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. 18, 2022

Filed:

Oct. 24, 2018
Applicant:

Nuralogix Corporation, Toronto, CA;

Inventors:

Kang Lee, Toronto, CA;

Pu Zheng, North York, CA;

Si Wu, Newmarket, CA;

Assignee:

NURALOGIX CORPORATION, Toronto, CA;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); A61B 5/16 (2006.01); G16H 50/20 (2018.01); A61B 5/318 (2021.01); A61B 5/00 (2006.01); A61B 5/024 (2006.01); A61B 5/145 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
A61B 5/165 (2013.01); A61B 5/0077 (2013.01); A61B 5/02405 (2013.01); A61B 5/14546 (2013.01); A61B 5/318 (2021.01); A61B 5/7246 (2013.01); A61B 5/7257 (2013.01); A61B 5/7267 (2013.01); G06N 3/08 (2013.01); G16H 50/20 (2018.01);
Abstract

A system and method for camera-based stress determination. The method includes: determining a plurality of regions-of-interest (ROIs) of a body part; determining a set of bitplanes in a captured image sequence for each ROI that represent HC changes using a trained machine learning model, the machine learning model trained with a hemoglobin concentration (HC) changes training set, the HC changes training set trained using bitplanes from previously captured image sequences of other human individuals as input and received cardiovascular data as targets; determining an HC change signal for each of the ROIs based on changes in the set of determined bitplanes; for each ROI, determining intervals between heartbeats based on peaks in the HC change signal; determining heart rate variability using the intervals between heartbeats; determining a stress level using at least one determination of a standard deviation of the heart rate variability; and outputting the stress level.


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