The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health *** integration of wearable sensors with intelligent systems is an overwhelming te...
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The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health *** integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health *** many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin *** previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated *** review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable *** begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice *** this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human *** attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine ***,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.
Airborne microorganisms pose a significant health threat, causing various illnesses. Traditional detection methods are often slow and complex. This review highlights the potential of nanomaterial-based biosensors, par...
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Airborne microorganisms pose a significant health threat, causing various illnesses. Traditional detection methods are often slow and complex. This review highlights the potential of nanomaterial-based biosensors, particularly colorimetric sensors, for rapid and on-site detection of airborne microbes. Colorimetric sensors offer real-time visual detection without complex instrumentation. We explore the integration of these sensors with Lab-on-a-Chip technology using PDMS microfluidics. This review also proposes a novel PDMS-based colorimetric biosensor for real-time detection of airborne microbes. The sensor utilizes a color change phenomenon easily observable with the naked eye, simplifying analysis and potentially enabling point-of-care applications.
The integration of real and virtual worlds through the Internet of Things (IoT) is driving the evolution of human lifestyle and production methods. For IoT applications, precise detection of human physical signals by ...
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The integration of real and virtual worlds through the Internet of Things (IoT) is driving the evolution of human lifestyle and production methods. For IoT applications, precise detection of human physical signals by flexible sensors is crucial. Although various polymer-based flexible sensors have been developed, they often struggle to combine high sensitivity with wide-range linear sensing capability. The human epidermis, our largest organ, is remarkably sensitive to a broad spectrum of deformations, from the subtle, like the sensation of an insect crawling, to the intense, such as skin compression. Inspired by this, we construct a compressive piezoresistive polyimide (PI)-based aerogel sensor with an epidermal-inspired mechanoreception network enabled by nerve-like reduced graphene oxide (rGO) networks and MXene-covered-liquid metal (MLM) tactile receptors. The rGO networks and MLM receptors work synergistically, mimicking neural system of epidermis. This intricate structure endows aerogel sensor with a full linear sensing range from 0 % to 80 % compressive strain, along with high sensitivity, characterized by a gauge factor (GF) of 1.23. Moreover, the aerogel shows promising potential as an anti-icing and heat-insulating material. This work advances the concept of creating aerogel sensors that offer a full-range linear response and high sensitivity, opening new possibilities for applications in various fields.
The ability to achieve real-time movement visualization in piezoresistive sensors remains a challenge. A visual piezoresistive sensor to perceive the intensity of mechanical stimuli and visible spatial location inform...
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The ability to achieve real-time movement visualization in piezoresistive sensors remains a challenge. A visual piezoresistive sensor to perceive the intensity of mechanical stimuli and visible spatial location information is designed based on the mechanoluminescence material CaZnOS: Mn. The linearity, detection range, sensitivity, and stability of the sensor are tested, and the sensing mechanism of the sensor is discussed, and the relationship between force, resistance, and light intensity is established. A 5 x 5 sensor array is prepared to realize the visual detection of dynamic force trajectory, and combined with a convolutional neural network and random forest algorithm, the human writing number and pressure characteristics are recognized, and the writing path and handwriting of the robot arm are controlled by multi-feature input. The experimental results show that the machine learning algorithm is very reliable with an accuracy of 98.33% for digit recognition and 97.21% for identity recognition. The visual piezoresistive pressure sensor provides a new idea for the visualization of flexible pressure and promotes the development of flexible sensors towards integration and intelligence.
Objective: Mental fatigue (MF) induced by prolonged cognitive tasks poses significant risks to postural stability, yet its effects on multi-sensory integration remain poorly understood. Method: This study investigated...
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Objective: Mental fatigue (MF) induced by prolonged cognitive tasks poses significant risks to postural stability, yet its effects on multi-sensory integration remain poorly understood. Method: This study investigated how MF alters sensory reweighting and postural control in 27 healthy young males. A 45 min incongruent Stroop task was employed to induce MF, validated via subjective Visual Analog Scale (VAS) scores and psychomotor vigilance tests. Postural stability was assessed under four sensory perturbation conditions (O-H: no interference;C-H: visual occlusion;O-S: proprioceptive perturbation;C-S: combined perturbations) using a Kistler force platform. Center of pressure (COP) signals were analyzed through time-domain metrics, sample entropy (SampEn), and Discrete Wavelet Transform (DWT) to quantify energy distributions across sensory-related frequency bands (visual: 0-0.1 Hz;vestibular: 0.1-0.39 Hz;cerebellar: 0.39-1.56 Hz;proprioceptive: 1.56-6.25 Hz). Results: MF significantly reduced proprioceptive energy contributions (p < 0.05) while increasing vestibular reliance under O-S conditions (p < 0.05). Time-domain metrics showed no significant changes in COP velocity or displacement, but SampEn decreased under closed-eye conditions (p < 0.001), indicating reduced postural adaptability. DWT analysis highlighted MF's interaction with visual occlusion, altering cerebellar and proprioceptive energy dynamics (p < 0.01). Conclusion: These findings demonstrate that MF disrupts proprioceptive integration, prompting compensatory shifts toward vestibular and cerebellar inputs. The integration of nonlinear entropy and frequency-domain analyses advances methodological frameworks for fatigue research, offering insights into real-time sensor-based fatigue monitoring and balance rehabilitation strategies. This study underscores the hierarchical interplay of sensory systems under cognitive load and provides empirical evidence for optimizing interventions in high-risk occupationa
A simple, reusable and sensitive electrochemical sensor based on a gold screen-printed electrode modified with silver nanoparticles has been developed for the detection of nitrate in water. Scanning electron microscop...
