"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates"
"uuid:06ffffc1-da1f-489b-86d6-a8dd4be79734","http://resolver.tudelft.nl/uuid:06ffffc1-da1f-489b-86d6-a8dd4be79734","Continuous Multimodal Monitoring of Neonates with a Congenital Diaphragmatic Hernia","Keulen, Bart (TU Delft Mechanical, Maritime and Materials Engineering; Erasmus MC)","Cochius - den Otter, Suzan (mentor); Gijsen, Frank (graduation committee); van Twist, Eris (graduation committee); Delft University of Technology (degree granting institution); Erasmus Universiteit Rotterdam (degree granting institution); Universiteit Leiden (degree granting institution)","2023","Introduction: Congenital diaphragmatic hernia (CDH) is a rare developmental defect of the diaphragm characterised by herniation of abdominal organs into the thoracic cavity during prenatal development. This herniation is usually accompanied by pulmonary hypertension (PH) and cardiac dysfunction (CD). Although several parameters are known to predict the clinical outcomes in CDH, most of these parameters do not monitor the degree of PH and CD and cannot be continuously measured. This retrospective observational trial aimed to monitor the degree of PH and CD in CDH using the oxygen saturation index (OSI), peripheral oxygen saturation (SpO2), heart rate (HR), heart rate variability (HRV), arterial blood pressure (ABP) and derivatives of these parameters.
Methods: the study population consisted of neonates admitted to the paediatric intensive care unit between 2019 and 2022 for treatment of CDH. The degree of PH and CD was determined for each cardiac ultrasound (CUS) performed. A 15-minute window of vital parameters, mechanical ventilator, and electrocardiogram data before each CUS was extracted to calculate the predictors. After preprocessing the data and meeting the statistical assumptions, both univariable and multivariable logistic mixed effects models were fitted and validated.
Results: in total, 136 CUS of 57 patients were included in the study. Of the univariable linear mixed-effects models, the median values of HR, pulse pressure (PP), preductal SpO2, dSpO2, OSI and the interquartile range (IQR) of HR were statistically significant predictors of PH. For the prediction of CD, this was the case for the power of HRV in the very low frequency band (HRV-VLF) and for the median values of HR, mean arterial pressure (MAP) and OSI. The multivariable model for the prediction of PH contained the median values of of dSpO2, HR, PP and OSI and the standard deviation of the normal-to-normal beat intervals (SDNN). The multivariable model for the prediction of CD included the median of dSpO2, HRV-VLF, SDNN and the IQR of the systolic arterial pressure (SAP) as predictors.
Conclusions: the most promising predictors are the median values of preductal SpO2, dSpO2 and OSI for the prediction of PH. For the prediction of CD, HRV-VLF and the median values of HR, OSI and dSpO2 were the most promising predictors. Despite limited predictive performance of the regression models, this study contributes to the improvement of monitoring of patients with CDH, which can lead to more timely interventions and eventually improved outcomes within this patient population.","Congenital Diaphragmatic Hernia; Continuous monitoring; Pulmonary hypertension; Cardiac dysfunction; Logistic mixed effect models; Multimodal monitoring; Paediatric Intensive Care Unit","en","master thesis","","","","","","","","","","","","Technical Medicine","",""
"uuid:b9ef4b8e-a18e-40cb-b222-a4221cb22431","http://resolver.tudelft.nl/uuid:b9ef4b8e-a18e-40cb-b222-a4221cb22431","Change Point Detection In Continuous Integration Performance Tests","van der Horst, Tim (TU Delft Electrical Engineering, Mathematics and Computer Science)","Langendoen, K.G. (mentor); Aniche, Maurício (graduation committee); Böhmer, Remy (graduation committee); Delft University of Technology (degree granting institution)","2021","Software testing is an integral part of the development of embedded systems. Among other reasons, tests are frequently used to ensure that a system meets all the specifications, which is especially important when designing systems for the medical industry. Software changes that have a detrimental impact on a real-time system's performance can accumulate until the systems no longer meet the required performance levels. At this point, fixing accumulated defects can become a costly and complex endeavor. The goal of this thesis is to create a method that can detect changes in performance metrics from a continuous integration pipeline with minimal manual intervention.
To achieve this goal, we have created a novel online, univariate change detection method, which consists of a diverse ensemble of more than 10 existing change detection algorithms. The ensemble is robust against changes in distribution and requires little tuning. The contributions of this work include the proposal of a generic architecture to combine both statistics and decisions from individual algorithms. Related work uses simple majority voting for decision fusion in the ensemble - we demonstrate that an ensemble can benefit from more complex decision fusion, for example using a Random Forest.
