Array For Monitoring Research Articles

Machine learning-enabled attapulgite/polyimide nanofiber composite aerogels-based colorimetric sensor array for real-time monitoring of balsa fish freshness

This paper presents the development and application of attapulgite/polyimide nanofiber composite aerogels (ATP/PI NFAs) integrated with a range of acid-base indicators, fabricated using electrospinning and freeze-drying technologies. A detailed characterization of the ATP/PI NFAs revealed a 3D multi-level pore structure that enhanced the mass transfer of target gas molecules and their interaction with probe molecules. Utilizing machine learning approaches, we designed an ATP/PI NFAs-based colorimetric sensor array capable of real-time evaluation of balsa fish freshness. Color features sensitive to changes in freshness were selected using principal component analysis and random forest. Partial least squares regression and random forest regression models were established, achieving the prediction of total volatile basic nitrogen content in balsa fish. The system was validated using a national standard method to demonstrate its accuracy and practicality. The combination of advanced ATP/PI NFAs-based colorimetric sensor array with robust machine learning models paves the way for food safety monitoring.

Fully integrated sensor array for additives, permittivity, and pH monitoring for fishery

Additive abuse in fishery, such as tricaine methanesulfonate (MS222), ciprofloxacin (CPFX), and malachite green (MG), threatens public human health and interferes with the ecological equilibrium of water resources. However, the majority of the present detection methods suffer from high costs, complex operations, and poor portability. Therefore, real-time and rapid detection of the above additive by mobile devices is becoming increasingly important. Here we report the fabrication and performance of an entirely electrochemical system with USB-stick size for simultaneous detection of MS222, CPFX, and MG, as well as pH and permittivity. The limits of detections are 0.17, 0.67, and 0.28 µg/mL, while the resolution ratios are 10 %, 10 %, and 5 % for MS222, MG, and CPFX, respectively. For both pH and permittivity, they have linear regressions measured by brightness and capacitance of the sample respectively, at the range of 1.5–9 (pH) and 10–20 (permittivity). The interference experiments, using target analytes (40 μg/mL) and 15 interfering analytes (80 μg/mL), demonstrated the anti-interference performance of the sensor patches. The field studies on carps, catfishes, and chubs indicated that the developed integrated portable system could be used for real sample analysis with high performance.

Antibody-Based Array for Tacrolimus Immunosuppressant Monitoring with Planar Plastic Waveguides Activated with an Aminodextran-Lipase Conjugate.

Cyclic olefin copolymers (COC; e.g., Zeonor, Topas, Arton, etc.) are materials with outstanding properties for developing point-of-care systems; however, the lack of functional groups in their native form makes their application challenging. This work evaluates different strategies to functionalize commercially available Zeonor substrates, including oxygen plasma treatment, photochemical grafting, and direct surface amination using an amino dextran-lipase conjugate (ADLC). The modified surfaces were characterized by contact angle measurements, Fourier transform infrared-attenuated total reflection analysis, and fluorescence assays based on evanescent wave excitation. The bioaffinity activation through the ADLC approach results in a fast, simple, and reproducible approach that can be used further to conjugate carboxylated small molecules (e.g., haptens). The usefulness of this approach has been demonstrated by the development of a heterogeneous fluorescence immunoassay to detect tacrolimus (FK506) immunosuppressant drug using an array biosensor platform based on evanescence wave laser excitation and Zeonor-ADLC substrates. Surface modification with ADLC-bearing FK506 provides a 3D layer that efficiently leads to a remarkably low limit of detection (0.02 ng/mL) and IC50 (0.9 ng/mL) together with a wide dynamic range (0.07-11.3 ng/mL).

Data and early results from temporary seismic arrays for monitoring and investigating magmatic processes beneath Mt. Halla and Ulleung Island volcanoes, South Korea

Data and early results from temporary seismic arrays for monitoring and investigating magmatic processes beneath Mt. Halla and Ulleung Island volcanoes, South Korea

Use of a pressure sensor array for multifunctional patient monitoring in radiotherapy: A feasibility study.

