Investigation of Interferences of Wearable Sensors with Plant Growth.

Plant wearable sensors have shown exceptional promise in continuously monitoring plant health. However, the potential adverse effects of these sensors on plant growth remain unclear. This study systematically quantifies wearable sensors' interference with plant growth using two ornamental species, Peperomia tetraphylla and Epipremnum aureum. We evaluated the impacts of four common disturbances-mechanical pressure, hindrance of gas exchange, hindrance of light acquisition, and mechanical constraint-on leaf growth. Our results indicated that the combination of light hindrance and mechanical constraint demonstrated the most significant interference. When the sensor weight was no greater than 0.6 g and the coverage was no greater than 5% of the leaf area, these four disturbances resulted in slight impacts on leaf growth. Additionally, we fabricated a minimally interfering wearable sensor capable of measuring the air temperature of the microclimate of the plant while maintaining plant growth. This research provides valuable insights into optimizing plant wearable sensors, balancing functionality with minimal plant interference.

Recent advances in ratiometric electrochemical sensors for food analysis.

Ratiometric electrochemical sensors are renowned for their dual-signal processing capabilities, enabling automatic correction of background noise and interferences through built-in calibration, thus providing more accurate and reproducible measurements. This characteristic makes them highly promising for food analysis. This review comprehensively summarizes and discusses the latest advancements in ratiometric electrochemical sensors and their applications in food analysis, emphasizing their design strategies, detection capabilities, and practical uses. Initially, we explore the construction and design strategies of these sensors. We then review the detection of various food-related analytes, including nutrients, additives, metal ions, pharmaceutical and pesticide residues, biotoxins, and pathogens. The review also briefly explores the challenges faced by ratiometric electrochemical sensors in food testing and potential future directions for development. It aims to provide researchers with a clear introduction and serve as a reference for the design and application of new, efficient ratiometric electrochemical sensors in food analysis.

Laser-Induced Electrochemical Biosensor Modified with Graphene-Based Ink for Label-Free Detection of Alpha-Fetoprotein and 17ß-Estradiol.

In this research, a novel electrochemical biosensor is proposed based on inducing graphene formation on polyimide substrate via laser engraving. Graphene polyaniline (G-PANI) conductive ink was synthesized by planetary mixing and applied to the working zone of the developed sensor to effectively enhance the electrical signals. The laser-induced graphene (LIG) sensor was used to detect alpha-fetoprotein (AFP) and 17ß-Estradiol (E2) in the phosphate buffer saline (PBS) buffer and human serum. The electrochemical performance of the biosensor in determining these biomarkers was investigated by differential pulse voltammetry (DPV) and chronoamperometry (CA). In a buffer environment, alpha-fetoprotein (AFP) and 17ß-Estradiol detection range were 4-400 ng/mL and 20-400 pg/mL respectively. The experimental results showed a limit of detection (LOD) of 1.15 ng/mL and 0.96 pg/mL for AFP and estrogen, respectively, with an excellent linear range (R2 = 0.98 and 0.99). In addition, the designed sensor was able to detect these two types of biomarkers in human serum successfully. The proposed sensor exhibited excellent reproducibility, repeatability, and good stability (relative standard deviation, RSD = 0.96%, 1.12%, 2.92%, respectively). The electrochemical biosensor proposed herein is easy to prepare and can be successfully used for low-cost, rapid detection of AFP and E2. This approach provides a promising platform for clinical detection and is advantageous to healthcare applications.

Improving urinary incontinence management and sleep quality with wetness sensing technology in absorbent products.

Using absorbent products to manage the urinary incontinence (UI) of dependent residents in care facilities (such as nursing homes, and hospitals) requires frequent routine checks throughout the day and night to see if products need changing. Timely changes of saturated products are necessary to avoid long-lasting skin exposure to wet absorbent products, unpleasant odor, leaking of such products and embarrassing moments for the users. Limited staffing, high workload, and peaks on the demand for caregiving are challenges that hamper swift support for the care dependent population. This paper describes novel sensing technology that has been developed for monitoring the wet state of absorbent products remotely. The Orizon system by Ontex enables caregivers to prioritize care routines, avoid sleep disturbance at night and achieve effective leakage prevention. Moreover, the monitoring data can be used to understand the individual product usage and incontinence pattern of individuals, helping incontinence specialists to choose the optimal product and implement appropriate toilet training for each user.

