Duplicate Tests Research Articles

MMMNA-Net for Overall Survival Time Prediction of Brain Tumor Patients.

Overall survival (OS) time is one of the most important evaluation indices for gliomas situations. Multi-modal Magnetic Resonance Imaging (MRI) scans play an important role in the study of glioma prognosis OS time. Several deep learning-based methods are proposed for the OS time prediction on multi-modal MRI problems. However, these methods usually fuse multi-modal information at the beginning or at the end of the deep learning networks and lack the fusion of features from different scales. In addition, the fusion at the end of networks always adapts global with global (eg. fully connected after concatenation of global average pooling output) or local with local (eg. bilinear pooling), which loses the information of local with global. In this paper, we propose a novel method for multi-modal OS time prediction of brain tumor patients, which contains an improved non-local features fusion module introduced on different scales. Our method obtains a relative 8.76% improvement over the current state-of-art method (0.6989 vs. 0.6426 on accuracy). An extra testing demonstrates that our method could adapt to the situations with missing modalities. The code is available at https://github.com/TangWen920812/mmmna-net.

Comparison of modified mallampati classification with Cormack and Lehane grading in predicting difficult laryngoscopy among elective surgical patients who took general anesthesia in Werabie comprehensive specialized hospital - Cross sectional study. Ethiopia, 2021

BackgroundDifficult laryngoscopy/intubation can cause a multitude of issues, including hypoxia, brain damage, and even death if not addressed swiftly. The Modified Mallampati test (MMT) is frequently used to predict difficult airway in patients with no clear difficult airway signal, despite its limited predictive power, in patients with no obvious difficult airway signal. Cormack and Lehane grading (CLG) is the gold standard, however it is not utilized before anesthesia. ObjectiveTo compare modified Mallampati classification (MMC) with Cormack and Lehane grading in predicting difficult laryngoscopy among patients who took general anesthesia. MethodAn institutionally based cross sectional survey study of 141 elective surgical patients with no obvious difficult airway sign was conducted from February to April 2021. The correlation between MMC and CLG was computed using spearman's correlation coefficient, and the area under the curve (AUC) for MMT was assessed using receiver operating characteristics (ROC) curve analysis. ResultThe incidence of difficult laryngoscopy and intubation, respectively, was 14.9% and 9.2%. The Spearman correlation coefficient (ρ) was 0.330, with a significance level of 0.001. The AUCs for difficult laryngoscopy and intubation, respectively, were 0.705 and 0.726. MMT had 47.6% sensitivity and 93.3% specificity for difficult laryngoscopy and 53.8% and 91.4% specificity for difficult intubation, respectively. Conclusionand Recommendation: There was little correlation between MMC and CLG. MMT sensitivity was similarly low. As a result, as part of the screening test for difficult airway, extra clinical tests are required.

High-accuracy ultrasonic method for in-situ monitoring of oil film thickness in a thrust bearing

The ultrasonic method has been widely applied to measure the oil film thickness – a critical variable that reflects lubrication conditions. However, due to the thermal dependence of ultrasonic signals, significant deviations in film thickness measurements are introduced, hindering the in-situ application of the ultrasonic technique. To address this issue, a real-time temperature compensation method that can accurately obtain the frequency domain information of the reference signal is proposed. Specifically, the reflection from the substrate-coating interface compensates for the thermal effect on the phase increment and amplitude attenuation – this is noted as “self-calibration”. An extra experimental test with a substrate-coating-air structure is performed to calibrate the thermal effect on the coating-induced phase shift – this part is denoted as “pre-calibration”. The combination of “self-calibration” and “pre-calibration” enables the overall temperature compensation strategy. After the effectiveness validation with a temperature-controlled experiment, the proposed method is implemented in a thrust bearing in a heavy-duty hydropower generator with full running conditions, including loading and unloading, normal speed and shut-down. The largely ranged oil film thickness (3–330 μm) is ultrasonically measured and compared with the theoretical value, showing a higher measurement accuracy than the eddy current method.

