Continuous Performance Monitoring Research Articles

Actigraphic measurement of the upper limbs movements in acute stroke patients

BackgroundStroke units provide patients with a multiparametric monitoring of vital functions, while no instruments are actually available for a continuous monitoring of patients motor performance. Our aim was to develop an actigraphic index able both to identify the paretic limb and continuously monitor the motor performance of stroke patients in the stroke unit environment.MethodsTwenty consecutive acute stroke patients (mean age 69.2 years SD 10.1, 8 males and 12 females) and 17 bed-restrained patients (mean age 70.5 years SD 7.3, 7 males and 10 females) hospitalized for orthopedic diseases of the lower limbs, but not experiencing neurological symptoms, were enrolled. This last group represented our control group. The motor activity of arms was recorded for 24 h using two programmable actigraphic systems showing off as wrist-worn watches. The firmware segmented the acquisition in epochs of 1 minute and for each epoch calculates two motor activity indices: MAe1 (Epoch-related Motor Activity index) and MAe2 (Epoch-related Motor Activity index 2). MAe1 is defined as the standard deviation of the acceleration module and MAe2 as the module of the standard deviation of acceleration components. To describe the 24 h motor performance of each limb, we calculated the mean value of MAe1 and MAe2 (respectively MA1_24h and MA2_24h). Then we obtained two Asymmetry Rate Indices: AR1_24h and AR2_24h to show the motor activity prevalence. AR1_24h refers to the asymmetry index between the values of MAe1 of both arms and AR2_24h to MAe2 values.The stroke patients were clinically evaluated by NIHSS at the beginning (NIHSST0) and at the end (NIHSST1) of the 24 h actigraphic recordings.ResultsBoth MA1_24h and MA2_24h indices were smaller in the paretic than in the unaffected arm (respectively p = 0.004 and p = 0.004). AR2_24h showed a better capability (95% of paretic arms correctly identified, Phi Coefficient: 0.903) to discriminate the laterality of the clinical deficit than AR1_24h (85% of paretic arms correctly identified, Phi Coefficient: 0,698). We also found that AR1_24h did not differ between the two groups of patients while AR2_24h was greater in stroke patients than in controls and positively correlated with NIHSS total scores (r: 0.714, p < 0.001 for NIHSS, IC95%: 0.42–0.90) and with the sub-score relative to the paretic upper limb (r: 0.812, p < 0.001, IC95%: 0.62–0.96).ConclusionsOur data show that actigraphic monitoring of upper limbs can detect the laterality of the motor deficit and measure the clinical severity. These findings suggest that the above described actigraphic system could implement the existing multiparametric monitoring in stroke units.

Building performance monitoring: from in-situ measurement to regression-based approaches

Simple and robust data analysis methodologies are crucial to learn insights from measured data and reduce the performance gap in building stock. For this reason, continuous performance monitoring should become a more diffuse practice in order to improve our design and operation strategies for the future. The research presented aims to highlight potential links between experimental approaches for test-facilities and methods and tools used for continuous performance monitoring, at the state of the art. In particular, we explore the relation between ISO 9869:2014 method for in-situ measurement of thermal transmittance (U) and regression-based monitoring approaches, such as co-heating test and energy signature, for heat load coefficient (HLC) and solar aperture (gA) estimation. In particular, we highlight the robustness and scalability of these monitoring techniques, considering relevant issues in current integrated engineer design perspective. These issues include, among others, the necessity of limiting the number of a sensors to be installed in buildings, the possibility of employing both experimental and real operation data and, finally, the possibility to automate and perform monitoring at multiple scales, from single components, to individual buildings, to building stock and cities.

Evidence-based medical equipment management: a convenient implementation

Maintenance is a crucial subject in medical equipment life cycle management. Evidence-based maintenance consists of the continuous performance monitoring of equipment, starting from the evidence—the current state in terms of failure history—and improvement of its effectiveness by making the required changes. This process is very important for optimizing the use and allocation of the available resources by clinical engineering departments. Medical equipment maintenance is composed of two basic activities: scheduled maintenance and corrective maintenance. Both are needed for the management of the entire set of medical equipment in a hospital. Because the classification of maintenance service work orders reveals specific issues related to frequent problems and failures, specific codes have been applied to classify the corrective and scheduled maintenance work orders at Careggi University Hospital (Florence, Italy). In this study, a novel set of key performance indicators is also proposed for evaluating medical equipment maintenance performance. The purpose of this research is to combine these two evidence-based methods to assess every aspect of the maintenance process and provide an objective and standardized approach that will support and enhance clinical engineering activities. Starting from the evidence (i.e. failures), the results show that the combination of these two methods can provide a periodical cross-analysis of maintenance performance that indicates the most appropriate procedures.Graphical abstractThe left side shows a block diagram of the process needed to calculate the proposed set of KPIs, starting from technological, organizational and financial data. On the upper right it is shown an example of scheduled maintenance analysis for a specific class of equipment (legend in the article body). The bottom right part shows how the KPIs can be implemented in a business intelligence dashboard.