Modern radiotherapeutic techniques, such as intensity-modulated radiation therapy or stereotactic body radiotherapy, require high-dose delivery precision. However, the precise localization of tumors during patient respiration remains a challenge. Therefore, it is essential to investigate effective methods for monitoring respiration to minimize potential complications. Despite several systems currently in clinical use, there are drawbacks, including the complexity of the setup, the discomfort to the patient, and the high cost. This study investigated the feasibility of using a novel pressure sensor array (PSA) as a tool to monitor respiration during radiotherapy treatments. The PSA was positioned between the treatment couch and the back of the patient lying on it and was intended to overcome some limitations of current methods. The main objectives included assessing the PSA's capability in monitoring respiratory behavior and to investigate prospective applications that extend beyond respiratory monitoring. A PSA with 31 pressure-sensing elements was used in 12 volunteers. The participants were instructed to breathe naturally while lying on a couch without any audio or visual guidance. The performance of the PSA was compared to that of a camera-based respiratory monitoring system (RPM, Varian, USA), which served as a reference. Several metrics, including pressure distribution, weight sensitivity, and correlations between PSA and RPM signals, were analyzed. The PSA's capacity to provide information on potential applications related to patient stability was also investigated. The linear relationship between the weight applied to the PSA and its output was demonstrated in this study, confirming its sensitivity to pressure changes. A comparison of PSA and RPM curves revealed a high correlation coefficient of 0.9391 on average, indicating consistent respiratory cycles. The PSA also effectively measured the weight distribution at the volunteer's back in real-time, which allows for monitoring the patient's movements during the radiotherapy. PSA is a promising candidate for effective respiratory monitoring during radiotherapy treatments. Its performance is comparable to the established RPM system, and its additional capabilities suggest its multifaceted utility. This paper shows the potential use of PSA for patient monitoring in radiotherapy and suggests possibilities for further research, including performance comparisons with other existing systems and real-patient applications with respiratory training.

Multi-directional strain sensor based on carbon nanotube array for human motion monitoring and gesture recognition

Flexible strain sensors have enormous application demands in health monitoring, soft robotics, and artificial skin. Traditional flexible strain sensors mainly focus on identifying strain amplitude. However, to determine complex movements, it is necessary for sensors to recognize not only the amplitude but also the direction of strain. Here, we propose a multi-directional strain sensor constructed from three flexible strain sensor units, which are based on a carbon nanotube (CNT) array, and configured in a right-angled triangle arrangement. Each strain sensor unit exhibited a strain detection range of over 90%, durability of over 5000 cycles, and fast response time (<150 ms). The multi-directional strain sensor can accurately identify the amplitude and direction (up to 180°) of the strain simultaneously. By optimizing the height and the size of the CNT array strips within the strain sensor unit, the preferred parameters for the sensor unit were determined. Further, by incorporating a neural network algorithm, the multi-directional strain sensor achieved synchronous detection of strain amplitude and direction with an accuracy rate exceeding 98%. Therefore, this work provides a new strategy for the design and construction of multi-directional strain sensors, underscoring their broad application potential in the fields of human motion monitoring and gesture recognition.

Ultra-low detection limit self-sensing nanocomposites with self-assembled conductive microsphere arrays for asphalt pavement health monitoring

Accurately monitoring micro-level strain within pavements poses a significant challenge in contemporary road engineering, limiting the effectiveness of early-stage pavement health diagnostics. Addressing this critical gap, this study introduces an innovative ultra-low detection limit sensor, specifically designed for intricate pavement health monitoring. It pivots on the unique structural design of a well-ordered 3D conductive network, where the self-assembly effect of microsphere arrays ingeniously mitigates the prevalent issue of nanofiller agglomeration within polymer matrices. The study highlights the significant role of carbon nanotubes (CNTs) length in shaping the structure of conductive networks, revealing that while longer CNTs lead to less uniform microsphere assemblies, they significantly enhance the bridging effect crucial for conductive pathways. To balance these traits, surface chemical modifications were strategically applied, effectively enhancing microsphere organization and dispersion, thereby elevating the conductive and sensing performance. The optimized sensor stands out for the ultra-low detection limit of 0.0005% (5 uε), significantly surpassing those of current strain sensors. Moreover, it exhibits remarkable sensitivity, evidenced by a gauge factor of 13.2, along with swift response and recovery times of 19 ms and 26 ms respectively, and impressive durability, enduring over 100,000 loading-unloading cycles. Field tests under diverse vehicular loads and speeds further validate the sensor's accuracy in capturing dynamic responses within pavement structures, a key factor in proactive pavement maintenance and management. Hence, this advancement shows promise in contributing to the development of safer and more resilient road networks, playing a beneficial role in the significant progress of intelligent transportation and sustainable infrastructure management.

Plant Tattoo Sensor Array for Leaf Relative Water Content, Surface Temperature, and Bioelectric Potential Monitoring

AbstractThis study presents a wearable plant tattoo sensor array designed for continuous monitoring of leaf temperature, relative water content, and biopotential. Current plant wearable sensor technologies often require relatively bulky substrates for sensor support and adhesives for leaf attachment, which potentially can hinder plant growth and affect long‐term measurements. The multifunctional tattoo sensor array overcomes these issues by adhering directly to the leaf surface without the need for additional supporting structures or glues. This array includes a biopotential electrode, a resistive temperature sensor, and an impedimetric water content sensor, all constructed using laminated gold‐on‐polymer thin‐film patterns. Due to their mechanical flexibility, stretchability, and conformability, the sensors can seamlessly attach to leaves via van der Waals force. Performances of these sensors are evaluated to explore plant responses under diverse growth environments. This sensor array is capable of both short‐term and long‐term monitoring, offering continuous data and detailed insights into plant physiological responses to various stress conditions.

