ESR1: The concept of “EMI footprint” combine tests to obtain characteristic curves for the impact of a stand-alone device in an environment, with an additional statistical approach to combine extra reactions occurring within a complex medical scenario.
ESR2: Novel time-domain EMI measurements and analysis methods establishes the relationship between measurement results and the behaviors of DCS.
ESR3: Validation of a methodology for hazard identification in three medical case studies, ensuring their viable use in an industrial setting. It provides a broader perspective on system interactions, ultimately improving the risk assessment of electromagnetic interference and enabling more effective mitigation techniques.
ESR4 develops a risk-based EMC management framework tailored to hospital environments and the integration of proactive EMI mitigation strategies to enhance system resilience, resulting in safer and more reliable systems
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ESR5 proposes a methodology to optimize DCS in healthcare settings, where EMI can critically affect device performance, through adaptive algorithms and real-time EMI mitigation strategies.
ESR6 implemented a simulation-based evaluation of EMI in wireless systems as a tool to optimize transmission parameters on EMC resilient medical devices.
ESR 7 developed a defined methodology that includes characteristics of the environment aiding the risk assessment process. Especially the progress on the neural network models for EM field reconstruction is a new step in using artificial intelligence for EMC.
ESR8 implemented a novel predistortion-based methodology for immunity testing of medical equipment in complex EM environments which significantly reduces failures in medical systems, resulting in a positive social impact by improving patient safety.
ESR9 worked on the development of a real-time, frequency-selective EMD detector, enhancing EMC in medical devices, leading to more reliable healthcare applications and potential cost savings in system maintenance and compliance.
ESR10 enhanced advances in current EMC testing by integrating statistical evaluations of EMDs, bridging gaps in existing standards. It enhances medical device safety, reduces EMI risks in hospitals, and contributes to socio-economic benefits by improving healthcare reliability and patient outcomes.
ESR11 developed clinical workflow-oriented risk-based EMI management methodologies for healthcare environments, with qualitative and quantitative tools for EMI-induced risk assessment, leading to healthcare more accessible and affordable.
ESR12 developed and implemented a cumulative EMI risk analysis technique for automotive embedded systems, resulting in a more robust and EMI-resilient system design that can improve reliability and safety in automotive electronics.
ESR13 proposed new approaches for evaluating susceptibility of biomedical devices with techniques appropriate for SME’s to make safer devices. The implementation of these techniques in the development of new devices will promote a shorter time-to-market while ensuring compliance with EMC guidelines from an early stage.
ESR14 aims to create a convincing argument that medical devices are safe and effective when it comes to EMI. It will help people trust these devices more, which can have a positive social impact. Additionally, this research can help reduce the economic impact of EMC risks.