QSAR, homology modeling, and docking simulation on SARS-CoV-2 and pseudomonas aeruginosa inhibitors, ADMET, and molecular dynamic simulations to find a possible oral lead candidate

BackgroundIn seek of potent and non-toxic iminoguanidine derivatives formerly assessed as active Pseudomonas aeruginosa inhibitors, a combined mathematical approach of quantitative structure-activity relationship (QSAR), homology modeling, docking simulation, ADMET, and molecular dynamics simulations were executed on iminoguanidine derivatives. ResultsThe QSAR method was employed to statistically analyze the structure-activity relationships (SAR) and had conceded good statistical significance for eminent predictive model; (GA-MLR: Q2LOO = 0.8027; R2 = 0.8735; R2ext = 0.7536). Thorough scrutiny of the predictive models disclosed that the Centered Broto-Moreau autocorrelation - lag 1/weighted by I-state and 3D topological distance-based autocorrelation—lag 9/weighted by I-state oversee the biological activity and rendered much useful information to realize the properties required to develop new potent Pseudomonas aeruginosa inhibitors. The next mathematical model work accomplished here emphasizes finding a potential drug that could aid in curing Pseudomonas aeruginosa and SARS-CoV-2 as the drug targets Pseudomonas aeruginosa. This involves homology modeling of RNA polymerase-binding transcription factor DksA and COVID-19 main protease receptors, docking simulations, and pharmacokinetic screening studies of hits compounds against the receptor to identify potential inhibitors that can serve to regulate the modeled enzymes. The modeled protein exhibits the most favorable regions more than 90% with a minimum disallowed region less than 5% and is simulated under a hydrophilic environment. The docking simulations of all the series to the binding pocket of the built protein model were done to demonstrate their binding style and to recognize critical interacting residues inside the binding site. Their binding constancy for the modeled receptors has been assessed through RMSD, RMSF, and SASA analysis from 1-ns molecular dynamics simulations (MDS) run. ConclusionOur acknowledged drugs could be a proficient cure for SARS-CoV-2 and Pseudomonas aeruginosa drug discovery, having said that extra testing (in vitro and in vivo) is essential to explain their latent as novel drugs and manner of action.

Barcode system – A boon for evidence based laboratory medicine [EBLM

Diagnostic pathology is intensely imerging in last 3 decade. Rapid development of technology and brisk gathering of basic knowledge has changed the whole practice of Pathology and laboratory medicine. The evidence-based laboratory medicine (EBLM) is one of the most essential fields to provide the backbone for the evidence-based medicine (EBM). Bar Coding System is one of the most useful tool for day to day laboratory work in the era of digitalization. Bar codes are being used more and more extensively in the laboratory for a variety of functions. By using barcode system we can overcome potential threat of duplicative testing, misdiagnosis, or delayed or unnecessary treatment.

Defensive medicine and the influence of litigation on doctors.

The term defensive medicine is used to describe the behavior of healthcare providers motivated by fear of litigation due to malpractice. It includes both avoidance behavior when the physician is unwilling to perform high risk procedures, as well as excessive ordering of extra tests and procedures. This leads to unnecessary diagnostic and therapeutic interventions which may be invasive and costly. Additionally, such a setting causes harms the patient-doctor relationship. A more specific legal framework, developed with respect to the innate nature of medicine, may improve the situation.