An integrated wearable differential microneedle array for continuous glucose monitoring in interstitial fluids

Monitoring biomarkers in human interstitial fluids (ISF) using microneedle sensors has been extensively studied. However, most of the previous studies were limited to simple in vitro demonstrations and lacked system integration and analytical performance. Here we report a miniaturized, high-precision, fully integrated wearable electrochemical microneedle sensing device that works with a customized smartphone application to wirelessly and in real-time monitor glucose in human ISF. A microneedle array fabrication method is proposed which enables multiple individually addressable, regionally separated sensing electrodes on a single microneedle system. As a demonstration, a glucose sensor and a differential sensor are integrated in a single sensing patch. The differential sensing electrodes can eliminate common-mode interference signals, thus significantly improving the detection accuracy. The basic mechanism of microneedle penetration into the skin was analyzed using the finite element method (FEM). By optimizing the structure of the microneedle, the puncture efficiency was improved while the puncture force was reduced. The electrochemical properties, biocompatibility, and system stability of the microneedle sensing device were characterized before human application. The test results were closely correlated with the gold standard (blood). The platform can be used not only for glucose detection, but also for various ISF biomarkers, and it expands the potential of microneedle technology in wearable sensing.

Superelastic bamboo fiber-based spongy aerogel for flexible piezoresistive sensors with wide response range and high sensitivity

Superelastic, breathable, and flexible piezoresistive sensors with excellent sensing performance are drawing tremendous attention in wearable electronics and sleeping furnishings. However, simultaneous realization of their high performance is still a huge challenge. In this study, inspired by the pore structure of natural sponges, a high-performance sponge-like bamboo fiber/graphene oxide aerogel piezoresistive sensor (M−CBF−rGO) was prepared utilizing bamboo fibers (BFs) and graphene oxide (GO) as raw materials through freeze casting and carbonization. Benefiting from the unique porous structure with effective absorbing/releasing energy, the M−CBF−rGO aerogel sensor exhibits excellent superelasticity (not being destroyed under 90 % deformation), mechanical durability (7,000 cycles), and good breathability. Moreover, the M−CBF−rGO sensor demonstrates ultra-high strain sensitivity (892.9), a wide detection range (0–300 kPa), and a fast recovery time (20 ms). Taking advantage of these benefits, the M−CBF−rGO sensor can not only be applied to detect human signals ranging from finger motion to swallowing recognition, but also integrated into the cushioning materials of upholstered furniture to generate a sensing array for monitoring and recogniting human activity including sitting postures and sleeping positions in real-time. This sensor demonstrates the potential application prospects in the fields of human health diagnosis, smart wearable products, and intelligent upholstered furniture.

Self‐Powered Flexible Sensor Array for Dynamic Pressure Monitoring

AbstractFlexible pressure sensors are valuable in applications such as electronic skin, smart robots, artificial prosthetics, and wearable electronics. In this study, a fully packaged, flexible, self‐powered, long‐term stable sensor array based on piezoelectrets is developed for pressure monitoring. A pressure sensor with a microcavity structure and a thickness of 500 µm achieved an impressive piezoelectric coefficient of 23.8 pC N−1 and a fast response time of 93 ms. The sensor yielded an output voltage of 0.26 V when subjected to a force using 0.3 g soybeans, and it displayed a remarkable linear relationship (R2 = 0.992) between force and electricity with pressure ranging from 1.4 to 13.6 N and a sensitivity of 9 mV N−1. Real‐time monitoring of sound vibration, radial artery pulse, and finger movement is demonstrated along with the successful recording of dynamic pressure changes within the porcine knee joint. It holds potential for fields such as monitoring pressure changes in the movement of human bodies and robotics and can contribute significantly to pressure assessment during total knee replacement.

Discrete ZnO p-n homojunction piezoelectric arrays for self-powered human motion monitoring

Zinc oxide (ZnO), as a typical piezoelectric semiconductor, has gained significant attention in the field of wearable electromechanical coupling. However, the presence of an intrinsic screening effect becomes a bottleneck in developing high-performance ZnO-based piezoelectric devices. To address this limitation, we propose the formation of p-n homojunction by La doping in ZnO nanorods (NRs) as well as discrete structural design to improve their electrical output and flexibility. The enhanced performance and the mechanism behind it are explored and revealed in terms of morphology, structure, built-in electric field, depletion layer width, and junction capacitance, respectively. Benefitting from the excellent electromechanical coupling performance of the developed devices, different human motions can be recognized and classified with the aid of machine learning. These findings provide a new insight into the impact of doping on the output performance of piezoelectric semiconductor devices, thus facilitating advancements in piezoelectric device design and application exploration.

