ambulatory monitoring. In-ear EEG offers a promising alternative by leveraging the ear canal's anatomical proximity to the temporal lobes and natural mechanical stability. To address this, we developed SeizEAR, a standardized, three-size in-ear EEG system using paste-based electrodes with cross-ear referencing. <b>Methods:</b> This pilot study evaluated SeizEAR devices featuring small, medium, and large earpieces with superior and inferior paste-based electrodes in each ear, configured in a cross-ear reference scheme. It included five healthy adults who underwent recording sessions of approximately three hours (2.4 to 3.3 h). Electrode impedance was monitored against the acquisition system's threshold indicator, with simultaneous scalp EEG from T7/T8 electrodes serving as the reference. Participants rated comfort on a 0-5 Likert scale every 30 min. <b>Results:</b> In-ear recordings showed moderate, band-dependent correspondence with ipsilateral temporal scalp electrodes, strongest in the delta and alpha bands and weakest in beta, and correspondence was consistently higher against a geometrically matched T7-T8 bipolar derivation than against a single referenced electrode. In-ear alpha reactivity to eye closure was present but attenuated relative to scalp. Comfort ratings remained high over the final two hours of wear, with no reported adverse events. <b>Conclusions:</b> SeizEAR acquired in-ear EEG that corresponded moderately with temporal scalp EEG and was well-tolerated over multi-hour wear in healthy adults. These preliminary findings support further development of a standardized in-ear EEG system and require confirmation in an adequately powered sample.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Budget-Constrained Edge Orchestration of DAG-Based Sensor-Data Workflows with Multicast Result Dissemination.","authors":"Shijie Jia, Jianwei Zhang","doi":"10.3390/s26196348","DOIUrl":"https://doi.org/10.3390/s26196348","url":null,"abstract":"<p><p>Distributed sensing applications increasingly transform observations through multi-stage pipelines executed across heterogeneous edge-cloud resources. A sensing request is operationally complete only after its actionable output reaches all subscribed monitoring or control endpoints. However, workflow scheduling and result dissemination are commonly optimized separately, even though the server executing the sink task determines the source of dissemination. This paper studies their coupling under a per-request budget. We model each sensor-data workflow as a directed acyclic graph of service-dependent processing stages and intermediate-data transfers, followed by shared delivery of the sink output. We formulate lexicographic minimization of end-to-end sensing-response delay and total cost, subject to precedence, server capacity, service availability, multicast connectivity, and budget constraints. We then propose Priority-Aware Constraint-based Large Neighborhood Search (PAC-LNS), which combines topology-aware prioritization, dynamic ready-window scheduling, bounded local refinement, dissemination-budget reservation, and shared-tree construction. We implement PAC-LNS scheduling and shared-tree construction in MATLAB and evaluate synthetic DAGs and Alibaba trace-derived computation workloads: feasibility determines admission, delay and cost are compared on common successful requests, and acceptance rate and online runtime are reported separately. In trace replay with R=5000, PAC-LNS accepts 89.04-90.12% of requests as the budget increases from B=100 to B=200, while its online scheduling and tree-construction time averages 16.644 ms per request across these settings. These results support joint processing and delivery orchestration for budget-constrained edge-assisted sensing services.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 3.2 Gb/s SPAD-Based Multi-Channel QRNG Chip with Low-Optical-Power Operation via Rolling-Sampling Temporal Decorrelation.","authors":"Tuo Zhou, Jiachang Li, Chao Luo, Zirui Zhang, Xiangshun Kong, Cheng Mao, Feng Yan","doi":"10.3390/s26196350","DOIUrl":"https://doi.org/10.3390/s26196350","url":null,"abstract":"<p><p>Random numbers play a vital role in modern information security, where quantum random number generators (QRNGs) based on single-photon avalanche diodes (SPADs) offer a promising physical platform for quantum random-number generation. However, practical SPAD QRNGs can exhibit temporal correlation arising from finite photon-event statistics and detector nonidealities. To overcome these limitations, this paper presents a high-speed, 256-channel SPAD QRNG chip, featuring a 256 × 512-pixel array integrated with a rolling-sampling time-division multiplexing architecture. By virtue of the rolling-sampling mechanism, the single-pixel sampling interval is extended to 40.96 μs, which substantially reduces the measured temporal