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Engineering of Trust Analysis-Driven Digital Twins for a Medical Device

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Software Architecture. ECSA 2022 Tracks and Workshops (ECSA 2022)

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Abstract

The DT paradigm has emerged as a suitable way to cope with the complexity of analyzing, controlling, and adapting complex systems in diverse domains. For medical systems, however, the DT paradigm is not fully exploited mainly due to the complexity of dealing with uncertain human behavior, and of preventing sensitive information leakage (e.g., patient personal medical profiles).

We present the first results of a long-term recently launched research aiming at engineering a DT for a medical device endowed with trust analyses techniques able to deal with human and environmental uncertainty, and security protection.

As a proof of concept, we apply our DT vision to the case study of a mechanical ventilator developed for Covid 19 patient care. The long-term aim is engineering a new generation of lung ventilators where the use of a DT can prevent unreliability and untrustworthiness of a system where interactions, both physical (machine-patient) and operational (machine-medical staff), are characterized by the presence of uncertainty and vulnerabilities.

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Notes

  1. 1.

    https://azure.microsoft.com/en-us/services/digital-twins/.

  2. 2.

    https://zeromq.org/.

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Acknowledgment

This work was partially supported by project SERICS (PE00000014) under the NRRP MUR program funded by the EU - NextGenerationEU.

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Authors and Affiliations

  1. Politecnico di Milano, Milano, Italy

    Marcello M. Bersani & Raffaela Mirandola

  2. Università degli Studi di Milano, Milano, Italy

    Chiara Braghin & Elvinia Riccobene

  3. Università degli Studi di Bergamo, Bergamo, Italy

    Angelo Gargantini & Patrizia Scandurra

Authors
  1. Marcello M. Bersani
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  2. Chiara Braghin
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  3. Angelo Gargantini
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  4. Raffaela Mirandola
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  5. Elvinia Riccobene
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  6. Patrizia Scandurra
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Corresponding author

Correspondence to Patrizia Scandurra .

Editor information

Editors and Affiliations

  1. Federal University of Rio Grande do Norte, Natal, Brazil

    Thais Batista

  2. Charles University, Prague, Czech Republic

    Tomáš Bureš

  3. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Claudia Raibulet

  4. University of L’Aquila, L’Aquila, Italy

    Henry Muccini

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Bersani, M.M., Braghin, C., Gargantini, A., Mirandola, R., Riccobene, E., Scandurra, P. (2023). Engineering of Trust Analysis-Driven Digital Twins for a Medical Device. In: Batista, T., Bureš, T., Raibulet, C., Muccini, H. (eds) Software Architecture. ECSA 2022 Tracks and Workshops. ECSA 2022. Lecture Notes in Computer Science, vol 13928. Springer, Cham. https://doi.org/10.1007/978-3-031-36889-9_31

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  • DOI: https://doi.org/10.1007/978-3-031-36889-9_31

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