Sensors International最新文献

The most recurrent side effect of diabetes is diabetic foot ulcers and if unattended cause imputations. Diabetic feet affect 15% to 25% of diabetic people globally. Diabetes complications are due to less or no awareness of the consequences of diabetes among diabetic patients. Technology leveraging is an attempt to create distinct, affordable, and simple diabetic foot diagnostic strategies for patients and doctors. This work proposes early detection and prognosis of diabetic foot ulcers using the EfficientNet, a deep neural network model. EfficientNet is applied to an image set of 844-foot images, composed of healthy and diabetic ulcer feet. Better performance is obtained compared to earlier models using EfficientNet by carefully balancing network width, depth, and image resolution. The EfficientNet performed better compared to popular models like AlexNet, GoogleNet, VGG16, and VGG19. It gave maximum accuracy, f1-score, recall, and precision of 98.97%, 98%, 98%, and 99%, respectively.

Microwave sensors offer appealing features such as susceptibility, quick response, and non-invasiveness, making them valuable tools for highly accurate measurements of material characterisation. A wide range of techniques, including cavity waveguide, planar transmission line, cavity waveguide perturbation, open-ended coaxial probe, and free-space transmission, have been employed to characterise materials that are essential for their cost-effectiveness, ease of manufacturing, high sensitivity, good quality factor (Q-factor), and compact size, allowing them to be applied to different material types. Among the microwave sensor types, the substrate-integrated waveguide (SIW) has emerged as a promising technology in order to characterise materials in an efficient manner. This paper presents a review of the current state and potential opportunities of SIW microwave sensors in the characterisation of dielectric materials. It provides insights into various design principles, techniques, and applications of SIW microwave sensors across different sectors, highlighting their advantages and limitations compared to conventional waveguide-based sensors. Furthermore, the paper summarises several fabrication methods that can be implemented for SIW microwave sensors to enable the production of efficient and reliable sensors. Additionally, the future directions provided in this paper aim to contribute to the ongoing development and optimisation of SIW-based microwave sensors for accurate and efficient dielectric material characterisation. Overall, this review article serves as a beneficial resource for new researchers seeking to understand the role of SIW microwave sensors in material characterisation. It outlines the current status, opportunities, and potential advancements of SIW sensors, shedding light on their significance and potential impact in the field of material characterisation.

In this research, the conductive polymers including polypyrrole (PPy), polyaniline (PANI), and polythiophene (PTh) and their hybrids in the role of sensors were studied for the detection of the gas molecules. The synthesis principles, sensing performance, sensing mechanism, characterization of the conductive polymers, and scale-up discussion have been investigated. In addition, the impact of the operating conditions including temperature, humidity, gas concentration, time, recovery, and common additives like tin oxide, iron chloride, and Pd were analyzed. Sensitivity, conductivity, and response were discussed as criteria to evaluate the efficiency of the sensors. The difference of conductive polymers in the gas sensing returns to the level of porosity and morphology in the different conductive polymers. The results reveal that PANI and its composites are the desired choice for sensing toxic gases even in industrial centers or commercial scales.

This paper shows how a single parallel plate capacitor can be used to sense volumetric flow rate in micro/nano and smaller scale fluidic conduits and how a double parallel plate capacitor can be used to sense both volumetric flow rate and direction of flow. The concept was developed based on the principles of conservation of energy with some fundamentals of electricity and electromagnetics. Furthermore, the concept was validated experimentally to be accurate. Upon validation the measurement of the sensor was found to be in good agreement with experimental measurement with more accuracy obtained as the supplied voltage for the sensor is increased. Also, the accuracy of the developed concept increases as the characteristic length of the conduit decreases which makes the developed concept even more suitable for smaller scales applications. The concept consumes extremely low power and can be used directly without calibration provided that accurate value for magnetic permittivity of fluid is available. Moreover, the concept can be used for any type of fluid of any conduit shape with easy incorporation onto lab-on-a-chip or MEMS technology. The sensitivity of the sensor is approximately 0.03 A/(m³/s) which is good compared to other sensors.

In this paper, we propose a multi-sensor IoT system-based smart predictive analytics care and movement monitoring model that can be applied to various diapers and solve these problems for the bedridden elderly. A multi-sensor is designed to monitor the condition of the diaper and the movement of the bedridden elderly, in addition, to know the use condition of the diaper and the attitude of the bedridden elderly. In addition, through the changed pattern of the time series data acquired from the multi-sensor, a model that can know not only the presence or absence of urine/feces/farts but also the attitude of bedridden people is constructed and compared to this, it detects urine/feces/farts, care sensing to know the diaper usage status and the bedridden elderly's attitude duration. We propose smart predictive analytics care monitoring model based on multi sensor IoT system: management of diaper and attitude for the bedridden elderly. The design and proposed method are tested and the results are derived through an accredited certification body for an objective evaluation method.

