Empirical Analysis of Autonomous Vehicle's LiDAR Detection Performance Degradation for Actual Road Driving in Rain and Fog.

Light detection and ranging (LiDAR) is widely used in autonomous vehicles to obtain precise 3D information about surrounding road environments. However, under bad weather conditions, such as rain, snow, and fog, LiDAR-detection performance is reduced. This effect has hardly been verified in actual road environments. In this study, tests were conducted with different precipitation levels (10, 20, 30, and 40 mm/h) and fog visibilities (50, 100, and 150 m) on actual roads. Square test objects (60 × 60 cm2) made of retroreflective film, aluminum, steel, black sheet, and plastic, commonly used in Korean road traffic signs, were investigated. Number of point clouds (NPC) and intensity (reflection value of points) were selected as LiDAR performance indicators. These indicators decreased with deteriorating weather in order of light rain (10-20 mm/h), weak fog (<150 m), intense rain (30-40 mm/h), and thick fog (≤50 m). Retroreflective film preserved at least 74% of the NPC under clear conditions with intense rain (30-40 mm/h) and thick fog (<50 m). Aluminum and steel showed non-observation for distances of 20-30 m under these conditions. ANOVA and post hoc tests suggested that these performance reductions were statistically significant. Such empirical tests should clarify the LiDAR performance degradation.

New-Type Shearing Interference Detection System Based on Double-Grating Structure for Suppressing the Skylight Background.

To overcome the influence of the daytime skylight background on long-distance optical detection, a new type of shearing interference detection system was proposed to improve the detection performance of the traditional detection system for finding dark objects such as dim stars during the daytime. This article focuses on the basic principle and mathematical model as well as the simulation and experimental research of the new type of shearing interference detection system. The comparison of the detection performance between this new-type detection system and the traditional system is also carried out in this article. The experimental results show that the detection performance of the new type of shearing interference detection system is significantly better than that of the traditional system, and the image signal-to-noise ratio of this new-type system (about 13.2) is much higher than that of the best result of the traditional detection system (about 5.1).

Vigilance Decrement During On-Road Partially Automated Driving Across Four Systems.

OBJECTIVE: This study uses a detection task to measure changes in driver vigilance when operating four different partially automated systems. BACKGROUND: Research show temporal declines in detection task performance during manual and fully automated driving, but the accuracy of using this approach for measuring changes in driver vigilance during on-road partially automated driving is yet unproven. METHOD: Participants drove four different vehicles (Tesla Model 3, Cadillac CT6, Volvo XC90, and Nissan Rogue) equipped with level-2 systems in manual and partially automated modes. Response times to a detection task were recorded over eight consecutive time periods. RESULTS: Bayesian analysis revealed a main effect of time period and an interaction between mode and time period. A main effect of vehicle and a time period x vehicle interaction were also found. CONCLUSION: Results indicated that the reduction in detection task performance over time was worse during partially automated driving. Vehicle-specific analysis also revealed that detection task performance changed across vehicles, with slowest response time found for the Volvo. APPLICATION: The greater decline in detection performance found in automated mode suggests that operating level-2 systems incurred in a greater vigilance decrement, a phenomenon that is of interest for Human Factors practitioners and regulators. We also argue that the observed vehicle-related differences are attributable to the unique design of their in-vehicle interfaces.

Performance comparison of two nucleic acid amplification systems for SARS-CoV-2 detection: A multi-center study.

BACKGROUND: Many rapid nucleic acid testing systems have emerged to halt the development and spread of COVID-19. However, so far relatively few studies have compared the diagnostic performance between these testing systems and conventional detection systems. Here, we performed a retrospective analysis to evaluate the clinical detection performance between SARS-CoV-2 rapid and conventional nucleic acid detection system. METHODS: Clinical detection results of 63,352 oropharyngeal swabs by both systems were finally enrolled in this analysis. Sensitivity (SE), specificity (SP), and positive and negative predictive value (PPV, NPV) of both systems were calculated to evaluate their diagnostic accuracy. Concordance between these two systems were assessed by overall, positive, negative percent agreement (OPA, PPA, NPA) and κ value. Sensitivity of SARS-CoV-2 rapid nucleic acid detection system (Daan Gene) was further analyzed with respect to the viral load of clinical specimens. RESULTS: Sensitivity of Daan Gene was slightly lower than that of conventional detection system (0.86 vs. 0.979), but their specificity was equivalent. Daan Gene had ≥98.0% PPV and NPV for SARS-CoV-2. Moreover, Daan Gene demonstrated an excellent test agreement with conventional detection system (κ = 0.893, p = 0.000). Daan Gene was 99.31% sensitivity for specimens with high viral load (Ct < 35) and 50% for low viral load (Ct ≥ 35). CONCLUSIONS: While showing an analytical sensitivity slightly below than that of conventional detection system, rapid nucleic acid detection system may be a diagnostic alternative to rapidly identify SARS-CoV-2-infected individuals with high viral loads and a powerful complement to current detection methods.

Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies around the MUAC Line.

Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from -30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.

Rapid Detection of Fusarium oxysporum Using Insulated Isothermal PCR and a Rapid, Simple DNA Preparation Protocol.

We developed an insulated isothermal PCR (iiPCR) method for the efficient and rapid detection of Fusarium oxysporum (Fo), which is a fungus that infects various hosts and causes severe crop losses. The Fo iiPCR method was sensitive enough to detect up to 100 copies of standard DNA template and 10 fg of Fo genomic DNA. In addition, it could directly detect 1 pg of mycelium and 10 spores of Fo without DNA extraction. Our study compared the performance of Fo iiPCR to that of three published in planta molecular detection methods-conventional PCR, SYBR green-based real-time PCR, and hydrolysis probe-based real-time PCR-in field detection of Fo. All diseased field samples yielded positive detection results with high reproducibility when subjected to an Fo iiPCR test combined with a rapid DNA extraction protocol compared to Fo iiPCR with an automated magnetic bead-based DNA extraction protocol. Intraday and interday assays were performed to ensure the stability of this new rapid detection method. The results of detection of Fo in diseased banana pseudostem samples demonstrated that this new rapid detection method was suitable for field diagnosis of Fusarium wilt and had high F1 scores for detection (the harmonic mean of precision and recall of detection) for all asymptomatic and symptomatic Fo-infected banana samples. In addition, banana samples at four growth stages (seedling, vegetative, flowering and fruiting, and harvesting) with mild symptoms also showed positive detection results. These results indicate that this new rapid detection method is a potentially efficient procedure for on-site detection of Fo.

Gaze mechanisms enabling the detection of faint stars in the night sky.

For millennia, people have used "averted vision" to improve their detection of faint celestial objects, a technique first documented around 325 BCE. Yet, no studies have assessed gaze location during averted vision to determine what pattern best facilitates perception. Here, we characterized averted vision while recording eye-positions of dark-adapted human participants, for the first time. We simulated stars of apparent magnitudes 3.3 and 3.5, matching their brightness to Megrez (the dimmest star in the Big Dipper) and Tau Ceti. Participants indicated whether each star was visible from a series of fixation locations, providing a comprehensive map of detection performance in all directions. Contrary to prior predictions, maximum detection was first achieved at ~8° from the star, much closer to the fovea than expected from rod-cone distributions alone. These findings challenge the assumption of optimal detection at the rod density peak and provide the first systematic assessment of an age-old facet of human vision.

Nanoporous platinum-copper flowers for non-enzymatic sensitive detection of hydrogen peroxide and glucose at near-neutral pH values.

Multimodal nanoporous PtCu flowers (np-PtCu) were prepared via a two-step dealloying strategy under mild conditions. The np-PtCu alloy possesses an interconnected flower-like network skeleton with multiscale pore distribution. This material was placed on a glassy carbon electrode where it shows outstanding detection performance towards hydrogen peroxide and glucose in near-neutral pH solutions. It can be attributed to the specific structure in terms of interconnected nanoscaled ligaments, rich pore openings and a synergistic alloying effect. Figures of merit for detection H2O2 assay include (a) a working voltage of 0.7 V (vs. the reversible hydrogen electrode); (b) a wide linear response range (from 0.01 to 1.7 mM), and (c) a low detection limit (0.1 µM). The respective data for the glucose assay are (a) 0.4 V, (b) 0.01-2.0 mM, and (c) 0.1 µM. The method is not interfered in the presence of common concentrations of dopamine, acetaminophen and ascorbic acid. Graphical abstract Multimodal nanoporous (np) PtCu alloy was prepared via a two-step dealloying strategy under mild conditions. Np-PtCu exhibits superior electrocatalytic activity. The assay is highly sensitive, selective, and it allows for a long-term detection of H2O2 and glucose.