Synthetic data and a case study, using a dataset provided by Philips, are used to demonstrate that the overall ensemble is consistently able to outperform the individual algorithms in the ensemble. In addition, unlike the individual algorithms, the ensemble generalizes well to data that is not normally distributed and have not been encountered during training. Compared to the monitoring system for performance metrics that is currently being used by Philips, the ensemble is able to detect 75\% more changes with a 50\% lower false positive rate.","change detection; control chart; ensemble learning; multiple classifier systems; continuous monitoring; performance benchmarks","en","master thesis","","","","","","","","","","","","Electrical Engineering | Embedded Systems","",""
"uuid:9908701b-4d68-46d5-ac77-872ffd44ec86","http://resolver.tudelft.nl/uuid:9908701b-4d68-46d5-ac77-872ffd44ec86","Controlled reefers in the banana supply chain: energy reduction and quality preservation","Mees, H.O.","Negenborn, R.R. (mentor)","2017","Bananas are the fourth most eaten product in the world. In Europe almost 4 million tonnes of bananas are consumed every year. These bananas need to be imported from plantations in, among others, Latin America. Due to the perishable nature of bananas the transport from plantation to Europe is done in cooled reefer containers. During transport the considered ripening stage is the green life period because of its ability to be influenced by external factors. The ripening rate within the green life period is largely dependent on temperature. Energy consumption for cooling is dependent on temperature. The current cooling strategy is keeping temperatures as low as possible without damaging the bananas, which asks for maximum energy consumption. This article proposes a cooling strategy which results in higher temperatures inside the container with the goal to minimize energy consumption which ultimately results in lower transport costs. In this article a model is developed to combine biological and logistical features of the banana supply chain. To assure right quality, continuous monitoring inside a reefer is used to check the ripening process and detect disturbances in ripening rate. To cope with the disturbances and delays in the supply chain a controller is designed which can adjust temperature during the journey. This is done to adjust the ripening rate and make sure the bananas reach the customer at the right quality at the right time while using up to 10% less energy than conventional cooling strategies.","Banana supply chain; green life; energy reduction; continuous monitoring; system and control","en","master thesis","","","","","","","","","Mechanical, Maritime and Materials Engineering","Marine and Transport Technology","","","",""
"uuid:4a9569c2-1299-491f-b266-10ca9b18c376","http://resolver.tudelft.nl/uuid:4a9569c2-1299-491f-b266-10ca9b18c376","CSO pollution analysis based on conductivity and turbidity measurements and implications for application of RTC","Rombouts, P.M.M.; Schilperoort, R.; Langeveld, J.G.; Clemens, F.H.L.R.","","2013","The objective of this paper is to demonstrate the applicability of, and need for, surrogate sensors as robust sensors for water quality based RTC. For this purpose 1.5 years of level, conductivity (EC) and turbidity (TU) measurements at 9 combined sewer overflow (CSO) locations have been performed and analysed to determine the most polluted CSO locations. The analysis is based on surrogate event mean concentrations (sEMC, defined as EC multiplied by TU) and surrogate pollution loads (sPL, defined as the sEMC multiplied by the overflow volume). It is shown that EC and TU measurements can serve as surrogate measurements to determine the relative pollution of a CSO location. Analysis of the EC and TU values with respect to the distance between the CSO location and the WWTP gave no indication that this is of importance. Comparison of the sEMC and sPL for the CSO locations, shows that water quality measurements will have a great impact on the application of RTC, leading to quality based RTC.","Conductivity, Continuous monitoring, CSO, Quality based real time control, Turbidity","en","conference paper","s.n.","","","","","","","","Civil Engineering and Geosciences","Water Management","","","",""
"uuid:02d7988d-baf2-4c30-8396-4c21526d253e","http://resolver.tudelft.nl/uuid:02d7988d-baf2-4c30-8396-4c21526d253e","Determining the transition between DWF and WWF based on water quality measurements","van Daal-Rombouts, P.M.M. (TU Delft Sanitary Engineering; Witteveen+Bos); Langeveld, J.G. (TU Delft Sanitary Engineering; Royal HaskoningDHV); Clemens, F.H.L.R. (TU Delft Sanitary Engineering; Deltares)","","2013","","conductivity; continuous monitoring; dry weather flow; turbidity; wet weather flow","en","conference paper","","","","","","","","","","","Sanitary Engineering","","",""