Periodic Reporting for period 2 - ETERNITY (European Training Network on Electromagnetic Risks in Medical Technology)
Reporting period: 2023-03-01 to 2025-02-28
Electromagnetic interference (EMI) is a growing concern also in the medical-technology industry, as it can disrupt communications and pose risks to patients, especially with life-support systems. The Blue Guide, which outlines EU product rules, has made a risk-based approach to EMI mandatory for new equipment. However, many companies, small and medium-sized enterprises (SMEs) and users in the industry, including hospitals, are struggling with this approach due to a lack of understanding and clear risk-assessment methodology. ETERNITY project aims to create a multidisciplinary network for doctoral training, involving leading industries and academia, to address EMI risks in the design of innovative medical equipment such as wearables, on-board platforms, and collaborative care systems for hospitals. The goals of ETERNITY include proposing solutions to scientific challenges, training young pioneers in electronic design for medical technology, building an industry-academia network, and enabling safe and reliable medical equipment innovation in various environments.
ESR 1 raised attention to the use of reverberation chambers as a fast and cost-effective method for radiated emission measurements above 1 GHz, and conducted experimental investigations into the risk-based EMI footprint of a MedTech product.
ESR 2 Characterized EMD in healthcare with predictive models and EMC guidelines. Identified and mitigated DCS disturbance in hospital rehab rooms.
ESR 3 applied a systems thinking approach using systems-theoretic process analysis to address electromagnetic (EM) interference hazards, and developed adaptive decision-making algorithms to improve decision-making in uncertain EM environments
ESR 4 applied multidisciplinary approach with zoning-based methods to identify and mitigate EMI risks, enhancing hospital safety, medical system resilience, and compliance with international standards.
ESR 5 carried out the identification of the various digital systems that operate in harsh EM environments and the analysis of the radio communication link in the presence of transient interference.
ESR 6 modeled communication links subject to broadband and narrowband disturbances to predict reception quality degradation.
ESR 7 worked on a new methodology to characterize EM field behavior. The main results obtained are on sampling strategies and usage of neural network models .
ESR8 enhanced immunity testing methodologies for medical equipment in complex EM environments and developed an approach using signal predistortion to mitigate nonlinear distortion effects, specifically in the testing process for immunity.
ESR9 focused on developing a frequency-selective electromagnetic disturbance detector using software-defined radio technology and successfully demonstrated its ability to detect unwanted EMDs with improved probability of interception, precision, and response time.
ESR10 focused on developing statistical testing methodologies for electromagnetic compatibility in dense electromagnetic environments. The outcomes include new emission testing methods for statistically evaluating electromagnetic disturbances.
ESR11 developed qualitative and quantitative methods to characterize disturbances and EMI-induced risks in healthcare environments, a clinical workflow-oriented risk-based EMC approach, and created tools for EM environment characterization.
ESR12 developed a cumulative EMI risk analysis technique for automotive embedded systems and a methodology to assess the EMI risks at both the system and component levels.
ESR13 evaluated the EM susceptibility of electrodes of different materials and demonstrated the influence of the material chose during manufacturing of electrodes in the signal integrity.
ESR14 worked on graphical representations to make easier to to ease the understanding on medical devices can be protected against EMI towards more resilience.
ESR 2 Characterized EMD in healthcare with predictive models and EMC guidelines. Identified and mitigated DCS disturbance in hospital rehab rooms.
ESR 3 applied a systems thinking approach using systems-theoretic process analysis to address electromagnetic (EM) interference hazards, and developed adaptive decision-making algorithms to improve decision-making in uncertain EM environments
ESR 4 applied multidisciplinary approach with zoning-based methods to identify and mitigate EMI risks, enhancing hospital safety, medical system resilience, and compliance with international standards.
ESR 5 carried out the identification of the various digital systems that operate in harsh EM environments and the analysis of the radio communication link in the presence of transient interference.
ESR 6 modeled communication links subject to broadband and narrowband disturbances to predict reception quality degradation.
ESR 7 worked on a new methodology to characterize EM field behavior. The main results obtained are on sampling strategies and usage of neural network models .
ESR8 enhanced immunity testing methodologies for medical equipment in complex EM environments and developed an approach using signal predistortion to mitigate nonlinear distortion effects, specifically in the testing process for immunity.
ESR9 focused on developing a frequency-selective electromagnetic disturbance detector using software-defined radio technology and successfully demonstrated its ability to detect unwanted EMDs with improved probability of interception, precision, and response time.
ESR10 focused on developing statistical testing methodologies for electromagnetic compatibility in dense electromagnetic environments. The outcomes include new emission testing methods for statistically evaluating electromagnetic disturbances.
ESR11 developed qualitative and quantitative methods to characterize disturbances and EMI-induced risks in healthcare environments, a clinical workflow-oriented risk-based EMC approach, and created tools for EM environment characterization.
ESR12 developed a cumulative EMI risk analysis technique for automotive embedded systems and a methodology to assess the EMI risks at both the system and component levels.
ESR13 evaluated the EM susceptibility of electrodes of different materials and demonstrated the influence of the material chose during manufacturing of electrodes in the signal integrity.
ESR14 worked on graphical representations to make easier to to ease the understanding on medical devices can be protected against EMI towards more resilience.
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
.
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.
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
.
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.