Ré-utilisation de lames d’immunohistochimie pour la réalisation de FISH : une solution pertinente d’épargne tissulaire

Diagnostic updates, an increased precision of tumor sub-type classification and the development of new diagnostic biomarkers (immunohistochemistry (IHC), Fluorescence in situ hybridization (FISH) and other molecular pathology techniques), have a significant impact on pathologists' management of tissue samples. The objective of this work was to test and validate the FISH technique on detached IHC slides. An IHC technique was first performed on 30 tissue samples. After detachment of the lamella, a FISH technique was then performed according to the usual protocol with a centromeric probe. A validation cohort (n=10) with duplicate testing using a traditional FISH technique and an IHC slide with a detached lamella was then carried out. Finally, a cohort of 20 "old" cases (IHC carried out over 2years ago) was also tested. Different types of probes (specific locus, break apart) have been used. All the slides were interpreted by a technician and a pathologist. Evaluation criteria were: the general interpretability of the slide; the percentage of labeled nuclei; intensity of the signal and the presence or absence of autofluorescence. FISH was interpretable in 100% of recently treated cases and 90% of "old" cases with a satisfactory intensity and a high percentage of labeled nuclei, without autofluorescence. The results of our study show that the reuse of IHC slides for performing FISH is a powerful means of economizing tissue samples, especially for small samples and in the absence of archived representative material.

A Hybrid Approach Using Design of Experiment and Artificial Neural Network in a Camless Heavy-Duty Engine

Abstract Increasingly stricter emission regulations and fleet CO2 targets drive the engine development toward clean combustion and high efficiency. To achieve this goal, planning and conducting experiments in a time- and cost-effective way play a vital role in finding the optimal combinations of all selectable parameters. This study investigated the effects of five engine parameters on two engine-out responses in a camless variable valve actuation (VVA) heavy-duty engine. Five engine parameters were intake valve lift (IVL), inlet valve closing (IVC), injection pressure, start of injection (SOI), and exhaust gas recirculation (EGR). Initially, a design of experiment (DoE) model was generated to predict both engine-out responses: brake-specific fuel consumption (BSFC) and BSNOx emissions. Due to a poor fit of the BSFC regression model from DoE analysis, an artificial neural network (ANN) model was developed to predict BSFC instead. A d-optimal design with five engine parameters at five levels was used to design the experiment. Extra test points together with d-optimal design points were utilized to train the ANN model. The well-trained ANN model for BSFC and DoE model for BSNOx were combined with a genetic algorithm (GA) to generate the Pareto-optimal front. The results proved the concept of using a hybrid statistical approach (DoE + ANN) with GA as an effective tool to generate a range of compromise design solutions. By extracting designs along the Pareto-optimal front, the impact of engine parameters on the system can be explained.

701-P: Time Features Improve Glucose Prediction

Objective: We show how the use of time features in a deep learning model improves glucose prediction on T1D patients. Method: Data of 139 adult T1D patients wearing DBLG1 System, from clinical trials NCT02987556 and NCT04190277, were used in this study. 70% of patients were used as a train set and 30% as a test set. The OHIO test database was used as an extra test set. In all cases, we only kept the data far from meals and physical activities. The hour of the day may reflect the meal pattern and night/day differences. To consider this, we added (cos ((time in hour) / 24 * 2 pi) , (sin ((time in hour) / 24 * 2 pi) as input to the perceptron. The day of the week may also reflect different behaviors. To consider this, we input a label for weekday vs. week-end. We trained 2-layer perceptrons using past glucose levels (13 values with 5 minutes interval) and combinations of these time features to predict the glycemia at 45 minutes. Results: On the clinical trials data, the baseline model achieved a 13.35% MARD and a 26.56 RMSE. When using the hour, we got a 13.2% MARD and 26.35 RMSE. When using the weekday label, we got a 13.32% MARD and an RMSE of 26.56. When using the hour and the weekday label, we obtained a 13.17% MARD and a 26.39 RMSE. We observe similar results on the Ohio data: the figure shows the clark grids for the baseline (left) and when using hour and weekday label (right) . Conclusion: The use of the time of the day leads to great improvements on MARD and RMSE, as does, to a lesser extent, the use of the day of the week. Disclosure M.Louis: Employee; Diabeloop SA. H.M.Romero-ugalde: Employee; Diabeloop SA. A.Adenis: Employee; Diabeloop SA. L.Daudet: Employee; Diabeloop SA. Y.Tourki: Employee; Diabeloop SA. E.Huneker: Board Member; Diabeloop SA.