A Tension Sensor Array for Cable-Driven Surgical Robots.

Tendon-sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.

Strategy, Design, and Fabrication of Electrochemical Biosensors: A Tutorial.

Advanced healthcare requires novel technologies capable of real-time sensing to monitor acute and long-term health. The challenge relies on converting a real-time quantitative biological and chemical signal into a desired measurable output. Given the success in detecting glucose and the commercialization of glucometers, electrochemical biosensors continue to be a mainstay of academic and industrial research activities. Despite the wealth of literature on electrochemical biosensors, reports are often specific to a particular application (e.g., pathogens, cancer markers, glucose, etc.), and most fail to convey the underlying strategy and design, and if it is transferable to detection of a different analyte. Here we present a tutorial review for those entering this research area that summarizes the basic electrochemical techniques utilized as well as discusses the designs and optimization strategies employed to improve sensitivity and maximize signal output.

Eddy Current Position Measurement in Harsh Environments: A Temperature Compensation and Calibration Approach.

Eddy current displacement sensors (ECDSs) are widely used for the noncontact position measurement of small displacements (lift-offs). Challenges arise with larger displacements as the sensitivity of the ECDSs decreases. This leads to a more pronounced impact of temperature variations on the inductance and, consequently, an increased position error. Design solutions often rely on multiple coils, suitable coil carrier materials, and compensation measures to address the challenges. This study presents a single-coil ECDS for large displacement ranges in environments with high temperatures and temperature variations. The analysis is based on a sensor model derived from an equivalent circuit model (ECM). We propose design measures for both the sensing coil and the target, focusing on material selection to handle the impact of temperature variations. A key part of improving performance under varying temperatures includes model-based temperature compensation for the inductance of the sensing coil. We introduce a method to calibrate the sensor for large displacements, using a modified coupling coefficient based on field simulation data. Our analysis shows that this single-coil ECDS design maintains a position error of less than 0.2% full-scale for a temperature variation of 100 K for the sensing coil and 110 K for the target.

The Use of Xenonucleic Acids Significantly Reduces the In Vivo Drift of Electrochemical Aptamer-Based Sensors.

Electrochemical aptamer-based sensors support the high-frequency, real-time monitoring of molecules-of-interest in vivo. Achieving this requires methods for correcting the sensor drift seen during in vivo placements. While this correction ensures EAB sensor measurements remain accurate, as drift progresses it reduces the signal-to-noise ratio and precision. Here, we show that enzymatic cleavage of the sensor's target-recognizing DNA aptamer is a major source of this signal loss. To demonstrate this, we deployed a tobramycin-detecting EAB sensor analog fabricated with the DNase-resistant "xenonucleic acid" 2'O-methyl-RNA in a live rat. In contrast to the sensor employing the equivalent DNA aptamer, the 2'O-methyl-RNA aptamer sensor lost very little signal and had improved signal-to-noise. We further characterized the EAB sensor drift using unstructured DNA or 2'O-methyl-RNA oligonucleotides. While the two devices drift similarly in vitro in whole blood, the in vivo drift of the 2'O-methyl-RNA-employing device is less compared to the DNA-employing device. Studies of the electron transfer kinetics suggested that the greater drift of the latter sensor arises due to enzymatic DNA degradation. These findings, coupled with advances in the selection of aptamers employing XNA, suggest a means of improving EAB sensor stability when they are used to perform molecular monitoring in the living body.

Electrostatic Acoustic Sensor with an Impedance-Matched Diaphragm Characterized for Body Sound Monitoring.