A 5-year assessment of malaria documentation and reporting practices in government healthcare facilities in Lagos, Nigeria

Background: Robust and effective information management systems are critical for successful malaria control and elimination. This study was a follow up study to assess the practices of Lagos State public healthcare facilities with regards to malaria documentations and reporting to the local government authorities (LGAs) in Lagos Nigeria in 2009 and then in 2013.Methods: We conducted a descriptive cross-sectional repeated survey of all 218 functional government-owned health facilities in Lagos State between in years 2009 and 2013 using a structured questionnaire. Approval was obtained from the research ethics committee of the Lagos State Ministry of Health.Results: There was a decrease in the proportion of primary &amp; secondary healthcare facilities that document all cases of malaria seen in the facilities from 97.9% and 95.5% respectively in 2009 to 91.5% and 85.7% in 2013. About 53% of the primary healthcare facilities rendered malaria data to the Local Government Area (LGA) using the IDSR system in 2009 which marginally increase to 62.4% in 2013. Whereas in 2009, 63.6% of secondary healthcare facilities rendered malaria data to the LGA whilst 50% did in 2013. The only Tertiary health facility in the state did not render malaria data to the LGA in 2009 but did in 2013.Conclusions: There was a gradual reduction in malaria documentation by the government healthcare facilities. Therefore, there is need to intensify training among health workers in the government health facilities in the state with continuous monitoring and evaluation of performance to determine the impact.

Performance monitoring beyond choice tasks: The time course of force execution monitoring investigated by event-related potentials and multivariate pattern analysis

Accurate force production is an essential motor function which, in most cases, requires continuous performance monitoring. Unlike choice-response tasks with two response alternatives, the accuracy in a force production paradigm is defined as an area between an upper and lower limit on the force continuum. In the present study, we investigated the neural mechanisms underlying force production. We used a force production task in which the participants (n = 48) were asked to exert a brief force pulse within a specific force range. This allowed: (1) investigation of action monitoring activity during force execution using response-locked and feedback-locked event-related potential (ERP) components known to be involved in error monitoring; (2) multivariate pattern analysis (MVPA) for ERPs. We found that the different force production ranges (characterised as too low, correct, and too high with respect to the target force range) showed no clear error-specific variations in the ERP components of interest. MVPA, on the other hand, allowed for successful classification, not only between the correct and the incorrect outcome conditions, but also between the two incorrect outcome conditions. This suggests that the classifier identified neural patterns reflecting the force magnitude rather than the correctness of a response. Moreover, additional support-vector regression (SVR) analyses showed that single-trial response parameters (i.e. peak force and time-to-peak) could be decoded from the brain activity pattern starting from 140 ms (for peak force) and 270 ms (for time-to-peak) before the response onset. These results indicate that the motor program defined the magnitude and timing of the force pulse before response execution, while the correctness of that response (in relation to the “default force” required) was not yet foreshadowed in neural signals. Finally, this study presents the first evidence of a post-error force adjustment mechanism, for which participants produced a higher force in trials after under-producing the required force, and a lower force in trials after over-producing the required force.

Assessment of online bacterial particle counts for monitoring the performance of reverse osmosis membrane process in potable reuse

Safety of potable reuse can be enhanced by improved water quality monitoring techniques for assessing water treatment processes. This study evaluated the efficacy of online bacterial counting for continuous monitoring of reverse osmosis (RO) membranes to remove bacteria using real-time bacteriological commercial counters and an on-site pilot-scale RO system. Prior to on-site assessments, the online bacterial counting was verified by comparing the measurement of fluorescent particles in water with flow cytometry. During a seven day pilot test of RO treatment at a water reclamation plant, online bacterial counts in RO permeate were monitored below 15 counts/mL; whereas the bacterial counts in RO feed water were approximately 2500 to 10,000 counts/mL. Removal rates of bacterial counts ranged from 2.6 to 3.1-log (average = 2.9-log) by continuously monitoring bacterial removal. This is greater than a 2-log reduction frequently determined using other water quality surrogates (i.e., electrical conductivity). Overall, the continuous monitoring of bacteria in RO feed and permeate can be implemented without the addition of chemicals to provide near real-time bacterial counts to measure their reduction after RO treatment. This can be developed for continuous performance monitoring of the RO process, providing greater assurance of microbial water quality after RO treatment.

