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Anomaly detection for interoperable and modular operating room tables
Andreas Puder
2025
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Technologies that enable connectivity, interoperability and automation have the potential to increase the quality and efficiency of patient care. In this dissertation, the necessary adaptations to the software and E/E architectures of medical devices are examined using the example of operating tables. In addition, a special focus is placed on anomaly detection, for which a novel approach is presented that uses hybrid plausibility checks that combine data- and model-based algorithms.
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Keywords
- Anomalie-Erkennung
- anomaly detection
- E/E architecture
- E/E-Architektur
- Kalman filter
- Kalman-Filter
- Machine learning
- Maschinelles Lernen
- medical devices
- Medizinische Geräte
- Safety
- security
- Sicherheit
- SOA
- Software architecture
- Softwarearchitektur
Links
DOI: 10.5445/KSP/1000179373Editions