Recent Progress on Flexible Self-Powered Tactile Sensing Platforms for Health Monitoring and Robotics.

Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self-powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e-skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self-powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self-powered tactile sensing systems are discussed.

Multi-Attribute Triboelectric Materials and Innovative Applications Via TENGs.

Triboelectric nanogenerators (TENGs) as an avant-garde technology that transforms mechanical energy into electrical energy, offering a new direction for green energy and sustainable development. By means of high-efficiency TENGs, conventional materials as new triboelectric materials have exhibited multi-attribute characteristics, achieving innovative applications in the field of micro-nano energy harvesting and self-powered sensing. The progress of TENGs technology with the triboelectric materials is complementary and mutually promoting. On the one hand, one of the cruxes of TENGs lies in the triboelectric materials, which have a decisive impact on their performance. On the other hand, as the research and application of TENGs continue to deepen, higher demands are placed on triboelectric materials, which in turn promotes the advancement of the entire material system as well as the fields of materials science and physics. This work aims to delve into the characteristics, types, preferred choices, and modification treatments of triboelectric materials on the performances of TENGs, hoping to provide guidance and insights for future research and applications.

A Portable Integrated Electrochemical Sensing System for On-Site Nitrite Detection in Food.

Ensuring an appropriate nitrite level in food is essential to keep the body healthy. However, it still remains a huge challenge to offer a portable and low-cost on-site food nitrite analysis without any expensive equipment. Herein, a portable integrated electrochemical sensing system (IESS) is developed to achieve rapid on-site nitrite detection in food, which is composed of a low-cost disposable microfluidic electrochemical patch for few-shot nitrite detection, and a reusable smartphone-assisted electronic device based on self-designed circuit board for signal processing and wireless transmission. The electrochemical patch based on MXene-Ti3C2Tx/multiwalled carbon nanotubes-cyanocobalamin (MXene/MWCNTs-VB12)-modified working electrode achieves high sensitivity of 10.533 µA mm-1 and low nitrite detection limit of 4.22 µm owing to strong electron transfer ability of hybrid MXene/MWCNTs conductive matrix and high nitrite selectivity of VB12 bionic enzyme-based ion-selective layer. Moreover, the portable IESS can rapidly collect pending testing samples through a microfluidic electrochemical patch within 1.0 s to conduct immediate nitrite analysis, and then wirelessly transmit data from a signal-processing electronic device to a smartphone via Bluetooth module. Consequently, this proposed portable IESS demonstrates rapid on-site nitrite analysis and wireless data transmission within one palm-sized electronic device, which would pave a new avenue in food safety and personal bespoke therapy.

In vitro investigation of relationship between quorum-sensing system genes, biofilm forming ability, and drug resistance in clinical isolates of Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas aeruginosa is an opportunistic pathogen in the health-care systems and one of the primary causative agents with high mortality in hospitalized patients, particularly immunocompromised. The limitation of effective antibiotic administration in multidrug-resistant and extensively drug-resistant P. aeruginosa isolates leads to the development of nosocomial infections and health problems. Quorum sensing system contributes to biofilm formation, expression of bacterial virulence factors, and development of drug resistance, causing prolonged patient infections. Therefore, due to the significance of the quorum sensing system in increasing the pathogenicity of P. aeruginosa, the primary objective of our study was to investigate the frequency of quorum sensing genes, as well as the biofilm formation and antibiotic resistance pattern among P. aeruginosa strains. METHODS: A total of 120 P. aeruginosa isolates were collected from different clinical specimens. The disk diffusion method was applied to detect the antibiotic resistance pattern of P. aeruginosa strains. Also, the microtiter plate method was carried out to evaluate the biofilm-forming ability of isolates. Finally, the frequency of rhlI, rhlR, lasI, and lasR genes was examined by the polymerase chain reaction method. RESULTS: In total, 88.3% P. aeruginosa isolates were found to be multidrug-resistant, of which 30.1% had extensively drug-resistant pattern. The highest and lowest resistance rates were found against ceftazidime (75.0%) and ciprofloxacin (46.6%), respectively. Also, 95.8% of isolates were able to produce biofilm, of which 42.5%, 33.3%, and 20.0% had strong, moderate, and weak biofilm patterns, respectively. The frequency of quorum sensing genes among all examined strains was as follows: rhlI (81.6%), rhlR (90.8%), lasI (89.1%), and lasR (78.3%). The most common type of quorum sensing genes among multidrug-resistant isolates were related to rhlR and lasI genes with 94.3%. Furthermore, rhlI, rhlR, and lasI genes were positive for all extensively drug-resistant isolates. However, the lasR gene had the lowest frequency among both multidrug-resistant (83.0%) and extensively drug-resistant (90.6%) isolates. Moreover, rhlR (94.7%) and lasR (81.7%) genes had the highest and lowest prevalence among biofilm-forming isolates, respectively. CONCLUSION: Our findings disclosed the significantly high prevalence of drug resistance among P. aeruginosa isolates. Also, the quorum sensing system had a significant correlation with biofilm formation and drug resistance, indicating the essential role of this system in the emergence of nosocomial infections caused by P. aeruginosa.