A skin patch for sensing blood pressures.

A wearable ultrasound patch enables the continuous monitoring of cardiovascular performance outside the intensive care unit.

Technology Focus: Reservoir Performance and Monitoring (September 2018)

Technology Focus Since the last Reservoir Performance and Monitoring feature in 2017, the industry has continued to advance with innovation in technology and business models to drive sustainable change. Operators around the world have continued lowering production costs aggressively, and oilfield service companies have continued to survive by making a low-margin profit in a greatly competitive market. If the industry until recently was lamenting an oversupply of oil and that a global upstream investment slump caused a focus on incremental technology improvements with fewer capital resources and personnel, now a looming oil-supply shortage has reignited discussions about how innovation, digital technologies, and collaborations can accelerate future major project development. In the last 12 months, 157 technical papers were presented at various conferences and meetings with reservoir performance and monitoring programs and were reviewed for this feature. For comparison, 160 were reviewed for the 2017 feature. Interestingly, 62 papers had first authors from academia, 70 from operating companies, and 25 from oilfield services companies and consulting firms. Sixty-three papers had authors with different affiliations. The six papers selected and recommended as additional reading are a representative sample of the papers reviewed for this feature. They are a geographically diverse mix of fundamental research, industrial research and development, and field-application studies, reporting the latest published advances in reservoir-performance monitoring, analysis, and optimization. In considering the 157 technical papers reviewed for this feature, I am looking forward to seeing how our industry is going to react through innovation and digital technologies to the supply and demand changes of coming years. A new era of operational efficiency improvements, improved recovery factors, and lower production costs from continuous reservoir performance monitoring, analysis, and optimization is ready to begin. Recommended additional reading at OnePetro: www.onepetro.org. SPE 188890 Effect of Irreversible Retention on Tracer Deployments: Constraining Novel Material Deployments by Hsieh Chen, Aramco, et al. SPE 189846 Applying Subsurface DNA Diagnostics and Data Science in the Delaware Basin by J. Silva, Anadarko, et al. SPE 190480 Effect of Dilution on Acoustic and Transport Properties of Reservoir Fluid Systems by Ram R. Ratnakar, Shell, et al.

Prognostic and predictive factors in patients with brain metastases from solid tumors: A review of published nomograms

To review published nomograms that predict endpoints such as overall survival (OS) or risk of intracranial relapse in patients with brain metastases from solid tumors. The methods and results of nomogram studies identified by a systematic search were extracted and compared, stratified by endpoint predicted by the respective nomograms. In particular, validation strategies (external/internal), concordance indices (cut-off 0.75) and comparisons to older models were analyzed. Six publications reported on prediction of OS. Most of these analyses focused on one particular primary tumor site, e.g., breast cancer or hepatocellular carcinoma, while the largest study included different primary tumor sites. The median number of patients was 244. Three of six studies included external validation cohorts. With few exceptions, concordance indices <0.75 were reported. In all studies reporting this endpoint, the nomogram outperformed older prognostic scores. Two nomograms focused on development of new brain metastases after radiosurgery (one externally validated), one on survival free from salvage whole brain radiotherapy (WBRT) after radiosurgery, and one on neurologic and non-neurologic death in patients receiving radiosurgery after WBRT failure. All concordance indices of these 4 nomograms were <0.70. Taking into account concordance indices and comparisons to older prognostic models, the most promising, externally validated nomograms are the breast cancer and the non-small cell lung cancer nomogram predicting OS, and the distant brain failure after radiosurgery nomogram. Additional validation studies as well as continuous monitoring of the models' performance appear necessary to ensure their clinical applicability in the present era of rapidly changing treatment paradigms.