Data Storage Security in Cloud Computing Using AES Algorithm and MD5 Algorithm

Abstract: The proposed method uses cryptographic techniques to maintain security as security is a critical issue for the cloud, and keeping secure data is a major concern today. Overload due to data duplication is a new challenge for clouds. This article presents the data a download algorithm based on MD5 and AES. Because MD5 more secure than other hashing algorithms, goal Using MD5 algorithm for duplicating data and bringing data to server after uninstalling duplicate copy server. Purpose of use AES security is encrypting data and storing it securely on a server. Update the hash of a newly uploaded file using AES. Results and provides a comparison of several hashing algorithms, showing that MD5 is much safer and takes less time than others. The basic method, which does not use duplicate testing, uses additional storage space and takes longer. The main goal storing useful data in the cloud. Keywords: Cloud Computing, Security, AES Algorithm, MD5 Algorithm

New EHR certification requirements and their association with duplicate tests and images.

Certified electronic health record (EHR) technology has been adopted by most hospitals and health care providers. In 2015, the Office of the National Coordinator for Health Information Technology (ONC) published new EHR certification requirements, known as the 2015 Edition. To date, no research has examined the impact of hospitals' adoption of the 2015 Edition on health care delivery. We analyzed aggregated, longitudinal data drawn from a repository of deidentified health insurance claims collected by FAIR Health, the repository was estimated to represent about 75% of the privately insured in the United States. These data were linked with the American Hospital Association (AHA) Information Technology Supplement Survey to obtain hospitals' health information technology characteristics. A fixed effects specification was used to assess the incidence of duplicate testing and imaging in both inpatient and outpatient settings before and after the hospitals' adoption of the 2015 Edition. Hospitals with the 2015 Edition were less likely to perform duplicate imaging for inpatients by 5 percentage points (or 50% from baseline). Hospitals that adopted the 2015 Edition and actively engaged in interoperable data exchange were even less likely to perform duplicate lab tests. Adoption of the 2015 Edition certified EHR was negatively associated with the incidence of lab and imaging test duplication in both the outpatient and inpatient settings. However, the results were not robust across specifications. Given that multiple factors influence care delivery decisions, improvements in certification standards alone are unlikely to eliminate unneeded duplicate lab and imaging tests.

A Deep Learning System to Predict the Histopathological Results From Urine Cytopathological Images.

BackgroundAlthough deep learning systems (DLSs) have been developed to diagnose urine cytology, more evidence is required to prove if such systems can predict histopathology results as well.MethodsWe retrospectively retrieved urine cytology slides and matched histological results. High-power field panel images were annotated by a certified urological pathologist. A deep learning system was designed with a ResNet101 Faster R-CNN (faster region-based convolutional neural network). It was firstly built to spot cancer cells. Then, it was directly used to predict the likelihood of the presence of tissue malignancy.ResultsWe retrieved 441 positive cases and 395 negative cases. The development involved 387 positive cases, accounting for 2,668 labeled cells, to train the DLS to spot cancer cells. The DLS was then used to predict corresponding histopathology results. In an internal test set of 85 cases, the area under the curve (AUC) was 0.90 (95%CI 0.84–0.96), and the kappa score was 0.68 (95%CI 0.52–0.84), indicating substantial agreement. The F1 score was 0.56, sensitivity was 71% (95%CI 52%–85%), and specificity was 94% (95%CI 84%–98%). In an extra test set of 333 cases, the DLS achieved 0.25 false-positive cells per image. The AUC was 0.93 (95%CI 0.90–0.95), and the kappa score was 0.58 (95%CI 0.46–0.70) indicating moderate agreement. The F1 score was 0.66, sensitivity was 67% (95%CI 54%–78%), and specificity was 92% (95%CI 88%–95%).ConclusionsThe deep learning system could predict if there was malignancy using cytocentrifuged urine cytology images. The process was explainable since the prediction of malignancy was directly based on the abnormal cells selected by the model and can be verified by examining those candidate abnormal cells in each image. Thus, this DLS was not just a tool for pathologists in cytology diagnosis. It simultaneously provided novel histopathologic insights for urologists.

