Electrocardiogram-based assessment of diastolic function
AssigneeHeart Test Laboratories, Inc.
InventorsAaron Peterson, Partho Sengupta, David Krubsack
Life of this patent
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Abstract
Diastolic function may be assessed by operating one or more machine-learned computational models on electrocardiograms or electrocardiogram-derived features to compute quantitative diastolic indicators, including estimates of echocardiography parameters conventionally measured by echocardiography. In various embodiments, parameters derived from time-frequency transforms of the electrocardiograms are used as input to the model(s) and/or computed within the model(s).
Claims20
A method for quantifying diastolic function, the method comprising:
- receiving one or more electrocardiograms measured for a patient;
- converting the one or more electrocardiograms, using time-frequency transform, into time-frequency features;
- operating one or more machine-learned computational models on input comprising the time-frequency features to compute an estimate or estimates of one or more echocardiogram parameters indicative of diastolic function, the one or more machine-learned computational models having been trained in a supervised manner using values of the one or more echocardiogram parameters obtained by echocardiography as ground-truth outputs.
A system comprising:
- one or more hardware processors;
- and
- memory storing instructions which, when executed by the one or more hardware processors, perform operations comprising:
- receiving one or more electrocardiograms measured for a patient;
- converting the one or more electrocardiograms, using time-frequency transform, into time-frequency features;
- operating one or more machine-learned computational models on input comprising the time-frequency features to compute an estimate or estimates of one or more echocardiogram parameters indicative of diastolic function, the one or more machine-learned computational models having been trained in a supervised manner using values of the one or more echocardiogram parameters obtained by echocardiography as ground-truth outputs.
A non-transitory computer-readable medium storing processor-executable instructions which, when executed by one or more computer processors, cause the one or more computer processors to perform operations comprising:
- receiving one or more electrocardiograms measured for a patient;
- converting the one or more electrocardiograms, using time-frequency transform, into time-frequency features;
- operating one or more machine-learned computational models on input comprising the time-frequency features to compute an estimate or estimates of one or more echocardiogram parameters indicative of diastolic function, the one or more machine-learned computational models having been trained in a supervised manner using values of the one or more echocardiogram parameters obtained by echocardiography as ground-truth outputs.
Dependencies are inferred from the claim text.