Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models
Andreas Puder,
Moritz Zink,
Luca Seidel
et al.
Abstract:Due to connectivity and automation trends, the medical device industry is experiencing increased demand for safety and security mechanisms. Anomaly detection has proven to be a valuable approach for ensuring safety and security in other industries, such as automotive or IT. Medical devices must operate across a wide range of values due to variations in patient anthropometric data, making anomaly detection based on a simple threshold for signal deviations impractical. For example, surgical robots directly conta… Show more
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