Isometric artifacts from polymerase chain reaction-massively parallel sequencing analysis of short tandem repeat loci: An emerging issue from a new technology?

The recent introduction of polymerase chain reaction (PCR)‐massively parallel sequencing (MPS) technologies in forensics has changed the approach to allelic short tandem repeat (STR) typing because sequencing cloned PCR fragments enables alleles with identical molecular weights to be distinguished based on their nucleotide sequences. Therefore, because PCR fidelity mainly depends on template integrity, new technical issues could arise in the interpretation of the results obtained from the degraded samples. In this work, a set of DNA samples degraded in vitro was used to investigate whether PCR‐MPS could generate “isometric drop‐ins” (IDIs; i.e., molecular products having the same length as the original allele but with a different nucleotide sequence within the repeated units). The Precision ID GlobalFiler NGS STR panel kit was used to analyze 0.5 and 1 ng of mock samples in duplicate tests (for a total of 16 PCR‐MPS analyses). As expected, several well‐known PCR artifacts (such as allelic dropout, stutters above the threshold) were scored; 95 IDIs with an average occurrence of 5.9 IDIs per test (min: 1, max: 11) were scored as well. In total, IDIs represented one of the most frequent artifacts. The coverage of these IDIs reached up to 981 reads (median: 239 reads), and the ratios with the coverage of the original allele ranged from 0.069 to 7.285 (median: 0.221). In addition, approximately 5.2% of the IDIs showed coverage higher than that of the original allele. Molecular analysis of these artifacts showed that they were generated in 96.8% of cases through a single nucleotide change event, with the C > T transition being the most frequent (85.7%). Thus, in a forensic evaluation of evidence, IDIs may represent an actual issue, particularly when DNA mixtures need to be interpreted because they could mislead the operator regarding the number of contributors. Overall, the molecular features of the IDIs described in this work, as well as the performance of duplicate tests, may be useful tools for managing this new class of artifacts otherwise not detected by capillary electrophoresis technology.

A cohort study of duplicate faecal immunochemical testing in patients at risk of colorectal cancer from North-West England

ObjectivesWe sought to investigate if duplicate faecal immunochemical testing (FIT) sampling improves the negative and positive predictive value of patients thought to be at risk of colorectal cancer (CRC). Specifically,...

Experimental analysis and predictive modelling of linear viscoelastic response of asphalt mixture under dynamic shear loading

The use of predictive models can facilitate the inclusion of shear parameters in asphalt mixture evaluation and design processes. Unlike more extensively studied tension–compression models, the currently existing shear model, the Hirsch model, has unrealistic constants, particularly for the prediction of phase angle. Aiming at an improved predictive model in shear, this study employs a simple shear apparatus to experimentally analyse the linear viscoelastic properties of asphalt mixtures for road paving. Master curves were constructed and compared between different asphalt mixtures. Additionally, the test results were also analysed in the Black space and the Cole-Cole space. The dynamic shear response of asphalt mixtures was thereafter modelled on the basis of the Hirsch model. As the original model for phase angle prediction was found to be unrealistic, a particular focus in this study was put on identifying realistic empirical relationships for predicting the phase angle of asphalt mixtures in shear. More reliable shear test results of asphalt mixtures were used to calibrate the model, and extra test data were utilized to validate the calibrated model. It is indicated that the predictive model after calibration could deliver results of greatly improved accuracy, especially at the high-frequency and low-frequency ends. The analysis and modelling also leads to realistic empirical relationships for predicting the phase angle of asphalt mixtures in shear. The experimental verification confirms the good prediction accuracy of the calibrated model and proposed empirical relationships.