Study on molecular epidemiology of carbapenem resistant Pseudomonas aeruginosa and related genes of quorum sensing signal system.

This study aims to investigate the drug resistance, regulation mechanism of quorum sensing system, expression of related virulence genes, and epidemiological characteristics of carbapenem-resistant Pseudomonas aeruginosa (CRPA).In this study, Polymerase chain reaction amplification was performed to evaluate carbapenemase genes, OprD2 gene, quorum sensing system, and related virulence genes. Bacterial genotypes were analyzed using multilocus sequence typing and evolutionary analysis was conducted based on the goeBURST algorithm. The results demonstrated that a total of 47 CRPA strains were collected in this study, primarily from respiratory specimens in the ICU. Drug sensitivity results showed that the resistance rates of the 47 CRPA strains were highest for imipenem (97.87 %). The loss of OprD2 may be the main factor contributing to carbapenem resistance in our hospital's CRPA strains.All isolates tested positive for the quorum sensing system genes lasI and rhlI/R, and the virulence gene lasB was detected in all isolates, while the algD gene was detected in 19.15 % of the isolates. Among the 47 strains, 6 were untypeable, and the 41 strains with 28 different sequence types were clustered into three clonal complexes (BG1, BG2, and BG3).In conclusion, the CRPA isolates from our hospital exhibit high genetic diversity, with the deletion of the OprD2 gene possibly being the primary determinant of carbapenem resistance in Pseudomonas aeruginosa.Moreover, Las and RhI systems play a key role in quorum sensing signal system. Further research and development of drugs targeting quorum sensing signaling system may provide valuable guidance for the treatment of CRPA.

A Study on Sensitivity Improvement of the Fiber Optic Acoustic Sensing System Based on Sagnac Interference.

A new pickup structure was introduced and modified to improve the resolution of the linear Sagnac optical fiber acoustic sensing system. The maximum strains corresponding to the material, diameter, wall thickness, and height of the pickups were analyzed by simulation. An aluminum cylinder with a diameter of 110 mm, a wall thickness of 3 mm, and a height of 120 mm was chosen as the basic pickup. A four-groove pickup with a vertical width of 80 mm and a horizontal width of 20 mm was introduced to improve the sensitivity of the system. The experiments showed that the average peak-to-peak sensitivity of the four-groove pickup increased by 215.54% to 106.806 mV/Pa. The improved pickup can be applied in areas to monitor the situation of invasion of the Sagnac optical fiber acoustic sensing system.

Structural Plastic Damage Warning and Real-Time Sensing System Based on Cointegration Theory.

Structural damage can affect the long-term operation of equipment. Real-time damage warning for structures can effectively avoid accidents caused by structural damage. In this paper, a real-time warning method of structural plastic damage based on the cointegration theory is proposed. This method calculates the cointegration relationship between the strain signals at different measuring points, and the stability of the strain signal relationships is also evaluated. The problem of inaccurate detection caused by the error of strain measurement and environmental influence can be eliminated by the comprehensive judgment of strain between asymmetrical measuring points. A real-time damage sensing system is developed in this paper. In order to improve the real-time and practicability of the system, this paper proposes and determines the residual warning coefficient by analyzing the proportion of the strain residuals exceeding the residual threshold. The research on this sensing system has certain value for the engineering application of damage monitoring methods.

Miniaturizable Chemiluminescence System for ATP Detection in Water.