Recent advancements in the field of quantum mechanics have opened the research avenues for the accurate mapping of the heart’s conductivity with the aid of quantum sensors.The heart rate variability can now be accessed to better levels with the aid of recent noninvasive approaches. This novel idea can be improved with the aid of transfer learning where a smart machine learning algorithm, the “improved dynamic time wrapping” can be used, after selecting the important attributes such as the cardiac action potential. During this research, a two step approach is used for the dynamical analysis of the atrial fibrillation cardiac amyloid, since the Atrial-fibrillation (AF) is more common in patients with the “cardiac amyloidosis”, resulting from the deposition of amyloid protein. During the first step, inspired from the experimental studies in the domain of cardiac amyloidosis, an electric heart model is simulated for different amyloid deposition levels, and during the second step, the transfer learning algorithm is applied to explore the time series data of the electric potential and its divergence. This AI- synchronised divergence can be used to cross verify the electric potential divergence, detected by novel quantum sensors, in ongoing and future research projects.

High strain piezoceramics are required for various sensor and actuator applications such as opening and closing of valves in fuel injector systems, for controlled flow of fuel in automobiles, applications for micro-propulsion in satellites, and other engineering applications. The precision control of fuel flow in automobiles is necessary for fuel efficiency and pollution control. In this article, lead free piezo systems having higher strain are reviewed with a focus on origin/mechanisms of high strain behavior with critical comments and future directions. Lead zirconate titanate (PZT) delivers linear but low strain of ∼0.15% of total length due to the piezoelectric effect. However, lead free piezoceramic material systems such as bismuth sodium titanate (BNT), potassium sodium niobate (KNN), barium zirconate titanate (BZT) etc. deliver high but non-linear strains, as high as 0.79% due to electrostriction.

Nanocrystalline titanium oxide nanoparticles (TiO₂ NPs) were synthesized by using a low-cost sonochemical method. TiO₂ NPs exhibited anatase phase and an average crystallite size of 40.64 ​nm, according to a powder X-ray diffraction (PXRD) investigation. SEM and TEM images revealed spherical shape, with asymmetric geometries for TiO₂ NPs. The micrographs thoroughly corroborated the plate-like structure for the NPs. In order to confirm the average energy gap of TiO₂ NPs, diffused reflectance spectroscopy (DRS) via Kubelka-Monk function was applied (3.66 ​eV). Navy blue dye was used to study the photocatalytic properties of NPs and discovered to be triggered at 590.9 ​nm. The photodegradation rate of NB dye decolorized up to 74.04% after 120 ​min of UV light exposure. The first order kinetics was indicated by a linear relationship between log C/Co and k. The demonstrated rates of photodecoloration for NB under UV light in the presence of scavengers AgNO₃, ethanol, and ethylenediamine tetraacetic acid (EDTA), were found to be 65.50%, 61.46%, and 57.33%, respectively. Using the carbon paste electrodes and cyclic voltammetry (CV) in 0.1 ​N HCl solution, the electrochemical characteristics of the obtained sample were studied. The carboxymethyl cellulose sensor made from TiO₂ NPs demonstrated a remarkable sensitivity of 0.08 A. The results showed a high recovery for lead with low% of RSD values. The TiO₂ electrode is a promising electrode material for sensing applications due to its outstanding electrochemical performance.

Applying quantum technology to dispatch face-to-face medical activities has generated significant interest. Unfortunately, the work on remote medical treatment soliciting quantum medication and information processing techniques is hard to observe. In this research, we proposed the Mach–Zehnder interferometer (MZI) based optoplasmonic biosensors (OPBs) with two homodyne detectors for remote-based lung cancer detection using classical and quantum mechanical principles. From the classical basis (Drude-Lorentz model and Kretschmann configuration), the influence of silver nanoparticles (Ag NPs) layers and biomolecule concentration on the performance of biosensors has been investigated. The different types of cancer cells for CL1-5, A549, and HT-29 have been used to analyze the sensitivity, and 319, 332, and 365 (deg/RIU) have been achieved, respectively. In addition, from quantum mechanical principles, the biosignals were conveyed through quantum teleportation in the form of the quantum state of light via fiber optics cable to enable precise remote detection of lung cancer. The obtained sensitivity and teleportation fidelity clearly reveal, the best candidacy of the proposed optoplasmonic biosensor for lung cancer telediagnosis.

A new colorimetric probe aminobenzopyranoxanthene salicylhydrazone (ABPX-Sal) has been synthesized by condensation of salicylaldehyde with aminobenzopyranoxanthene hydrazide (ABPX-hy). Owing to its spirohydrazone structure, this probe showed a significant absorption enhancement at 419 ​nm in the presence of Cu²⁺, and the color changed from colorless to yellow. There was a good linear relationship between the absorption intensity of ABPX-Sal and the amount of Cu²⁺ (R² = ​0.9928), and the detection limit was calculated to be 0.912 ​μM. The binding mode between ABPX-Sal and Cu²⁺ was 1:2, which was proved by ESI-MS. The sensing mechanism was revealed to be a spiro-ring enacted coordination process by DFT calculation. The desired level of selectivity, sensitivity (within 30 ​s), and reusability made this probe very practical in acidic samples.