The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 15, 2019

Filed:

Mar. 20, 2018
Applicant:

Analytics for Life, Ganaoque, CA;

Inventors:

Timothy Burton, Ottawa, CA;

Shyamlal Ramchandani, Kingston, CA;

Matthew Howe-Patterson, Ottawa, CA;

Mohsen Yazdi, Montreal, CA;

Sunny Gupta, Amherstview, CA;

Assignee:

ANALYTICS FOR LIFE INC., Toronto, ON, CA;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A61B 5/04 (2006.01); A61B 5/0402 (2006.01); A61B 5/0468 (2006.01); A61B 5/00 (2006.01); G16H 50/50 (2018.01); A61B 5/02 (2006.01); G06F 19/00 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A61B 5/4848 (2013.01); A61B 5/02028 (2013.01); A61B 5/0402 (2013.01); A61B 5/04011 (2013.01); A61B 5/04012 (2013.01); A61B 5/0468 (2013.01); A61B 5/681 (2013.01); A61B 5/6804 (2013.01); A61B 5/7264 (2013.01); A61B 5/7275 (2013.01); G06F 19/00 (2013.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); A61B 5/7203 (2013.01); A61B 5/7267 (2013.01);
Abstract

Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.


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