We present the design, fabrication, and testing of a low-cost, miniaturized detection system that utilizes chemiluminescence to measure the presence of adenosine triphosphate (ATP), the energy unit in biological systems, in water samples. The ATP-luciferin chemiluminescent solution was faced to a silicon photomultiplier (SiPM) for highly sensitive real-time detection. This system can detect ATP concentrations as low as 0.2 nM, with a sensitivity of 79.5 A/M. Additionally, it offers rapid response times and can measure the characteristic time required for reactant diffusion and mixing within the reaction volume, determined to be 0.3 ± 0.1 s. This corresponds to a diffusion velocity of approximately 44 ± 14 mm2/s.

A Low-Cost Sensing Solution for SHM, Exploiting a Dedicated Approach for Signal Recognition.

Health assessment and preventive maintenance of structures are mandatory to predict injuries and to schedule required interventions, especially in seismic areas. Structural health monitoring aims to provide a robust and effective approach to obtaining valuable information on structural conditions of buildings and civil infrastructures, in conjunction with methodologies for the identification and, sometimes, localization of potential risks. In this paper a low-cost solution for structural health monitoring is proposed, exploiting a customized embedded system for the acquisition and storing of measurement signals. Experimental surveys for the assessment of the sensing node have also been performed. The obtained results confirmed the expected performances, especially in terms of resolution in acceleration and tilt measurement, which are 0.55 mg and 0.020°, respectively. Moreover, we used a dedicated algorithm for the classification of recorded signals in the following three classes: noise floor (being mainly related to intrinsic noise of the sensing system), exogenous sources (not correlated to the dynamic behavior of the structure), and structural responses (the response of the structure to external stimuli, such as seismic events, artificially forced and/or environmental solicitations). The latter is of main interest for the investigation of structures' health, while other signals need to be recognized and filtered out. The algorithm, which has been tested against real data, demonstrates relevant features in performing the above-mentioned classification task.

Identification of Beef Odors under Different Storage Day and Processing Temperature Conditions Using an Odor Sensing System.

This study used an odor sensing system with a 16-channel electrochemical sensor array to measure beef odors, aiming to distinguish odors under different storage days and processing temperatures for quality monitoring. Six storage days ranged from purchase (D0) to eight days (D8), with three temperature conditions: no heat (RT), boiling (100 °C), and frying (180 °C). Gas chromatography-mass spectrometry (GC-MS) analysis showed that odorants in the beef varied under different conditions. Compounds like acetoin and 1-hexanol changed significantly with the storage days, while pyrazines and furans were more detectable at higher temperatures. The odor sensing system data were visualized using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP). PCA and unsupervised UMAP clustered beef odors by storage days but struggled with the processing temperatures. Supervised UMAP accurately clustered different temperatures and dates. Machine learning analysis using six classifiers, including support vector machine, achieved 57% accuracy for PCA-reduced data, while unsupervised UMAP reached 49.1% accuracy. Supervised UMAP significantly enhanced the classification accuracy, achieving over 99.5% with the dimensionality reduced to three or above. Results suggest that the odor sensing system can sufficiently enhance non-destructive beef quality and safety monitoring. This research advances electronic nose applications and explores data downscaling techniques, providing valuable insights for future studies.

Enhanced Perception for Autonomous Vehicles at Obstructed Intersections: An Implementation of Vehicle to Infrastructure (V2I) Collaboration.

In urban intersections, the sensory capabilities of autonomous vehicles (AVs) are often hindered by visual obstructions, posing significant challenges to their robust and safe operation. This paper presents an implementation study focused on enhancing the safety and robustness of Connected Automated Vehicles (CAVs) in scenarios with occluded visibility at urban intersections. A novel LiDAR Infrastructure System is established for roadside sensing, combined with Baidu Apollo's Automated Driving System (ADS) and Cohda Wireless V2X communication hardware, and an integrated platform is established for roadside perception enhancement in autonomous driving. The field tests were conducted at the Singapore CETRAN (Centre of Excellence for Testing & Research of Autonomous Vehicles-NTU) autonomous vehicle test track, with the communication protocol adhering to SAE J2735 V2X communication standards. Communication latency and packet delivery ratio were analyzed as the evaluation metrics. The test results showed that the system can help CAV detect obstacles in advance under urban occluded scenarios.

Laser Processing of Crumpled Porous Graphene/MXene Nanocomposites for a Standalone Gas Sensing System.