An Adaptive Multi-Target Radar Waveform Design Based on PWS Algorithm.

Due to the uncertainty of radar target prior information in actual scenes, waveform design based on radar target prior information cannot meet the requirements of detection performance and parameter estimation. Aiming at the problem of waveform design for detecting multi-target in the presence of clutter, a linear probability-weighted summation (PWS) algorithm based on multi-target impulse response is proposed and includes the radar waveform design based on mutual information (MI) and signal-to-interference ratio (SINR) criteria. In view of the traditional water-filling algorithm, the problem of multi-target is further investigated in a new way to improve the overall performance of the system. The method makes a lot of deductions by using Jensen's inequality, to determine the algorithm objective function and energy constraint. The simulation results show that the proposed algorithm has better detection performance and more accurate target information.

When and Why Threats Go Undetected: Impacts of Event Rate and Shift Length on Threat Detection Accuracy During Airport Baggage Screening.

OBJECTIVE: We aimed to assess the impact of task demands and individual characteristics on threat detection in baggage screeners. BACKGROUND: Airport security staff work under time constraints to ensure optimal threat detection. Understanding the impact of individual characteristics and task demands on performance is vital to ensure accurate threat detection. METHOD: We examined threat detection in baggage screeners as a function of event rate (i.e., number of bags per minute) and time on task across 4 months. We measured performance in terms of the accuracy of detection of Fictitious Threat Items (FTIs) randomly superimposed on X-ray images of real passenger bags. RESULTS: Analyses of the percentage of correct FTI identifications (hits) show that longer shifts with high baggage throughput result in worse threat detection. Importantly, these significant performance decrements emerge within the first 10 min of these busy screening shifts only. CONCLUSION: Longer shift lengths, especially when combined with high baggage throughput, increase the likelihood that threats go undetected. APPLICATION: Shorter shift rotations, although perhaps difficult to implement during busy screening periods, would ensure more consistently high vigilance in baggage screeners and, therefore, optimal threat detection and passenger safety.

Performance evaluation of Eu3+-based CRP/SAA and PCT/IL-6 lateral flow immunoassay kits and their diagnostic value in respiratory tract infections.

Objectives: Respiratory infections are among the most common infectious diseases, resulting in significant morbidity and mortality. C-reactive protein (CRP), serum amyloid A (SAA), procalcitonin (PCT), and interleukin-6 (IL-6) are advantageous for diagnosing respiratory tract infections. This study assessed the analytical performance and accuracy of new kits for Eu3+-based CRP/SAA and PCT/IL-6 lateral flow immunoassay and its diagnostic value in respiratory tract infections. Methods: This study evaluated the detection performance of a test kit using guidelines from the Center for Medical Device Evaluation (CMDE) and the Clinical and Laboratory Standards Institute (CLSI). The test results were compared to those of the commercial kits (CRP: Mindray; SAA: Norman; PCT: Shanghai Upper; IL-6: Wantai BioPharm). A total of 156 patients with respiratory tract infections (53 with bacterial infections (Bac group); 50 with viral infections (Vir group); and 53 with co-infections (Bac + Vir group)) were enrolled, along with 50 healthy controls (HC group). Venous blood samples were collected to measure levels of SAA, PCT, CRP, and IL-6 using both the test and commercial kits. The diagnostic value of these biomarkers was assessed using receiver operating characteristic (ROC) curves. Results: Correlation analysis demonstrated a strong concordance between the test kits and commercial kits (CRP: r = 0.9396, P < 0.0001; SAA: r = 0.8986, P < 0.0001; PCT: r = 0.9594, P < 0.0001; IL-6: r = 0.9009, P < 0.0001). The diagnostic performance of the test kits in identifying bacterial, viral, and co-infections was highly consistent with that of the commercial kit. Conclusions: The Eu3+-based CRP/SAA and PCT/IL-6 lateral flow immunoassay test kits demonstrated high levels of consistency with commercial kits in terms of quantitative outcomes and diagnostic performance for respiratory tract infections.

An effective electricity worker identification approach based on Yolov3-Arcface.

