Prof Paul Stewart – University of Derby UK

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  • iTrend Intelligent Technologies for Renal Dialysis project publication roundup

    The content is about a compilation of all publications related to the MSTART-funded iTrend project. It emphasizes the availability of these publications for download, showcasing the progress and research outputs generated through the project. This collection serves as a resource for those interested in the findings and developments associated with iTrend.

  • Understanding Morbidity in Renal Dialysis Patients

    Renal dialysis patients (end-stage renal disease, ESRD) experience high rates of morbidity and mortality, with survival rates often significantly lower than the general population. The leading causes of morbidity and mortality are cardiovascular disease (CVD) and infection. Here are the major morbidity and comorbidity factors for renal dialysis patients:  1. Cardiovascular Disease (CVD) – The Leading…

  • Optimizing Blood Flow: Cardiorenal Device Perspectives

    Hemodynamics and fluid dynamics play essential roles in kidney and cardiac device design, impacting organ perfusion, hemolysis, and thrombosis risk. In cardiac devices such as MCS and LVADs, continuous flow can hinder the body’s pressure regulation. High shear stress from internal rotors may cause blood cell rupture and thrombosis, making CFD crucial for minimizing blood…

  • Miniaturizing Dialysis: Roadblocks and Innovations

    As of 2026, creating a wearable kidney remains a significant challenge because researchers are typically attempting to condense a room-sized dialysis infrastructure into a device small enough to be worn under clothing. While a few models have reached human trials, the following factors continue to delay widespread production:  1. Water Regeneration and Miniaturization  Traditional hemodialysis requires…

  • Understanding Sublethal RBC Damage in Dialysis

    Chronic sublethal damage to red blood cells (RBCs) significantly affects patients undergoing dialysis, reducing RBC lifespan from 100-120 days to approximately 58-65 days. This damage, resultant from non-physiological shear stress in dialysis machines, alters cell membranes and cytoskeletons without hemolysis, leading to premature filtration and chronic anemia. Contributing factors include device design, patient characteristics, and…

  • Optimizing SMR Layout with Genetic Algorithms

    The paper discusses optimizing module layouts for Small Modular Reactors (SMRs) using a genetic algorithm. By grouping components and arranging them efficiently, the study aims to minimize pipe length and reduce construction costs. Results indicate significant potential savings in time, materials, and cost, enhancing the overall feasibility of nuclear power plants.

  • Engineering Professors Council select iTrend project as a Case Study showcasing Engineering

    The iTrend project at the University of Derby addresses critical issues in improving care for end-stage renal disease (ESKD) patients undergoing dialysis, specifically targeting the estimated 40-45,000 annual premature deaths from chronic kidney disease in the UK. Key challenges include inadequate monitoring during dialysis, where traditional methods lack real-time insights leading to risks like intradialytic…

  • @Corpora.ai Generated Sequence Diagram of Data Flow and the Intervention Process in the iTrend Intelligent Technologies for Renal Dialysis Research Programme

    I am using @corpora.ai to support the documentation of the iTrend programme, which generated this excellent sequence diagram which demonstrates real-time sensing, analysis, clinician intervention, and personalized treatment adjustments, underpinning the integrated monitoring approach. I couldn’t have done better myself. Insight: Demonstrates real-time sensing, analysis, clinician intervention, and personalised treatment adjustments, underpinning the integrated monitoring approach.…

  • What are the key innovations of the iTrend Intelligent Technologies for Renal Dialysis project?

    The project focuses on non-invasive blood pressure monitoring in dialysis, leveraging advanced sensors and real-time data analysis since its inception in 2017. Key stakeholders include the University of Derby, University of Nottingham, and Royal Derby Hospital, collaborating on research and clinical trials. Machine learning algorithms are developed for predictive analytics, enhancing treatment safety by anticipating…

  • Understanding Micro EV Growth: Challenges and Innovations

    Strategic Outlook Micro EVs transition ownership from private to shared models, facilitated by technological advances, regulatory support, and innovative business models like Battery-as-a-Service (BaaS). Policy incentives and technological progress synergistically drove market adoption, prompting industry innovation and shifting ownership models towards shared/micro-ownership. The evolution of electric microcars is driven by advancements in battery technology, supportive…