correlation by increasing the per-pixel revisit interval while preserving aggregate throughput. Within one complete operating cycle, the chip generates 256 random bits simultaneously, achieving a maximum aggregate raw output bitrate of 3.2 Gb/s without digital post-processing. An FPGA-based test platform was constructed for experimental verification. Measurements demonstrate that under standard indoor illumination (8 W/m²), the generated raw bitstreams pass all 15 NIST SP 800-22 statistical randomness tests at 3.2 Gb/s without post-processing. Furthermore, under controlled 530 nm illumination, the measured lag-1 serial autocorrelation coefficient decreases below the 10^-3 reference level at an incident optical power of 11.6 μW. The proposed chip offers a low-optical-power, high-throughput solution for integrated hardware security.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Raman Thermometry of Confined Gas Milli-Flows.","authors":"Guzmán Tejeda, Carlos Álvarez, José M Fernández","doi":"10.3390/s26196344","DOIUrl":"https://doi.org/10.3390/s26196344","url":null,"abstract":"<p><p>The temperature of rarefied gas flows inside small channels is hard to measure without disturbing the flow. We present here an optical approach with submillimeter spatial resolution, based on Raman spectroscopy, and several examples of its application to gas flows within millimeter-sized channels. For this work, we have designed and built several channels with different geometries, and forced thermal gradients between some of their surfaces while flowing N₂, CO₂ and H₂ through the channels. The pressures ranged from atmospheric down to 11 mbar, and the flow velocities ranged from 8 to over 450 cm/s. The most rarefied flows lie in the slip regime (Kn ≥0.001). Raman spectra of the flowing gases were recorded inside the channels, and the intensities of the rotational lines were analyzed in terms of Boltzmann plots to retrieve the local gas temperature. It is demonstrated that Raman spectroscopy is able to measure the temperature profiles across dimensions as short as 1 mm inside the channels. The achieved precisions (1-σ uncertainties) at 100 mbar are 0.8 K for CO₂, 2.0 K for N₂, and 3.7 K for H₂.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"VFedA: A Vertical Federated Learning Framework with Relational Alignment for Cross-Regional False Data Injection Attack Detection in Smart Grids.","authors":"Binyuan Yan, Guozhi Yang, Xin Che, Xiaohan Huang","doi":"10.3390/s26196336","DOIUrl":"https://doi.org/10.3390/s26196336","url":null,"abstract":"<p><p>Large-scale smart grids have introduced significant challenges for false data injection attack (FDIA) detection due to the distributed nature of power system operation and the limited observability of individual regions. Existing horizontal federated learning approaches enable collaborative model training without sharing raw data; however, they rely on local information and often fail to capture the global operational characteristics needed to detect sophisticated attacks. To address this limitation, the present paper proposes VFedA, a federated vertical relational alignment framework for FDIA detection via cross-regional feature fusion. Specifically, each regional client employs a self-supervised spatiotemporal contrastive learning encoder to extract local representations from measurements. The extracted representations are uploaded to a control center and concatenated to construct global feature representations for attack detection. In order to mitigate inconsistencies across heterogeneous regional feature spaces, a relational alignment mechanism is introduced to enforce structural consistency by aligning similarity matrices derived from local representations. The proposed approach enables effective cross-regional information fusion while preserving data privacy. Extensive experiments are conducted on IEEE 30-bus and IEEE 118-bus benchmark systems. The results demonstrate that VFedA consistently outperforms conventional horizontal federated learning methods and achieves performance comparable to centralized detection models.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A CMOS Capacitive Fingerprint Sensor Chip with Column-Shared Charge-Accumulation Readout for Ridge-Valley Contrast Enhancement.","authors":"Kyungsaeng Kim","doi":"10.3390/s26196335","DOIUrl":"https://doi.org/10.3390/s26196335","url":null,"abstract":"<p><p>Capacitive fingerprint sensors are widely used in mobile, access-control, IoT, and biometric authentication systems because of their compact size, low power consumption, low cost, and CMOS compatibility. However, the small capacitance difference between fingerprint ridges and valleys can be degraded by passivation thickness, skin condition, contact pressure, contamination, and circuit noise, especially in high-resolution sensors with reduced pixel pitch. This