Pathologist initiated reflex BRAF mutation testing in metastatic melanoma: experience at a specialist melanoma treatment centre

Testing for BRAF mutations in metastatic melanoma is pivotal to identifying patients suitable for targeted therapy and influences treatment decisions regarding single agent versus combination immunotherapy. Knowledge of BRAF V600E immunohistochemistry (IHC) results can streamline decisions during initial oncology consultations, prior to DNA-based test results. In the absence of formal guidelines that require pathologist initiated ('reflex') BRAF mutation testing, our institution developed a local protocol to perform BRAF V600E IHC on specimens from all stage III/IV melanoma patients when the status is otherwise unknown. This study was designed to evaluate the application of this protocol in a tertiary referral pathology department. A total of 408 stage III/IV melanoma patients had tissue specimens accessioned between 1 January and 31 March in three consecutive years (from 2019 to 2021), reported by 32 individual pathologists. The BRAF mutation status was established by pathologists in 87% (352/408) of cases. When a prior BRAF mutation status was previously known, as confirmed in linked electronic records (202/408), this status had been communicated by the clinician on the pathology request form in 1% of cases (3/202). Pathologists performed BRAF V600E IHC in 153 cases (74% of cases where the status was unknown, 153/206) and testing was duplicated in 5% of cases (20/408). Reflex BRAF IHC testing was omitted in 26% of cases (53/206), often on specimens with small volume disease (cytology specimens or sentinel node biopsies) despite adequate tissue for testing. Incorporating BRAF IHC testing within routine diagnostic protocols of stage III/IV melanoma was both feasible and successful in most cases. Communication of a patient's BRAF mutation status via the pathology request form will likely improve implementation of pathologist initiated BRAF mutation testing and may result in a reduction of duplicate tests. To improve pathologist reflex testing rates, we advocate for the use of an algorithmic approach to pathologist initiated BRAF mutation testing utilising both IHC and DNA-based methodologies for stage III/IV melanoma patients.

Medical costs of children admitted to the neonatal intensive care unit: The role and possible economic impact of WES in early diagnosis

It has been estimated that at least 6.0% of neonates admitted to the Neonatal Intensive Care Unit remains genetically undiagnosed because genetic testing is not routinely performed. The objective of this study is to provide an overview of average healthcare costs for patients admitted to the Neonatal Intensive Care Unit and to assess possible impact of implementing Whole Exome Sequencing (WES) on these total healthcare costs. Hereto, we retrospectively collected postnatal healthcare data of all patients admitted to the level IV Neonatal Intensive Care Unit at the Radboudumc (October 2013–October 2015) and linked unit costs to these healthcare consumptions. Average healthcare costs were calculated and a distinction between patients was made based on performance of genetic tests and the presence of congenital anomalies. Overall, on average €26,627 was spent per patient. Genetic costs accounted for 2.3% of all costs. Healthcare costs were higher for patients with congenital anomalies compared to patients without congenital anomalies. Patients with genetic diagnostics were also more expensive than patients without genetic diagnostics. We next modelled four scenarios based on clinical preselection. First, when performing trio-WES for all patients instead of current diagnostics, overall healthcare costs will increase with 22.2%. Second, performing trio-WES only for patients with multiple congenital anomalies will not result in any cost changes, but this would leave patients with an isolated congenital anomalies untested. We therefore next modelled a scenario performing trio-WES for all patients with congenital anomalies, increasing the average per patient healthcare costs by 5.3%. This will rise to a maximum of 5.5% when also modelling for an extra genetic test for clinically selected patients to establish genetic diagnoses that are undetectable by WES. In conclusion, genetic diagnostic testing accounted for a small fraction of total costs. Implementation of trio-WES as first-tier test for all patients with congenital anomalies will lead to a limited increase in overall healthcare budget, but will facilitate personalized treatments options guided by the diagnoses made.

