NON-INVASIVE METHODS APPLIED FOR COMPLEX SIGNALS

This paper presents the application of a novel algorithm on virtually generated data from patients during anesthesia. Realistic artefacts are simulated in order to validate the usefulness of the proposed methods in separating the signal components: biological trend and artefacts. The results show that the proposed new algorithm can be successfully employed on biological signals to dynamically extract information and distil useful parameters for clinical evaluation.

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