To address the issues of low efficiency and high complexity of detection models for electric power workers in distribution rooms, the electric power worker identification approach is proposed. The ArcFace loss function is used as the coordinate regression loss of the target box. According to the score, the template box with the highest score is selected for prediction, which speeds up the rate of convergence. Dimensional clustering is used to set template boxes for bounding box prediction. The experimental results show that the improved YOLOv3 is a high-performance and lightweight model. The electric power worker identification approach proposed in this paper has a high-speed recognition process, accurate recognition results. The effectiveness of the approach is verified with better detection performance and robustness.

Validation of a new kit for preeclampsia screening: A comprehensive analysis.

Objectives: Preeclampsia is a common pregnancy complication that significantly contributes to maternal mortality, perinatal mortality, and preterm delivery. The sFlt-1/PlGF (fms-like tyrosine kinase-1/placental growth factor) ratio has demonstrated robust diagnostic value for preeclampsia. This study assessed the analytical performance and diagnostic accuracy of a novel quantitative determination kit for sFlt-1 and PlGF for the diagnosis of preeclampsia. Methods: The detection performance of the test kit was validated using the Center for Medical Device Evaluation (CMDE) and Clinical and Laboratory Standards Institute (CLSI) documents. The test results were compared to those of the Elecsys immunoassay (Roche Diagnostics). Independent discovery and validation sets were used to analyze the diagnostic efficacy of the preeclampsia kit. The area under the curve (AUC) for preeclampsia at different gestational ages was calculated. Results: Correlation analysis between the test and Roche kits revealed a strong concordance (sFlt-1: r = 0.9966, P < 0.0001; PlGF: r = 0.9935, P < 0.0001). The AUCs for sFlt-1, PlGF, and the sFlt-1/PlGF ratio in diagnosing preeclampsia were 0.749, 0.795, and 0.834, respectively, in the discovery set and 0.729, 0.811, and 0.831, respectively, in the validation set. The corresponding results from the Roche kit were 0.741, 0.795, and 0.829, respectively, and 0.761, 0.864, and 0.844, respectively. Conclusions: Quantitative sFlt-1 and PlGF kits exhibited high levels of consistency with the Roche kits in terms of quantitative outcomes and diagnostic performance for preeclampsia.

Remote sensing image road network detection based on channel attention mechanism.

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high training accuracy but unsatisfactory actual extraction and detection results. The attention mechanism is one of the efficient and practical mechanisms in deep learning. It improves the performance of deep learning by selectively focusing on a portion of all information while ignoring other visible information, while effectively utilizing computing resources. Numerous experiments have also confirmed that the attention mechanism is resource-saving and effective. Its plug and play feature brings great convenience to programmers. In order to provide better road network detection results and solve the above problem, this paper combines the channel attention mechanism with ResNet and proposes SE-ResNet and ECA-ResNet for remote sensing image road network detection, making networks extract and learn road network features and ignore some non-road network features. The experimental results show that on the Massachusetts roads (MR) and CHN6-CUG roads datasets, ECA-ResNet and SE-ResNet based on channel attention mechanism perform similar to LeNet7 and ResNet in terms of accuracy, loss, accuracy convergence, and loss convergence, and even increase a certain computational burden. However, their final road network detection results (including road network detection pixel count, precision, recall, accuracy, IOU, F1 score, and actual road network detection result) of the former are significantly better than those of the latter. The channel attention mechanism makes the deep neural network pay more attention to the extraction and learning of road network features, while ignoring the extraction and learning of some non-road network features, which improves the accuracy of containing road network samples and reduces the accuracy of not containing road network samples. Therefore, the performance of ECA-ResNet and SE-ResNet is similar to that of LeNet7 and ResNet in the accuracy, loss, accuracy convergence and loss convergence, but the final road network detection results of ECA-ResNet and SE-ResNet are significantly better than those of LeNet7 and ResNet. Therefore, the proposed ECA-ResNet and SE-ResNet have broad application prospects in road network detection, especially ECA-ResNet.

A canine model to evaluate the effect of exercise intensity and duration on olfactory detection limits: the running nose.