Prediction model for load effective distribution width of slab in composite box girders using gene expression programming

To determine the loading condition of the deck slab in girder bridges, the concept of the load effective distribution width is widely accepted in practical design. However, effective models for calculating the load effective distribution width of deck slab in steel–concrete composite box girders (SCCBG) are still lacking, which may bring about significant errors in slab design. In this study, a rational model to calculate the load effective distribution width of deck slabs in SCCBG in both the elastic and elastoplastic stages is proposed using the gene expression programming (GEP). First, four loading tests were conducted and elaborate finite element (FE) models were developed to investigate the load distribution of the slab in SCCBG. The FE models were validated by the test results and then applied to conduct a comprehensive parametric study to obtain the influences of the design parameters and the database for the GEP model. On this basis, formulas forthe load effective distributionwidth in the elastic and elastoplastic stages were proposed by using the GEP algorithm. Furthermore, extra testing data were applied to verify the validity of the proposed models. By comparing the results given by several bridge codes, it is demonstrated that the proposed models can provide more accurate and reliable predictions and are quite simple and useful for pre-design applications.

Using a simplified ATP algorithm to improve data reliability and improve cleanliness standards for surface and medical device hygiene.

An algorithm has been improved to mitigate variability in cleanliness measurements of various surfaces using rapid Adenosine Triphosphate (ATP) testing. A cleaning intervention step (CIS) verifies the cleanability of those surfaces. ATP testing was performed on surfaces which were pre-approved as "clean" and ready for re-use. Adjacent (duplicate) ATP sampling was undertaken on 421 environmental surfaces, medical devices and other implements. The CIS was conducted on 270 surfaces using an aseptic technique and disposable cleaning wipes. The two initial ATP results were plotted against each other with a 100 RLU threshold grading the results as clean (2x<100RLU), dirty (2x>100RLU) or equivocal (1x<100RLU and 1x>100RLU). Of the surfaces sampled, 68.5% were clean (288/421), 13.5% were dirty (57/421) and 18% were equivocal (76/421). The duplicate testing demonstrated a false negative rate of 10% (44/421) where the first swab was <100 RLU and the second swab >100 RLU. For the equivocal group, the gap between the two swabs was >100 RLU for 7.5% of surfaces (33/421). The CIS was conducted on 270 of the surfaces tested and showed that cleaning could be improved (P=<0.001) on 88.5% of surfaces (239/270). The simplified ATP testing algorithm provides real-time discrimination between surface cleanliness levels and improved certainty over surface hygiene. The duplicate swab sampling approach mitigates uncontrolled variability in the results and the CIS provides a nuanced understanding of the measurable cleanliness of any surface.

SEMG-Triggered Fast Assistance Strategy for a Pneumatic Back Support Exoskeleton.

To prevent lower back pain (LBP) in the industrial workplace, various powered back support exoskeletons (BSEs) have been developed. However, conventional kinematics-triggered assistance (KA) strategies induce latency, degrading assistance efficiency. Therefore, we proposed and experimentally evaluated a surface electromyography (sEMG)-triggered assistance (EA) strategy. Nine healthy subjects participated in the lifting experiments: 1) external loads test, 2) extra latency test, and 3) repetitive lifting test. In the external loads test, subject performed lifting with four different external loads (0 kg, 7.5 kg, 15 kg, and 22.5 kg). The assistance was triggered earlier by EA compared to KA from 114 ms to 202 ms, 163 ms to 269 ms for squat and stoop lifting respectively, as external loads increased from 0 kg to 22.5 kg. In the extra latency test, the effects of extra latency (manual switch, 0 ms, 100 ms and 200 ms) in EA on muscle activities were investigated. Muscle activities were minimized in the fast assistance (0 ms and 100 ms) condition and increased with extra latency. In the repetitive lifting test, the EA strategy significantly reduced L1 muscle fatigue by 70.4% in stoop lifting, compared to KA strategy. Based on the experimental results, we concluded that fast assistance triggered by sEMG improved assistance efficiency in BSE and was particularly beneficial in heavy external loads situations. The proposed assistive strategy can be used to prevent LBP by reducing back muscle fatigue and is easily applicable to various industrial exoskeleton applications.