Acoustic sensors are able to capture more incident energy if their acoustic impedance closely matches the acoustic impedance of the medium being probed, such as skin or wood. Controlling the acoustic impedance of polymers can be achieved by selecting materials with appropriate densities and stiffnesses as well as adding ceramic nanoparticles. This study follows a statistical methodology to examine the impact of polymer type and nanoparticle addition on the fabrication of acoustic sensors with desired acoustic impedances in the range of 1-2.2 MRayls. The proposed method using a design of experiments approach measures sensors with diaphragms of varying impedances when excited with acoustic vibrations traveling through wood, gelatin, and plastic. The sensor diaphragm is subsequently optimized for body sound monitoring, and the sensor's improved body sound coherence and airborne noise rejection are evaluated on an acoustic phantom in simulated noise environments and compared to electronic stethoscopes with onboard noise cancellation. The impedance-matched sensor demonstrates high sensitivity to body sounds, low sensitivity to airborne sound, a frequency response comparable to two state-of-the-art electronic stethoscopes, and the ability to capture lung and heart sounds from a real subject. Due to its small size, use of flexible materials, and rejection of airborne noise, the sensor provides an improved solution for wearable body sound monitoring, as well as sensing from other mediums with acoustic impedances in the range of 1-2.2 MRayls, such as water and wood.

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth.

We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.

Evaluating the Potential of an Oral-Based Bioguard to Estimate Heart Rate Using Photoplethysmography.

The reliable monitoring of heart rate during intense exercise is imperative to effectively manage training loads while providing insights from a healthcare perspective. However, current technologies perform poorly in contact sports settings. This study aims to evaluate the best approach for heart rate tracking using photoplethysmography sensors embedded into an instrumented mouthguard (iMG). Seven adults wore iMGs and a reference heart rate monitor. Several sensor placements, light sources and signal intensities were explored for the iMG. A novel metric related to the positioning of the sensor in the gum was introduced. The error between the iMG heart rate and the reference data was assessed to obtain insights into the effect of specific iMG configurations on measurement errors. Signal intensity was found to be the most important variable for error prediction, followed by the sensor light source, sensor placement and positioning. A generalized linear model combining an infrared light source, at an intensity of 5.08 mA, and a frontal placement high in the gum area resulted in a heart rate minimum error of 16.33%. This research shows promising preliminary results for the use of oral-based heart rate monitoring, but highlights the need for the careful consideration of sensor configurations within these systems.

Nitrogen-doped carbon dots: Recent developments in its fluorescent sensor applications.

Doped carbon dots have attracted great attention from researchers across disciplines because of their unique characteristics, such as their low toxicity, physiochemical stability, photostability, and outstanding biocompatibility. Nitrogen is one of the most commonly used elements for doping because of its sizeable atomic radius, strong electronegativity, abundance, and availability of electrons. This distinguishes them from other atoms and allows them to perform distinctive roles in various applications. Here, we have reviewed the most current breakthroughs in nitrogen-doped CDs (N-CDs) for fluorescent sensor applications in the last five years. The first section of the article addresses several synthetic and sustainable ways of making N-CDs. Next, we briefly reviewed the fluorescent features of N-CDs and their sensing mechanism. Furthermore, we have thoroughly reviewed their fluorescent sensor applications as sensors for cations, anions, small molecules, enzymes, antibiotics, pathogens, explosives, and pesticides. Finally, we have discussed the N-CDs' potential future as primary research and how that may be used. We hope that this study will contribute to a better understanding of the principles of N-CDs and the sensory applications that they can serve.

Development of a Novel Spherical Light-Based Positioning Sensor in Solar Tracking.

Tracking of the sun, which increases the efficiency of solar energy production systems, has shown considerable development in recent years. This development has been achieved by custom-positioned light sensors, image cameras, sensorless chronological systems and intelligent controller supported systems or by synergetic use of these systems. This study contributes to this research area with a novel spherical-based sensor which measures spherical light source emittance and localizes the light source. This sensor was built by using miniature light sensors placed on a spherical shaped three-dimensional printed body with data acquisition electronic circuitry. Besides the developed sensor data acquisition embedded software, preprocessing and filtering processes were conducted on these measured data. In the study, the outputs of Moving Average, Savitzky-Golay, and Median filters were used for the localization of the light source. The center of gravity for each filter used was determined as a point, and the location of the light source was determined. The spherical sensor system obtained by this study is applicable for various solar tracking methods. The approach of the study also shows that this measurement system is applicable for obtaining the position of local light sources such as the ones placed on mobile or cooperative robots.

