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- Department Life Science Engineering (81) (remove)
This paper provides insight into how restricted data can be incorporated in an open-be-default-by-design digital infrastructure for scientific data. We focus, in particular, on the ethical component of FAIRER (Findable, Accessible, Interoperable, Ethical, and Reproducible) data, and the pseudo-anonymization and anonymization of COVID-19 datasets to protect personally identifiable information (PII). First we consider the need for the customisation of the existing privacy preservation techniques in the context of rapid production, integration, sharing and analysis of COVID-19 data. Second, the methods for the pseudo-anonymization of direct identification variables are discussed. We also discuss different pseudo-IDs of the same person for multi-domain and multi-organization. Essentially, pseudo-anonymization and its encrypted domain specific IDs are used to successfully match data later, if required and permitted, as well as to restore the true ID (and authenticity) in individual cases of a patient's clarification.Third, we discuss application of statistical disclosure control (SDC) techniques to COVID-19 disease data. To assess and limit the risk of re-identification of individual persons in COVID-19 datasets (that are often enriched with other covariates like age, gender, nationality, etc.) to acceptable levels, the risk of successful re-identification by a combination of attribute values must be assessed and controlled. This is done using statistical disclosure control for anonymization of data. Lastly, we discuss the limitations of the proposed techniques and provide general guidelines on using disclosure risks to decide on appropriate modes for data sharing to preserve the privacy of the individuals in the datasets.
New COVID-19 related instruments are being rapidly developed around the world to collect patient- and population-based information. Heterogeneity between instruments limits comparability of results. The present study provides an overview of instruments and resources. We scoped the content domain on a selection of instruments using the Maelstrom taxonomy. Content of the instruments varied widely, from proximal measures (e.g., clinical symptoms, comorbidities, etc.) to distal measures such as political attitudes. We recommend that researchers reuse existing instruments to the greatest extent possible, and that they make results openly available in machine-readable format to facilitate reuse and maximize comparability of results across studies and countries.
Certifying for Interoperability Update: EU Projekt Antilope, IHE Conformity Assessment Scheme Pilot
(2014)
Presentation of successful use of IHE profiles in national strategies (Austria and Switzerland)
(2019)
DEVELOPMENT AND EXTENSION OF A MODULAR, JAVA-BASED, 2ND GENERATION ISO/IEEE 11073 MANAGER FRAMEWORK
(2010)
Application of Functional Electrical Stimulation (FES) for training in Long-Term Space Flights
(2001)
The Research Data Alliance (RDA) COVID-19 Working Group members bring various, global expertise to develop a body of work that comprises how data from multiple disciplines inform response to a pandemic combined with guidelines and recommendations on data sharing under the present COVID-19 cicumstances. This extends to research software sharing, in recognition of the key role in software in analysing data. The work has been divided into four research areas (namely, clinical, omics, epidemiology, social sciences) with four cross cutting themes (namely, community participation, indigenous data, legal and ethical considerations, research software), as a way to focus the conversations, and provide an initial set of guidelines in a tight timeframe. The detailed guidelines are aimed to help stakeholders follow best practices to maximise the efficiency of their work, and to act as a blueprint for future emergencies. The recommendations in the document are aimed at helping policymakers and funders to maximise timely, quality data sharing and appropriate responses in such health emergencies.
This work was executed in an intense period over just over 6 weeks, with five iterations, all of which were opened for public community comment. Draft releases and comments are avaialable here (https://doi.org/10.15497/rda00046).
This activity has been conducted under the RDA guiding principles of Openness, Consensus, Balance, Harmonization, Community-driven, and Non-profit and technology-neutral.
LUMOR: An App for Standardized Control and Monitoring of a Porcine Lung and its Nutrient Cycle
(2014)
LUMOR: An App for Standardized Control and Monitoring of a Porcine Lung and its Nutrient Cycle
(2014)
Simulation models in respiratory research are increasingly used for medical product development and testing, especially because in-vivo models are coupled with a high degree of complexity and ethical concerns. This work introduces a respiratory simulation system, which is bridging the gap between the complex, real anatomical environment and the safe, cost-effective simulation methods. The presented electro-mechanical lung simulator, xPULM, combines in-silico, ex-vivo and mechanical respiratory approaches by realistically replicating an actively breathing human lung. The reproducibility of sinusoidal breathing simulations with xPULM was verified for selected breathing frequencies (10–18 bpm) and tidal volumes (400–600 ml) physiologically occurring during human breathing at rest. Human lung anatomy was modelled using latex bags and primed porcine lungs. High reproducibility of flow and pressure characteristics was shown by evaluating breathing cycles (nTotal = 3273) with highest standard deviation |3σ| for both, simplified lung equivalents (μV˙ = 23.98 ± 1.04 l/min, μP = −0.78 ± 0.63 hPa) and primed porcine lungs (μV˙ = 18.87 ± 2.49 l/min, μP = −21.13 ± 1.47 hPa). The adaptability of the breathing simulation parameters, coupled with the use of porcine lungs salvaged from a slaughterhouse process, represents an advancement towards anatomically and physiologically realistic modelling of human respiration.
Tele-rehabilitation at home is one of the promising approaches in increasing rehabilitative success and simultaneously decreasing the
financial burden on the healthcare system. Objectives: Novel and mostly mobile devices are already in use, but shall be used in the future to a higher extent for allowing at home rehabilitation processes at a high quality level. The combination of exercises, assessments and available equipment is the basic objective of the
presented database. Methods: The database has been structured in order to allow easy-to-use and fast access for the three main user groups. Therapists – looking for exercise and equipment combinations – patients – rechecking their tasks for home exercises – and manufacturers – entering their equipment for specific use cases.
Results: The database has been evaluated by a proof of concept study and shows a high degree of applicability for the field of rehabilitative medicine. Currently it contains 110 exercises/assessments and 111 equipment/systems. Conclusion: Foundations of presented database are already established in the rehabilitative field of application, but can and will be enhanced in its functionality to be usable for a higher variety of medical fields and specificatios.