work presents a CMOS capacitive fingerprint sensor chip with a column-shared charge-accumulation readout to enhance ridge-valley contrast. The proposed readout repeatedly senses the same pixel and accumulates the resulting charge-domain signals at the column level before analog-to-digital conversion, improving ridge-valley separability without increasing pixel-level circuit complexity. The chip was fabricated in a 0.18 μm CMOS process and includes a 144 × 40 sensor array with a 50 μm pixel pitch, corresponding to approximately 508 dpi. Fingerprint images were acquired from two participants for accumulation numbers from <i>N</i> = 1 to <i>N</i> = 5. After image-quality screening, the average ridge-valley contrast increased from 5.71% to 43.86%, corresponding to a contrast ratio of approximately 7.68, while the average image-based ridge-valley SNR remained above 12 dB. The Energy-Contrast Efficiency (ECE) increased with <i>N</i>, although capture time and frame energy also increased. These results indicate that the proposed readout enhances ridge-valley contrast while the image-based ridge-valley SNR remains relatively stable.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TD-YOLO: Tomato Leaf Disease Detection Based on Hypergraph Multi-Scale Aggregation.","authors":"Yuwen Liu, Xi Feng, Mengting Liu, Shunxin Cao","doi":"10.3390/s26196340","DOIUrl":"https://doi.org/10.3390/s26196340","url":null,"abstract":"<p><p>To address the challenges of tomato leaf diseases, including significant variations in disease size, discrete spatial distribution in complex field environments, and the difficulty in distinguishing early symptoms of certain diseases, which lead to low detection accuracy and a large number of model parameters, this paper proposes a tomato leaf disease detection model, TD-YOLO, based on multi-scale hypergraph aggregation. During the feature extraction stage, the RetC3k2 is employed to enhance the shallow network's ability to detect disease regions. The C2TSSA attention mechanism is introduced to filter out key diseases and suppress background interference. At the same time, the GDown adaptive downsampling module is designed to reduce the model size while preserving feature integrity. In the neck network section, a multi-scale hypergraph aggregation structure is constructed by integrating a multi-scale semantic aggregation layer, the HyperConv, and a MANet network. By connecting disease features at different spatial locations through hyperedges, the network models high-order associative relationships and achieves a refined representation of multi-scale features. Experimental results show that on the Tomato-Village-Diseases dataset, TD-YOLO achieves an mAP50 of 92.5%, a 7.1% improvement over the baseline YOLOv11, with only 2.21M parameters and a computational cost of 6.8 GFLOPs. On the Tomato-Leaf-2-v1 dataset, the mAP50 reached 81.0%, outperforming all comparison models and demonstrating the model's strong adaptability. This study provides an efficient and feasible technical solution for the accurate detection of tomato leaf diseases.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic Admission Control with Dual-Window Channel Occupancy Statistics for Statistical Priority-Based Multiple Access.","authors":"Yu Wu, Byung-Seo Kim","doi":"10.3390/s26196347","DOIUrl":"https://doi.org/10.3390/s26196347","url":null,"abstract":"<p><p>Statistical priority-based multiple access (SPMA) provides differentiated channel access for multi-priority traffic by comparing the channel occupancy statistic (COS) with hierarchical thresholds. However, existing threshold-setting methods ignore the inherent fluctuation in the COS caused by random traffic arrivals, so that a large fraction of time slots are incorrectly blocked and the channel performance degrades sharply under overload. To address this issue, this paper proposes DW-PA-SPMA, a dual-window probabilistic admission SPMA protocol. Its core idea is to move traffic management from post-hoc threshold interception at the transmission time slot to probabilistic admission at the packet generation instant: based on a capacity budget that relates the available channel capacity to the traffic demand of each priority, excess packets are truncated at the source following the principle of \"highest priority first, remaining capacity for lower priorities\", so that no queue buffers or channel contention resources are wasted. A dual-window statistic separates instantaneous fluctuation from the steady-state trend, and a dual-EWMA difference method estimates the load variation time scale online, allowing the long window length to adapt to traffic variations without prior load information. Simulation results under a six-segment time-varying load show that the protocol keeps the highest-priority end-to-end completion rate above the 90% target from light load to full load and remains stable under 2.0× overload, whereas existing threshold-based protocols degrade sharply in the heavy-load segment, demonstrating the advantages of the proposed protocol in dynamic traffic scenarios.