Soft Sensor Design via Switching Observers.

The goal of the paper is the design of soft sensors for single input single output (SISO) nonlinear processes. This goal is of essential importance for process monitoring, fault detection and fault isolation. The observer-based technique, being a fruitful direction in soft sensor design, is followed to develop soft sensors for nonlinear processes with known dynamics and unknown physical parameters. A new and general approach, based on the identified I/O linear approximant system descriptions, around prespecified operating points, and a bank of switching linear observers, will be developed. The system property of the I/O reconstructability of the state space linear approximant of a nonlinear model is presented. The design of each observer is based on the I/O measurements and structural characteristics of the nonlinear process. Observer-oriented target areas are introduced, and the respective dense web principle is formulated. The design is completed by the design of a data-driven rule-based system, providing stepwise switching among the observers of the bank. The number of observers of the bank is equal to the number of the linear approximants of the nonlinear process model and is equal to the number of the respective target operating areas. The target operating areas are required to satisfy the dense web principle. The information provided by the soft sensor is the estimation of the non-measured variables of the process. The information used by the soft sensor is the identified I/O approximants of the process as well as the real time values of the measurement variables. The efficiency of the design scheme is illustrated through symbolic and numerical simulation results for a chemostat. The nonlinear model of the chemostat is initially approximated by a set of ten linear approximants. After, the I/O approximants are identified, the respective observers are designed and the target operating areas are determined, where several cases of the satisfaction of the dense web principle are investigated. The soft sensor is composed in terms of the designed observers. Simulation results illustrate the satisfactory performance of the designed soft sensor.

Research on Rapid and Low-Cost Spectral Device for the Estimation of the Quality Attributes of Tea Tree Leaves.

Tea polyphenols, amino acids, soluble sugars, and other ingredients in fresh tea leaves are the key parameters of tea quality. In this research, a tea leaf ingredient estimation sensor was developed based on a multi-channel spectral sensor. The experiment showed that the device could effectively acquire 700-1000 nm spectral data of tea tree leaves and could display the ingredients of leaf samples in real time through the visual interactive interface. The spectral data of Fuding white tea tree leaves acquired by the detection device were used to build an ingredient content prediction model based on the ridge regression model and random forest algorithm. As a result, the prediction model based on the random forest algorithm with better prediction performance was loaded into the ingredient detection device. Verification experiment showed that the root mean square error (RMSE) and determination coefficient (R2) in the prediction were, respectively, as follows: moisture content (1.61 and 0.35), free amino acid content (0.16 and 0.79), tea polyphenol content (1.35 and 0.28), sugar content (0.14 and 0.33), nitrogen content (1.15 and 0.91), and chlorophyll content (0.02 and 0.97). As a result, the device can predict some parameters with high accuracy (nitrogen, chlorophyll, free amino acid) but some of them with lower accuracy (moisture, polyphenol, sugar) based on the R2 values. The tea leaf ingredient estimation sensor could realize rapid non-destructive detection of key ingredients affecting tea quality, which is conducive to real-time monitoring of the current quality of tea leaves, evaluating the status during tea tree growth, and improving the quality of tea production. The application of this research will be helpful for the automatic management of tea plantations.

Four-Stage Multi-Physics Simulations to Assist Temperature Sensor Design for Industrial-Scale Coal-Fired Boiler.