Analysis of the Learning Curve in Mitral Valve Replacement Through the Right Anterolateral Minithoracotomy Approach: A Surgeon’s Experience with the First 100 Patients

To apply the cumulative sum (CUSUM) failure analysis to assess the performance of a single surgeon during mitral valve replacement via the right anterolateral minithoracotomy (RAMT) approach and to analyse the learning curve for the procedure. A total of 100 mitral valve replacements were performed using the RAMT approach from June 2011 to April 2013 by a single surgeon with no prior experience of this technique. Patients were divided into five blocks according to the operation date. The perioperative data were collected prospectively and analysed using descriptive statistics and CUSUM failure analysis. No significant differences in the background factors among the five periods were observed, except for a small increase in patient age from periods 1 to 5 (p=0.004). The surgeon's performance improved with time; a decrease in the cross-clamp time, operative time, and blood loss was observed (p<0.001). However, no significant difference in the number of failed cases was observed among the periods. All failure cases were evaluated by the CUSUM failure analysis and the CUSUM curve reflected a learning curve associated with this new procedure. The surgeon crossed the lower 80% boundary after about 33 operations, which indicates that better results can be obtained after this point. Minimally invasive mitral valve surgery using the RAMT approach can be performed by a new surgeon. Furthermore, CUSUM curve analysis is a simple statistical method to implement continuous individual performance monitoring.

Brain activations supporting linking of action phases in a sequential manual task

Most everyday manual tasks, like grabbing a cup of coffee to drink, are comprised of a sequence of action phases. Efficient phase transitions, or linking, are achieved using a predictive control policy where motor commands for the next phase are specified and released in anticipation of sensory confirmation of goal completion of the current phase. If there is a discrepancy between predicted and actual sensory feedback about goal completion, corrective actions are employed to complete the current action phase before proceeding to the next. However, we lack understanding about brain activations supporting such predictive linking and corrective actions in manual tasks. In this study, during 3-T MRI-scanning, sixteen participants (5 males, 11 females; mean age 27.3 years, range 23–37) performed a sequential manual task, with or without the possibility for predictive linking. We found that predictive linking of action phases was associated with increased activation in a network that included right-sided fronto-parietal areas related to visuospatial attention, eye movements and motor planning, left-sided parietal areas related to implicit timing and shifts of motor attention, occipital regions bilaterally reflecting visual processing related to the attended next target, and finally, the anterior midcingulate cortex involved in continuous performance monitoring. Corrective actions were associated with increased activation in the left dorsolateral prefrontal cortex involved in reestablishing executive control over previously automatized behavior.

The Design and Development of Prediction Models for Maximizing Students’ Academic Achievement

To enable early identification and intervention for students at risk for academic failure and for failure on the USMLE Step 1 Examination, three predictive models (pre-matriculation, end of M1, and end of M2) were developed that include both behavioral attributes (Learning and Study Strategies Inventory: LASSI subscale scores) and performance measures (internal examinations and National Board of Medical Examiners [NBME] Comprehensive Basic Science Examination [CBSE] progress tests). Pearson product moment correlation coefficients and multivariate regression modeling were used to determine optimal combinations of independent variables. The pre-matriculation prediction model includes MCAT scores and undergraduate overall GPA. The end of M1 model includes the progress test scores on the NBME CBSE administered at the end of first year medical school (M1), LASSI subscale scores, and weighted performance on M1 internal examinations. Finally, the end of M2 model includes CBSE progress test scores at the end of M1 and second year medical school (M2), LASSI subscale scores, and weighted performance on M1 and M2 internal examinations. Our pre-matriculation, end of M1, and end of M2 models explain 24, 62, and 81% of the variation in USMLE Step 1 performance, respectively. The inclusion of LASSI subscale scores improves the end of M1 model from 60 to 62% and end of M2 model from 79 to 81% in explaining variation in USMLE Step 1 scores. Continuous monitoring of student performance based on these multiple measures supports a holistic perspective on progress, areas of ongoing weakness, and potentially, identification of yet-undetected weakness for targeted interventions.

Variable life adjusted display methodology for continuous performance monitoring of carotid endarterectomy.

Introduction The aim of this study was to use variable life-adjusted display (VLAD) methodology to monitor performance of six vascular surgeons undertaking carotid endarterectomy in a single institution. Materials and methods This was a prospective study with continuous analysis. A risk score model to predict 30-day stroke or death for individual patients was developed from data collected from 839 patients from 1992 to 1999. The model was used to monitor performance of six surgeons from 2000 to 2009. Individual risk factors and 30-day outcomes were analysed and VLAD plots were created for the whole unit and for each surgeon. Results Among the 941 carotid endarterectomies in the performance analysis, 28 adverse events were recorded, giving an overall stroke or death rate of 3.06%. The risk model predicted there would be 33 adverse events. There was no statistical difference between the predicted and the observed adverse events (P>0.2, χ2 value 1.25, 4 degrees of freedom). The VLAD plot for the whole unit shows an overall net gain in operative performance, although this could have been chance variation. The individual VLAD plot showed that surgeons 1, 2, 3 and 6 to have an overall net gain in the number of successful operations. The changes observed between the surgeons was not significant (P>0.05) suggesting chance variation only. Conclusions Performance of carotid endarterectomy can be continuously assessed using VLAD methodology for units and individual surgeons. Early identification and correction of performance variation could facilitate improved quality of care.