Integrating wearable gas sensors with energy harvesting and storage devices can create self-powered systems for continuous monitoring of gaseous molecules. However, the development is still limited by complex fabrication processes, poor stretchability, and sensitivity. Herein, we report the low-cost and scalable laser scribing of crumpled graphene/MXenes nanocomposite foams to combine stretchable self-charging power units with gas sensors for a fully integrated standalone gas sensing system. The crumpled nanocomposite designed in island-bridge device architecture allows the integrated self-charging unit to efficiently harvest kinetic energy from body movements into stable power with adjustable voltage/current outputs. Meanwhile, given the stretchable gas sensor with a large response of ∼1% ppm-1 and an ultralow detection limit of ∼5 ppb to NO2/NH3, the integrated system provides real-time monitoring of the exhaled human breath and the local air quality. The innovations in materials and structural designs pave the way for the future development of wearable electronics.

Advancing air quality monitoring: A low-cost sensor network in motion - Part I.

In urban areas, high levels of air pollution pose significant risks to human health, emphasising the need for detailed air quality (AQ) monitoring. However, traditional AQ monitoring relies on the data from Reference Monitoring Stations, which are sparsely distributed and provide only hourly or daily data, failing to capture the spatial and temporal variability of air pollutant concentrations. Addressing this challenge, we introduce in this article the ExpoLIS system, an all-weather mobile AQ monitoring system that integrates various AQ low-cost sensors (LCSs), providing high spatio-temporal resolution data. This study demonstrates that the inclusion of an extended sampling device may mitigate the effect of the meteorological parameters and other disturbances on readings. At the same time, it did not reduce the quality of the data, both in static conditions and in motion, as we were able to maintain a certain level of agreement between the LCSs. In conclusion, the ExpoLIS system proves its versatility by enabling the collection of large quantities of accurate data, allowing a deeper understanding of the AQ dynamics in urban environments.

[Research progress of traditional Chinese medicines as quorum sensing inhibitors in collaboration with antibiotics to inhibit drug-resistant bacteria].

Quorum sensing system regulates the expression of genes related to bacterial growth, metabolism and other behaviors by sensing bacterial density, and controls the unified action of the entire bacterial population. This mechanism can ensure the normal secretion of bacterial metabolites and the stability of the biofilm microenvironment, providing protection for the formation of biofilms and the normal growth and reproduction of bacteria. Traditional Chinese medicine, capable of quorum sensing inhibition, can inhibit the formation of bacterial biofilms, reduce bacterial resistance, and enhance the anti-infection ability of antibiotics when combined with antibiotics. In recent years, the combination of traditional Chinese and Western medicine in the treatment of drug-resistant bacterial infections has become a research hotspot. Starting with the associations between quorum sensing, biofilm and drug-resistant bacteria, this paper reviews the relevant studies about the combined application of traditional Chinese medicines as quorum sensing inhibitors with antibiotics in the treatment of drug-resistant bacteria. This review is expected to provide ideas for the development of new clinical treatment methods and novel anti-infection drugs.

Fast, Selective and Sensitive Fluorescence Detection of Levofloxacin, Fe3+ and Cu2+ Ions in 100% Aqueous Solution Via Their Reciprocal Recognition.

The fluorescence detection of ions and pharmaceutical effluents by using organic chemosensors is a valuable surrogate to the currently existing expensive analytical methods. In this regard, the design of multi-functional chemosensors to recognize desirable guests is of utmost importance. In this study, we first show that levofloxacin (LVO) is able to use as a fluorescent chemosensor for the detection of biologically important Cu2+ (turn-off) and Fe3+ (turn-on) ions via independent signal outputs in 100% aqueous buffer solutions. Next, using the reciprocal recognition of LVO and Fe3+ provides a unique emission pattern for the detection of LVO. This approach exhibited a high specificity to LVO among various pharmaceutical samples, namely acetaminophen (AC), azithromycin (AZ), gemifloxacin (GEM) and ciprofloxacin (CIP) and also showed great anti-interference property in urine. The attractive features of this sensing system are availability, easy-to-use, high sensitivity (limit of detection = 18 nM for Cu2+, 22 nM for Fe3+ and 0.12 nM for LVO), rapid response (5 s) with an excellent selectivity. Levofloxacin (LVO) is able to use as a fluorescent chemosensor for the detection of Cu2+ (turn-off) and Fe3+ (turn-on) ions via independent signal outputs. Moreover, using the reciprocal recognition of LVO and Fe3+ a unique emission pattern for the detection of LVO was achieved which is applicable for biological samples. The attractive features of this sensing system are availability, easy-to-use, high sensitivity, rapid response (5 s) with an excellent selectivity.

