US 11,948,688 B2
Method and system to assess disease using phase space volumetric objects
Sunny Gupta, Belleville, CA (US); Timothy William Fawcett Burton, Toronto (CA); and Shyamlal Ramchandani, Kingston (CA)
Assigned to Analytics for Life Inc., Toronto (CA)
Filed by Analytics For Life Inc., Toronto (CA)
Filed on Sep. 10, 2021, as Appl. No. 17/472,353.
Application 17/472,353 is a division of application No. 16/232,801, filed on Dec. 26, 2018, granted, now 11,133,109.
Claims priority of provisional application 62/611,826, filed on Dec. 29, 2017.
Prior Publication US 2022/0139555 A1, May 5, 2022
Int. Cl. G16H 50/20 (2018.01); A61B 5/00 (2006.01); A61B 5/02 (2006.01); A61B 5/0265 (2006.01)
CPC G16H 50/20 (2018.01) [A61B 5/02007 (2013.01); A61B 5/0265 (2013.01); A61B 5/40 (2013.01); A61B 5/726 (2013.01); A61B 5/7282 (2013.01)] 20 Claims
OG exemplary drawing
 
9. A system comprising:
a processor; and
a memory having instructions thereon, wherein the instructions, when executed by the processor, cause the processor to:
obtain data acquired from a measurement of one or more biopotential signals of a subject, wherein the acquired data comprises a high-frequency time series data having a frequency component greater than about 1 kHz and less than about 10 kHz, wherein the acquired data is derived from measurements acquired via non-invasive equipment configured to measure properties of the heart;
generate one or more phase space volumetric objects based on the acquired data, wherein at least one of the one or more phase space volumetric objects comprises a plurality of faces and a plurality of vertices, wherein the plurality of vertices are determined by subtracting data points of a base-line raw channel data set of the acquired data with corresponding data points of a modeled channel data set, wherein the modeled channel data set is generated from a model-derived reconstruction operation of the acquired data to generate low-energy subspace parameters; and
determine, using a machine-learned based classifier, (i) a parameter associated with a presence, absence, or degree of significant coronary artery disease or (ii) one or more coronary physiological parameters of the subject selected from the group consisting of a fractional flow reserve estimation, a stenosis value, and a myocardial ischemia estimation, based on the generated phase space volumetric object.