The growth of renewable energy sources presents a pressing challenge to the operation and maintenance of existing fossil fuel power plants, given that fossil fuel remains the predominant fuel source, responsible for over 60% of electricity generation in the United States. One of the main concerns within these fossil fuel power plants is the unpredictable failure of boiler tubes, resulting in emergency maintenance with significant economic and societal consequences. A reliable high-temperature sensor is necessary for in situ monitoring of boiler tubes and the safety of fossil fuel power plants. In this study, a comprehensive four-stage multi-physics computational framework is developed to assist the design, optimization installation, and operation of the high-temperature stainless-steel and quartz coaxial cable sensor (SSQ-CCS) for coal-fired boiler applications. With the consideration of various operation conditions, we predict the distributions of flue gas temperatures within coal-fired boilers, the temperature correlation between the boiler tube and SSQ-CCS, and the safety of SSQ-CCS. With the simulation-guided sensor installation plan, the newly designed SSQ-CCSs have been employed for field testing for more than 430 days. The computational framework developed in this work can guide the future operation of coal-fired plants and other power plants for the safety prediction of boiler operations.

Design of electrical impedance spectroscopy sensing surgical drill using computational modelling and experimental validation.

Electrical Impedance Spectroscopy (EIS) sensing surgical instruments could provide valuable and real-time feedback to surgeons about hidden tissue boundaries, therefore reducing the risk of iatrogenic injuries. In this paper, we present an EIS sensing surgical drill as an example instrument and introduce a strategy to optimize the mono-polar electrode geometry using a finite element method (FEM)-based computational model and experimental validation. An empirical contact impedance model and an adaptive mesh refinement protocol were developed to accurately preserve the behaviour of sensing electrodes as they approach high impedance boundaries. Specifically, experiments with drill-bit, cylinder, and conical geometries suggested a 15%-35% increase in resistance as the sensing electrode approached a high impedance boundary. Simulations achieved a maximum mean experiment-to-simulation mismatch of +1.7% for the drill-bit and +/-11% range for other electrode geometries. The simulations preserved the increase in resistance behaviour near the high impedance boundary. This highly accurate simulation framework allows us a mechanism for optimizing sensor geometry without costly experimental evaluation.

Case-Specific Focal Sensor Design for Cardiac Electrical Impedance Tomography.

Electrical impedance tomography (EIT) is a non-invasive detection technology that uses the electrical response value at the boundary of an observation field to image the conductivity changes in an area. When EIT is applied to the thoracic cavity of the human body, the conductivity change caused by the heartbeat will be concentrated in a sub-region of the thoracic cavity, that is, the heart region. In order to improve the spatial resolution of the target region, two sensor optimization methods based on conformal mapping theory were proposed in this study. The effectiveness of the proposed method was verified by simulation and phantom experiment. The qualitative analysis and quantitative index evaluation of the reconstructed image showed that the optimized model could achieve higher imaging accuracy of the heart region compared with the standard sensor. The reconstruction results could effectively reflect the periodic diastolic and systolic movements of the heart and had a better ability to recognize the position of the heart in the thoracic cavity.

A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement.

Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.

Optimal Design of Complementary Experiments for Parameter Estimation at Elevated Temperature of Food Processing.

Simultaneous estimation of thermal properties can be challenging, especially when the parameters are temperature-dependent. Previous research has shown that by using a complementary experiment, temperature-dependent thermal conductivity can be estimated using a single experiment. The objective of this study was to optimize the complementary experiments that can facilitate the simultaneous estimation of temperature-dependent thermal conductivity and volumetric heat capacity. A theoretical study was conducted with two experiments in a single trial with the sample being kept in a cylindrical sample holder, which had a thin film heater in the center. The first part of the experiment was conducted by keeping the external surface temperature at 50 °C for 300 s and allowing the center temperature to equilibrate with the boundary temperature. Then, the second part of the experiment followed, where the thin film heater was supplied with electrical power to increase the center temperate to 140 °C. Several heating profiles were studied to maximize the information obtained from the complementary experiments, and the best one was the power profile with a sinusoidal function. All four parameters of sweet potato puree temperature-dependent thermal conductivity (0.509 to 0.629 W/mK at 25 °C and 140 °C, respectively) and volumetric heat capacity (3.617 × 106 to 4.180 × 106 J/m3K at 25 °C and 140 °C, respectively) were estimated with low standard errors.