Measurement of the Perception of Control during Continuous Movement using Electroencephalography.

“Sense of control” refers to the subjective feeling of control over external events. Numerous neuropsychological studies have investigated the neural basis of the sense of control during action performance; however, most previous studies have focused on responses to a single discrete action outcome rather than real-time processing of action-outcome sequences. In the present study, we aimed to identify whether certain patterns of brain activation are associated with the perceived control during continuous movement. We recorded electroencephalography (EEG) signals while participants continuously moved a right-handed mouse in an attempt to control multiple visual stimuli. When participants perceived a sense of control over the stimuli, we observed a positive potential approximately 550 ms after the onset of movement, while no similar potential was observed when participants reported a lack of control. The appearance of this potential was consistent with the time window of awareness of control in a behavioral test using the same task, and likely reflected the explicit allocation of attention to control. Moreover, we found that the alpha-mu rhythm, which is linked to sensorimotor processing, was significantly suppressed after participants came to a conclusion regarding the level of control, regardless of whether control or lack of control was perceived. In summary, our results suggest that the late positive potential after the onset of the movement and the suppression of alpha-mu rhythm can be used as markers of the perception of control during continuous action performance and feedback monitoring.

Minimizing Attrition for Multisite Emergency Care Research.

Loss to follow-up of enrolled patients (a.k.a. attrition) is a major threat to study validity and power. Minimizing attrition can be challenging even under ideal research conditions, including the presence of adequate funding, experienced study personnel, and a refined research infrastructure. Emergency care research is shifting toward enrollment through multisite networks, but there have been limited descriptions of approaches to minimize attrition for these multicenter emergency care studies. This concept paper describes a stepwise approach to minimize attrition, using a case example of a multisite emergency department prospective cohort of over 3,000 patients that has achieved a 30-day direct phone follow-up attrition rate of <3%. The seven areas of approach to minimize attrition in this study focused on patient selection, baseline contact data collection, patient incentives, patient tracking, central phone banks, local enrollment site assistance, and continuous performance monitoring. Appropriate study design, including consideration of these methods to reduce attrition, will be time well spent and may improve study validity.

Screening, Brief Intervention and Referral to Treatment Implementation in the Emergency Department

We sought to qualitatively evaluate impediments in implementing a novel Screening, Brief Intervention and Referral to Treatment (SBIRT) protocol into normal emergency department (ED) workflow for patients with at-risk drug/alcohol behavior. From 2010, administrative and nursing champions trained nurses at a single ED (census: 50,000 visits/yr) in SBIRT and incorporated SBIRT into normal ED nursing workflow in 2012. To qualitatively analyze impediments in SBIRT implementation, we created a semi-structured questionnaire for protocol champions with subsequent follow-up. Investigators analyzed responses using qualitative methodology based on a modified grounded theory framework. In 2012, 47693 visits by 31525 patients met SBIRT protocol initiation criteria with a protocol execution rate of 83.4%. Interview data identified the following impediments: (1) Need for multi-layer leadership support; (2) Application of an overarching vision to constantly address personnel attitudes towards SBIRT appropriateness in the ED; (3) Continuous performance monitoring to address implementation barriers close to real time; (4) Strategic and adaptive SBIRT training; and (5) External systemic changes through internal leadership. Qualitative analysis suggests that impediments to SBIRT implementation in the ED include views of SBIRT appropriateness in the ED, need for continuous reinforcement/refinement of personnel training / protocol execution, and fostering of additional administrative/financial champions.

