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Non-invasive method and system for characterizing cardiovascular systems

  • US 10,362,951 B2
  • Filed: 04/24/2018
  • Issued: 07/30/2019
  • Est. Priority Date: 08/17/2012
  • Status: Active Grant
First Claim
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1. A method of pre-processing data to extract variables for use in a machine learning operation to diagnose a pathology, the method comprising:

  • receiving a biopotential signal data set associated with a subject, said biopotential signal data set being associated with a biopotential signal collected from one or more electrical leads;

    generating, via a processor, an estimated noiseless model of the received biopotential signal data set, wherein generation comprises iterative selection of member atoms of a pre-defined dictionary of member atoms to form a sparse approximation of the received biopotential signal data set;

    extracting, via the processor, a plurality of features from a low-energy complex sub-harmonic subspace derived from the estimated noiseless model, wherein one or more of the plurality of extracted features includes one or more fractional derivative derived features of the low-energy complex sub-harmonic subspace; and

    linking, via the processor, the one or more of the plurality of extracted features to a genetic algorithm to generate outputs that correlate with clinical parameters describing tissue architecture, structure and/or function.

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