Fault Diagnosis of the Autonomous Driving Perception System Based on Information Fusion.

The reliability of autonomous driving sensing systems impacts the overall safety of the driving system. However, perception system fault diagnosis is currently a weak area of research, with limited attention and solutions. In this paper, we present an information-fusion-based fault-diagnosis method for autonomous driving perception systems. To begin, we built an autonomous driving simulation scenario using PreScan software, which collects information from a single millimeter wave (MMW) radar and a single camera sensor. The photos are then identified and labeled via the convolutional neural network (CNN). Then, we fused the sensory inputs from a single MMW radar sensor and a single camera sensor in space and time and mapped the MMW radar points onto the camera image to obtain the region of interest (ROI). Lastly, we developed a method to use information from a single MMW radar to aid in diagnosing defects in a single camera sensor. As the simulation results show, for missing row/column pixel failure, the deviation typically falls between 34.11% and 99.84%, with a response time of 0.02 s to 1.6 s; for pixel shift faults, the deviation range is between 0.32% and 9.92%, with a response time of 0 s to 0.16 s; for target color loss, faults have a deviation range of 0.26% to 2.88% and a response time of 0 s to 0.05 s. These results prove the technology is effective in detecting sensor faults and issuing real-time fault alerts, providing a basis for designing and developing simpler and more user-friendly autonomous driving systems. Furthermore, this method illustrates the principles and methods of information fusion between camera and MMW radar sensors, establishing the foundation for creating more complicated autonomous driving systems.

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification.

This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.

Vision-Based Automated Recognition and 3D Localization Framework for Tower Cranes Using Far-Field Cameras.

Tower cranes can cover most of the area of a construction site, which brings significant safety risks, including potential collisions with other entities. To address these issues, it is necessary to obtain accurate and real-time information on the orientation and location of tower cranes and hooks. As a non-invasive sensing method, computer vision-based (CVB) technology is widely applied on construction sites for object detection and three-dimensional (3D) localization. However, most existing methods mainly address the localization on the construction ground plane or rely on specific viewpoints and positions. To address these issues, this study proposes a framework for the real-time recognition and localization of tower cranes and hooks using monocular far-field cameras. The framework consists of four steps: far-field camera autocalibration using feature matching and horizon-line detection, deep learning-based segmentation of tower cranes, geometric feature reconstruction of tower cranes, and 3D localization estimation. The pose estimation of tower cranes using monocular far-field cameras with arbitrary views is the main contribution of this paper. To evaluate the proposed framework, a series of comprehensive experiments were conducted on construction sites in different scenarios and compared with ground-truth data obtained by sensors. The experimental results show that the proposed framework achieves high precision in both crane jib orientation estimation and hook position estimation, thereby contributing to the development of safety management and productivity analysis.

Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks.

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients' health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

A Feedback Control Sensing System of an Electrorheological Brake to Exert a Constant Pressing Force on an Object.

The paper presents the application of a strain gauge sensor and a viscous brake filled with an electrorheological (ER) fluid, which is a smart material with controlled rheological properties, by an electric field to the fluid domain. For experimental tests, a cylindrical viscous brake was designed. The tests were carried out on a test stand especially prepared for this purpose and suitable for the examination of the impact of the rotational speed of the input shaft and the value of the electric voltage supplied to the viscous brake on pressing forces, taking into account the ER fluid temperature and brake fluid filling level. On the basis of the experimental research results, a viscous brake control system to exert constant pressing forces with feedback from a strain gauge sensor, based on the programmable logic controller, was designed and implemented. This system, using its own control algorithm, ensured a control pressing force within the assumed range, both during the constant and follow-up control. The measurement results obtained during the tests of the viscous brake designed to exert a force were presented in the form of time courses, showing the changes of the pressing force, the electric voltage applied to the brake and the rotational speed of the brake input shaft. The developed ER fluid brake control system with feedback was tested for constant and follow-up control, taking into account the impact of the working fluid temperature. During the test it was possible to obtain a maximum pressing force equal to 50 N for an electric voltage limited to 2.5 kV. The resultant error was lower than 1 N, wherein the adjustment time after changing the desired value of the force was around 1.5 s. The correct operation of both the brake and the control system, as well as the compatibility of the pressing force value and time adjustment, were determined. The main technical contribution described in this article is the design of a new type of DECPF and a new method for its control with the use of a specifically programmed programmable logic controller which simulates the proportional-integral controllers' operation.