Detection canines serve critical roles to support the military, homeland security and border protection. Some explosive detection tasks are physically demanding for dogs, and prior research suggests this can lead to a reduction in olfactory detection sensitivity. To further evaluate the effect of exercise intensity on olfactory sensitivity, we developed a novel olfactory paradigm that allowed us to measure olfactory detection thresholds while dogs exercised on a treadmill at two different exercise intensities. Dogs (n = 3) showed a decrement in olfactory detection for 1-bromooctane at 10-3 (v/v) dilutions and lower under greater exercise intensity. Dogs' hit rate for the lowest concentration dropped from 0.87 ± 0.04 when walking at low intensity to below 0.45 ± 0.06 when trotting at moderate intensity. This decline had an interaction with the duration of the session in moderate intensity exercise, whereby dogs performed near 100% detection in the first 10 min of the 8 km/h session, but showed 0% detection after 20 min. Hit rates for high odor concentrations (10-2) were relatively stable at both low (1 ± 0.00) and moderate (0.91 ± 0.04) exercise intensities. The paradigm and apparatus developed here may be useful to help further understand causes of operationally relevant olfactory detection threshold decline in dogs.

Advantages of aggregation-induced luminescence microspheres compared with fluorescent microspheres in immunochromatography assay with sandwich format.

Organic fluorescein dye-embedded fluorescent microspheres (FMs) are currently the most established commercially fluorescent markers, and they have been widely used to improve the sensitivity of immunochromatography assay (ICA). However, these FMs have natural defects, such as the aggregation-caused quenching effect and small Stokes shift, which are not conducive to improving the detection performance of ICA. Herein, two green emitted FMs, namely aggregation-induced emission FMs (AIEFMs) and fluorescein isothiocyanate FMs (FITCFMs), were prepared by swelling the AIE luminogens and FITC dyes into the carboxyl group-modified polystyrene microspheres. The average diameters of AIEFMs and FITCFMs were 350 and 450 nm, respectively. Compared with FITCFMs, the AIEFMs exhibited stronger fluorescence intensity and a larger Stokes shift. These two FMs were used as the labeling markers of ICA for procalcitonin (PCT) detection with the sandwich format. Among them, AIEFM-ICA showed dynamic linear detection of PCT from 7.6 pg mL-1 to 125 ng mL-1 with the limit of detection (LOD) at 3.8 pg mL-1. These values were remarkably superior to those of FITCFM-ICA (linear range from 61 pg mL-1 to 62.5 ng mL-1 and LOD value at 60 pg mL-1). Furthermore, the average recoveries of the intra- and inter-assays of AIEFM-ICA ranged from 86% to 112%, with coefficients of variation ranging from 1.2% to 8.8%, indicating accuracy and precision for PCT quantitative detection. Additionally, the reliability of the developed AIEFM-ICA was further assessed by analyzing 30 real serum samples from systemic inflammatory response by infectious diseases, and the results showed good agreement with the chemiluminescence immunoassay. In conclusion, compared with traditional FITCFMs, green emitted AIEFMs as a novel fluorescent label, exhibits greater potential to enhance the detection performance of the ICA platform.

Increasing pupil size is associated with improved detection performance in the periphery.

Visible light enters our body via the pupil. By changing its size, the pupil shapes visual input. Small apertures increase the resolution of high spatial frequencies, thus allowing discrimination of fine details. Large apertures, in contrast, provide a better signal-to-noise ratio, because more light can enter the eye. This should lead to better detection performance of peripheral stimuli. Experiment 1 shows that the effect can reliably be demonstrated even in a less controlled online setting. In Experiment 2, pupil size was measured in a laboratory using an eye tracker. The findings replicate findings showing that large pupils provide an advantage for peripheral detection of faint stimuli. Moreover, not only pupil size during information intake in the current trial n, but also its interaction with pupil size preceding information intake, i.e., in trial n-1, predicted performance. This suggests that in addition to absolute pupil size, the extent of pupillary change provides a mechanism to modulate perceptual functions. The results are discussed in terms of low-level sensory as well as higher-level arousal-driven changes in stimulus processing.

Recent advances in inorganic functional nanomaterials based flexible electrochemical sensors.