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement-Based Prediction of Inductive Ignition Risk Boundaries for Bridgewire Electro-Explosive Devices Under Transient Magnetic Fields.","authors":"Hongyu Li, Yan Hu, Lizhi Wu, Yinghua Ye, Ruiqi Shen","doi":"10.3390/s26196345","DOIUrl":"https://doi.org/10.3390/s26196345","url":null,"abstract":"<p><p>Predicting the ignition risk of bridgewire electro-explosive devices (EEDs) under transient magnetic fields requires linking the local magnetic field history to the inductive response of the associated closed loop and the thermal response of the bridgewire-charge system. In this study, a measurement-grounded framework was developed by combining transient field measurement with a three-dimensional electromagnetic-thermal model. A custom inductive probe with a manufacturer-specified equivalent magnetic flux area of <i>A_p</i> = 12,029 mm² was used to obtain the local magnetic field rate history (<i>dB</i>/<i>dt</i>). In bench tests, the induced-voltage histories of closed loops with different measured areas were reconstructed from the probe signal using the loop-to-probe area ratio and used as inputs to the bridgewire-charge model. Three measured transient magnetic field waveforms were used to evaluate the predicted ignition boundaries. For Waveform I, the experimental and predicted critical-area intervals were (772, 824] and (804.2, 907.9] mm², respectively. For Waveforms II and III, the experimental interval (542, 583] mm² lay within the predicted interval (530.9, 615.8] mm². The evaluated framework was further applied to the projectile-fixed magnetic field history of a five-stage coilgun, yielding a predicted critical equivalent loop radius interval of (14, 15] mm. The results demonstrate that inductive ignition risk depends on closed-loop magnetic flux coupling and the complete transient excitation history rather than on peak magnetic flux density or peak <i>dB</i>/<i>dt</i> alone. The proposed method establishes a quantitative link among local transient magnetic field measurement, installed loop magnetic flux coupling, and device-level ignition risk boundaries, providing a practical framework for electromagnetic safety assessment of projectile-borne EEDs under complex transient magnetic field environments.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Innovative Decoupled Spatio-Vertical-Temporal Learning Model Based on Topography Guidance for Wind Vector Forecasting.","authors":"Xinyu Liu, Huan Li, Xinyue Mo","doi":"10.3390/s26196352","DOIUrl":"https://doi.org/10.3390/s26196352","url":null,"abstract":"<p><p>Accurate wind speed forecasting (WSF) is pivotal for the secure grid integration of wind farms and the optimization of power dispatching. However, the stochastic nature of atmospheric dynamics and their complex interactions with local terrain pose significant challenges. Traditional spatiotemporal models inherently suffer from severe homogenization, irreversibly destroying fine-grained aerodynamic textures and leading to cumulative directional errors over extended horizons. To dismantle these limitations, this study proposes a novel Topography-Guided Spatio-Vertical-Temporal Transformer (TG-SVTFormer) for the multi-step forecasting of zonal and meridional wind vectors. Specifically, a dual-stage topography-guided mechanism explicitly injects static geographical variables (elevation, slope, and roughness) into both the spatial encoding and microscopic decoding phases, imposing key physical constraints on aerodynamic friction. Furthermore, the architecture employs a structured decoupled learning paradigm: a re-engineered Mix-Transformer spatial encoder deliberately eliminates deep-stage downsampling in favor of dilated convolutions-drastically expanding the global receptive field while preserving the intrinsic meteorological textures. Subsequently, the temporal evolution hub explicitly decouples the vertical dimension, utilizing upper-air atmospheric states to guide the target surface layer via simulated vertical momentum transport. The experiments showed the accuracy of TG-SVTFormer in predicting the wind speed with mean absolute error of 0.71 m/s in 3 h, 0.85 m/s in 6 h, and 1.06 m/s in 12 h. Compared to five existing baseline WSF models, the proposed TG-SVTFormer model demonstrates superior performance in wind speed forecasting and, more importantly, offers a transferable and physics-informed framework that can be adapted to other terrain-complex regions and extended to related renewable-energy and air-quality forecasting tasks.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"26 19","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}