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A simple, reusable and sensitive electrochemical sensor based on a gold screen-printed electrode modified with silver nanoparticles has been developed for the detection of nitrate in water. Scanning electron microscopy, square wave voltammetry and electrochemical impedance spectroscopy were used to characterize the modification of the electrode surface. The modified electrode with different silver nanoparticle loadings was also tested, as well as the influence of scan rate on the reduction of nitrate. The sensor exhibited a wide linear response to nitrate from 100 to 1500 mu M and a detection limit of 7.7 mu M, which is significantly less than the maximum contaminant level admitted in drinking water (800 mu M). The reproducibility, repeatability and selectivity of the sensor have also been examined. The suitability of the proposed sensor for real sample detection was successfully demonstrated via recovery studies performed in spiked tap water samples. The proposed approach was used to determine nitrate in freshwater, and the results were in good agreement with those obtained from a commercial nitrate sensor. These advantages make the developed sensor a promising alternative approach for integration into an online monitoring system for water monitoring.
The demand for wearable and flexible strain gauges is gradually increasing owing to their ease of integration with the human body. However, despite technological advancements, these sensors face challenges such as env...
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The demand for wearable and flexible strain gauges is gradually increasing owing to their ease of integration with the human body. However, despite technological advancements, these sensors face challenges such as environmental factors, durability concerns, and calibration difficulties. Hydrogels are semi-solids, contain more water than metals or polymers, and are known for their viscoelasticity, ionic conductivity, and shapeability. One of the drawbacks of hydrogel-based sensors is the reduction in conductivity owing to faster dehydration. Herein, we introduce a material combination of poly (vinyl alcohol) (PVA)/NaCl/carbon nanotube (CNT)/polyethylene glycol (PEG)/glycerol (PNCPG) to synthesize an ionic hydrogel that improves electromechanical properties and reduces the pores present in the hydrogel structure. The ionic hydrogel exhibited self-healing properties, allowing the strain sensor to be reused even after tampering. Furthermore, the relative alteration in resistance demonstrated remarkable consistency and dependability when subjected to cyclic strain conditions for successful real-time human motion detection in addition to smart, wearable, flexible strain sensors. The hydrogel exhibited excellent sensitivity to mechanical deformation;as a result, exceptionally efficient stretchy ionic-hydrogel strain sensors offer substantial opportunities for use in flexible human health motions, soft robotics applications, and wearable electronics.
Mission System integration Rig (MSyIR) setup facilitates the integration, testing, evaluation of Mission payloads of Airborne Surveillance system prior to actual flight test in a controlled environment. In MSyIR, the ...
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ISBN:
(纸本)9798350367393;9798350367386
Mission System integration Rig (MSyIR) setup facilitates the integration, testing, evaluation of Mission payloads of Airborne Surveillance system prior to actual flight test in a controlled environment. In MSyIR, the sensors part of Aircraft surveillance platform can be seamlessly integrated and tested either as actual or simulated. The test setup can use functionally simulated sensor model for all the sensors in the absence of actual sensor. This paper elaborates the framework for a centralized simulation controller that manages multiple airborne sensor simulators in a cohesive manner to perform mission simulation.
This study explores the integration of titanium aluminum nitride (TiAlN) and zirconium aluminum nitride (ZrAlN) thin-film sensors into cutting tools for real-time temperature monitoring during machining of Ti6Al4V tit...
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This study explores the integration of titanium aluminum nitride (TiAlN) and zirconium aluminum nitride (ZrAlN) thin-film sensors into cutting tools for real-time temperature monitoring during machining of Ti6Al4V titanium alloy. These sensors, integrated into a multilayer coating for electrical and wear shielding, were deposited directly onto the tool surfaces and calibrated for temperatures up to 750 degrees C. Due to the integration into the multilayer coating, the sensors exhibit different beta sensitivities across the temperature range, ranging from 108 to 825 K for TiAlN and from 950 to 6681 K for ZrAlN. The cutting tests conducted under various cutting conditions, such as cutting speed, feed rate, depth of cut, and cooling, revealed the influence of these parameters on the cutting temperature. Our findings indicate that the sensor position in the tool's rake face is fundamental for measuring the cutting temperature. The study introduces an innovative tool connector for integration and signal retrieval of the cutting tool in a "plug-and- play" fashion, compatible with industry standards. Additionally, implementing wireless data transmission for real-time and in-situ temperature monitoring offers a pathway for integrating smart cutting tools into modern manufacturing environments, aligning with Industry 4.0.
The field of fluorescence barcode sensor signal processing is the focus, with the development of a high-throughput fluorescence detection visualization platform that integrates multiple efficient fluorescence array lo...
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The field of fluorescence barcode sensor signal processing is the focus, with the development of a high-throughput fluorescence detection visualization platform that integrates multiple efficient fluorescence array localization algorithms, including manual mask positioning, an optimized k-means++ algorithm, and a projection iterative algorithm designed based on fluorescence image projection data. Comprehensive monitoring, real-time adjustment, and integrated data analysis are enabled by the platform, significantly enhancing the accuracy, speed, and convenience of fluorescence image processing. Experimental results demonstrate that the projection iterative algorithm excels in both accuracy and processing speed, achieving a mean squared error (mse) of 6.42130, which is 20.97% lower than that of the k-means++ algorithm, and a processing time of 1095 ms, which is 80.21% and 94.37% faster than the mask positioning and k-means++ algorithms, respectively. Furthermore, evaluation of different fitting algorithms shows that sigmoid curve fitting performs best across various metrics, with an R-2 value as high as 0.987480, indicating excellent data interpretability and fitting accuracy. Overall, precise, rapid, and efficient signal processing in high-throughput fluorescence detection is achieved, providing robust technical support and innovative tools for related research fields.
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