The flexible electrochemical sensor is a key component of the health monitoring system which can continuously track the physiological signals of the human body, while there is no obvious discomfort and invasiveness. Therefore, it has great potential in personalized medical testing. However, the development of flexible electrochemical sensors currently faces many difficulties, such as the limitations of conductive material properties and manufacturing methods, and the disadvantages of commonly used flexible substrates that are not resistant to high temperatures. In this work, inorganic nanomaterials commonly used to make flexible electrochemical sensors were classified to zero-dimensional (0D) nanomaterials, one-dimensional (1D) nanomaterials, two-dimensional (2D) nanomaterials, and hybrid nanomaterials according to their morphology. The fabrication method of the nanomaterials-based flexible electrochemical sensors was also introduced. Furthermore, the application of flexible electrochemical sensors for chemical and biological sensing and their detection performance were summarized. The detection targets were classified to ion, small molecule, biomacromolecule, and bacteria, respectively.

Distributed Small-Step Path Planning and Detection Method for Post-earthquake Robot to Inspect and Evaluate Building Damage.

Post-earthquake robots can be used extensively to inspect and evaluate building damage for safety assessment. However, the surrounding environment and path for such robots are complex and unstable with unexpected obstacles. Thus, path planning for such robot is crucial to guarantee satisfactory inspection and evaluation while approaching the ideal position. To achieve this goal, we proposed a distributed small-step path planning method using modified reinforcement learning (MRL). Limited distance and 12 directions were gridly refined for the robot to move around. The small moving step ensures the path planning to be optimal in a neighboring safe region. The MRL updates the direction and adjusts the path to avoid unknown disturbances. After finding the best inspection angle, the camera on the robot can capture the picture clearly, thereby improving the detection capability. Furthermore, the corner point detection method of buildings was improved using the Harris algorithm to enhance the detection accuracy. An experimental simulation platform was established to verify the designed robot, path planning method, and overall detection performance. Based on the proposed evaluation index, the post-earthquake building damage was inspected with high accuracy of up to 98%, i.e., 20% higher than traditional unplanned detection. The proposed robot can be used to explore unknown environments, especially in hazardous conditions unsuitable for humans.

Development of Microfluidic Chip-Based Loop-Mediated Isothermal Amplification (LAMP) Method for Detection of Carbapenemase Producing Bacteria.

The rapid and accurate diagnostic methods to identify carbapenemase-producing organisms (CPO) is of great importance for controlling the CPO infection. Herein, we have developed a microfluidic chip-based technique to detect CPO and assessed its clinical value in detecting CPO directly from blood cultures (BCs). The detection performance of the microfluidic chip-based LAMP amplification method was analyzed retrospectively on a collection of 192 isolates including molecularly characterized 108 CPO and 84 non-CPO and prospectively on a collection of 133 positive BCs with or without CPO suspicion, respectively. In the retrospective study, the microfluidic chip-based LAMP amplification method exhibited 87.5% accuracy (95% CI [82.0-91.5]), 97.7% sensitivity (95% CI [91.2-99.6]), 78.8% specificity (95% CI [69.5-86.0]), 79.6% positive predictive value (PPV) (95% CI [70.6-86.5]) and 97.6% negative predictive value (NPV) (95% CI [90.9-99.6]). Among the 192 isolates, 22 (11.5%) false-positives (FP) and 2 (1.0%) false negatives (FN) were observed. In the prospective study, the 133 routine isolates of positive BCs including 18 meropenem-resistant CPO and 115 non-CPO were assessed, and 4 FP were observed in non-CPO and CPO, respectively. The current method showed a total detection performance of 94.0% accuracy (95% CI [88.4-97.1]), 100.0% sensitivity (95% CI [73.2-100.0]), 93.2% specificity (95% CI [86.7-96.8]), 63.6% PPV (95% CI [40.8-82.0]) and 100.0% NPV (95% CI [95.8-100.0]). In summary, the microfluidic chip-based LAMP amplification method is reliable for the rapid screening and detection of CPO with high accuracy, sensitivity, and specificity, and could easily be implemented in clinical microbiology laboratories. IMPORTANCE Rapid and accurate identification of CPO may reduce the genetic exchanges among bacteria and prevent further dissemination of carbapenemases to non-CPO. The current method had designed microfluidic chip-based LAMP amplification method for multiplex detection of carbapenemase genes and evaluated the detection performance of the newly method. The current method can rapidly screen and detect CPO with high accuracy, sensitivity, and specificity, and could easily be implemented in clinical microbiology laboratories, as this will reduce the carbapenem resistance issues worldwide.