Flexible LC Sensor Array for Wireless Multizone Pressure Monitoring

Flexible <i>LC</i> Sensor Array for Wireless Multizone Pressure Monitoring

Species-specific SNP arrays for non-invasive genetic monitoring of a vulnerable bat

Genetic tagging from scats is one of the minimally invasive sampling (MIS) monitoring approaches commonly used to guide management decisions and evaluate conservation efforts. Microsatellite markers have traditionally been used but are prone to genotyping errors. Here, we present a novel method for individual identification in the Threatened ghost bat Macroderma gigas using custom-designed Single Nucleotide Polymorphism (SNP) arrays on the MassARRAY system. We identified 611 informative SNPs from DArTseq data from which three SNP panels (44–50 SNPs per panel) were designed. We applied SNP genotyping and molecular sexing to 209 M. gigas scats collected from seven caves in the Pilbara, Western Australia, employing a two-step genotyping protocol and identifying unique genotypes using a custom-made R package, ScatMatch. Following data cleaning, the average amplification rate was 0.90 ± 0.01 and SNP genotyping errors were low (allelic dropout 0.003 ± 0.000) allowing clustering of scats based on one or fewer allelic mismatches. We identified 19 unique bats (9 confirmed/likely males and 10 confirmed/likely females) from a maternity and multiple transitory roosts, with two male bats detected using roosts, 9 km and 47 m apart. The accuracy of our SNP panels enabled a high level of confidence in the identification of individual bats. Targeted SNP genotyping is a valuable tool for monitoring and tracking of non-model species through a minimally invasive sampling approach.

Design and Optimization of Flexible and Stretchable Ultrasonic Transducer Array for Arterial Blood Pressure Monitoring

Design and Optimization of Flexible and Stretchable Ultrasonic Transducer Array for Arterial Blood Pressure Monitoring

Reconstruction of the Frequency-Wavenumber Spectrum of Water Waves With an Airborne Acoustic Doppler Array for Noncontact River Monitoring

Reconstruction of the Frequency-Wavenumber Spectrum of Water Waves With an Airborne Acoustic Doppler Array for Noncontact River Monitoring

Supervised Contrastive Learning Framework and Hardware Implementation of Learned ResNet for Real-time Respiratory Sound Classification.

This paper presents a supervised contrastive learning (SCL) framework for respiratory sound classification and the hardware implementation of learned ResNet on field programmable gate array (FPGA) for real-time monitoring. At the algorithmic level, multiple techniques such as features augmentation and MixUp are combined holistically to mitigate the impact of data scarcity and imbalanced classes in the training dataset. Bayesian optimization further enhances the classification accuracy through parameter tuning in pre-processing and SCL. The proposed framework achieves 0.8725 total score (including runtime score) on a ResNet-18 model in both event and record multi-class classification tasks using the SJTU Paediatric Respiratory Sound Database (SPRSound). In addition, algorithm-hardware co-optimizations including Quantization-Aware Training (QAT), merge of network layers, optimization of memory size and number of parallel threads are performed for hardware implementation on FPGA. This approach reduces 40% model size and 70% computation latency. The learned ResNet is implemented on a Xilinx Zynq ZCU102 FPGA with 16ms latency and less than 2% inference score degradation compared to the software model.

LTCC With Temperature Sensor Array for Monitoring of Reactive Die Bond Processes–Design Optimization Using CFD

LTCC With Temperature Sensor Array for Monitoring of Reactive Die Bond Processes–Design Optimization Using CFD

(Invited) Continuous Molecular Monitoring in Interstitial Fluid Via Wearable Microneedle Aptamer-Based Sensors

The ability to continuously monitor the concentration of specific molecules in the body is a long-sought goal of biomedical research. For this purpose, interstitial fluid (ISF) has been proposed as the ideal target biofluid because its composition can rapidly equilibrate with that of systemic blood, allowing the assessment of molecular concentrations that reflect full-body physiology. To tap into this measurement compartment, it is possible to use microneedle sensor arrays for continuous molecular monitoring. In this presentation, I will discuss our efforts to develop microneedle-supported electrochemical, aptamer-based (E-AB) sensors. This platform allows affinity-based monitoring of target concentrations in ISF, and takes advantage of the versatility of aptamers to selectively bind a large variety of molecular targets. I will discuss our current state of platform development, including fabrication challenges, in-vivo deployment in rodent models, and variability of pharmacokineitc profiles as a function of microneedle penetration depth in the skin.

A Sock-Embedded Wireless Sensing System Employing Paper-Substrate-Based MEMS Tactile Sensors Array and Low-Power ASIC for Accurate and Comfortable AFib Monitoring

A Sock-Embedded Wireless Sensing System Employing Paper-Substrate-Based MEMS Tactile Sensors Array and Low-Power ASIC for Accurate and Comfortable AFib Monitoring