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:
Dec. 13, 2022

Filed:

Jun. 02, 2020
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Dibyanshu Jaiswal, Kolkata, IN;

Debatri Chatterjee, Kolkata, IN;

Arijit Chowdhury, Kolkata, IN;

Rahul Gavas, Bangalore, IN;

Tanushree Banerjee, Kolkata, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/16 (2006.01); A61B 5/024 (2006.01); A61B 5/08 (2006.01); A61B 5/00 (2006.01);
U.S. Cl.
CPC ...
A61B 5/165 (2013.01); A61B 5/02416 (2013.01); A61B 5/0816 (2013.01); A61B 5/7267 (2013.01); A61B 5/7278 (2013.01); A61B 5/742 (2013.01);
Abstract

This disclosure relates generally to assessment of cognitive workload using breathing pattern of a person, where cognitive workload is the amount of mental effort required while doing a task. The method and system provides assessment of cognitive workload based on breathing pattern extracted from photoplethysmograph (PPG) signal, which is collected from the person using a wearable device. The PPG signal collected using the wearable device are processed in multiple stages that include breathing signal extraction to extract breathing pattern. The extracted breathing pattern is used for assessment of cognitive workload using a generated personalized training model, wherein the personalized training model is generated and dynamically updated for each person based on selection of a sub-set of breathing pattern features using feature selection and classification techniques that include maximal information coefficient (MIC) techniques. Finally based on personalized training model, the extracted breathing pattern is classified as high cognitive workload or low cognitive workload.


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