Structural and seismic monitoring of the “Cardarelli” Hospital in Campobasso

Recent earthquakes occurred in Italy and throughout the world have once again emphasized the critical role of health facilities for post-earthquake emergency management. Due to earthquake, several hospitals (L’Aquila 2009, Amatrice 2016) have lost their functionality because of damage to structural as well as non-structural members, equipment and installations.The primary role of hospitals after hazardous events requires the development of specific analysis and monitoring strategies aimed at quickly assessing their health conditions. Turning a hospital into a "Smart Health Facility" (SHF) allows remote assessment of the structural health; moreover, it can effectively support the mitigation of administrative and organizational vulnerability by acting on preparedness of the medical staff and supporting management and maintenance of structural as well as non-structural subsystems over time. Continuous monitoring of health and performance of hospitals can support the formulation of disaster mitigation plans and the definition of investment priorities to ensure the overall safety.In the present paper, some results of an on-going monitoring project for the main hospital in Campobasso (Southern Italy) are presented, focusing the attention on the response of the structure in operational conditions and after seismic events. Moreover, the results of experimental as well as operational modal analysis tests on a drug dispenser are discussed in order to assess their applicative perspectives for qualification of medical equipment in view of their seismic vulnerability assessment as non-structural elements.

Industrial Gas Turbine Health and Performance Assessment With Field Data

The paper presents a thorough analysis of the historical data and results acquired over a period of two years through an on-line real-time monitoring system installed at a combined heat and power (CHP) plant. For gas turbine health and performance assessment, a gas path analysis tool based on the adaptive modeling method is integrated into the system. An engine adapted model built through a semi-automated method is part of a procedure which includes a steam/water cycle simulation module and an economic module used for power plant performance and economic assessment. The adaptive modeling diagnostic method allowed for accurate health assessment during base and part load operation identifying and quantifying compressor recoverable deterioration and the root cause of an engine performance shift. Next, the performance and economic assessment procedure was applied for quantifying the economic benefit accrued by implementing daily on-line washing and for evaluating the financial gains if the off-line washings time intervals are optimized based on actual engine performance deterioration rates. The results demonstrate that this approach allows continuous health and performance monitoring at full and part load operation enhancing decision making capabilities and adding to the information that can be acquired through traditional analysis methods based on heat balance and base load correction curves.

Influenza A virus drift variants reduced the detection sensitivity of a commercial multiplex nucleic acid amplification assay in the season 2014/15.

The influenza season 2014/15 was dominated by drift variants of influenza A(H3N2), which resulted in a reduced vaccine effectiveness. It was not clear if the performance of commercial nucleic-acid-based amplification (NAT) assays for the detection of influenza was affected. The purpose of this study was to perform a real-life evaluation of two commercial NAT assays. During January-April 2015, we tested a total of 665 samples from patients with influenza-like illness using the Fast Track Diagnostics Respiratory pathogens 21, a commercial multiplex kit, (cohorts 1 and 2, n=563 patients) and the Xpert Flu/RSV XC assay (cohort 3, n=102 patients), a single-use cartridge system. An in-house influenza real-time RT-PCR (cohort 1) and the RealStar Influenza RT-PCR 1.0 Kit (cohort 2 and 3) served as reference tests. Compared to the reference assay, an overall agreement of 95.9% (cohort 1), 95% (cohort 2), and 98% (cohort 3) was achieved. A total of 24 false-negative results were observed using the Fast Track Diagnostics Respiratory pathogens 21 kit. No false-negative results occurred using the Xpert Flu/RSV XC assay. The Fast Track Diagnostics Respiratory pathogens 21 kit and the Xpert Flu/RSV XC assay had sensitivities of 90.7% and 100% and specificities of 100% and 94.1%, respectively, compared to the RealStar 1.0 kit. Upon modification of the Fast Track Diagnostics Respiratory pathogens 21 kit, the sensitivity increased to 97.3%. Influenza virus strains circulating during the 2014/15 season reduced the detection sensitivity of a commercial NAT assay, and continuous monitoring of test performance is therefore necessary.

Innovative Design of a Health Monitoring System and Its Implementation in a Complicated Long-Span Arch Bridge

AbstractThe implementation and operation of health monitoring systems in structures is an effective method of evaluating structural serviceability, reliability, safety, and integrity and providing economical maintenance and repair planning. This paper reports on an innovative structural health monitoring (SHM) system designed and permanently deployed on a complicated long-span arch bridge during its construction for the purpose of continuous performance monitoring throughout the bridge’s lifespan. The SHM system integrates several novel and practice-based concepts—i.e., life-cycle concerns for system design and implementation; newly designed high-performance sensors; flexible, modularized hardware and software; multilevel data management; multiscale condition evaluation; and reliable warning strategies. More than 300 sensors of 10 types are installed on the bridge with the aim of monitoring the environmental effects and structural responses. The innovative design and implementation of the monitoring syste...