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:
May. 18, 2021

Filed:

Mar. 30, 2018
Applicant:

Intel Corporation, Santa Clara, CA (US);

Inventors:

Cagri Tanriover, Bethany, OR (US);

Nese Alyuz Civitci, Hillsboro, OR (US);

Asli Arslan Esme, Istanbul, TR;

Hector Cordourier, Guadalajara, MX;

Paulo Lopez Meyer, Zapopan, MX;

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/08 (2006.01); A61B 5/16 (2006.01); A61B 5/00 (2006.01); G16H 50/20 (2018.01); G16H 40/63 (2018.01); G16H 20/70 (2018.01); G16H 40/67 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
A61B 5/165 (2013.01); A61B 5/0022 (2013.01); A61B 5/0816 (2013.01); A61B 5/4011 (2013.01); A61B 5/6803 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); A61B 5/7278 (2013.01); G16H 20/70 (2018.01); G16H 40/63 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01);
Abstract

Technologies for emotion prediction based on breathing patterns include a wearable device. The wearable device includes a breathing sensor to generate breathing data, one or more processors, and one or more memory devices having stored therein a plurality of instructions that, when executed, cause the wearable device to calibrate a personalized emotion predictive model associated with the user, collect breathing data of the user of the wearable device, analyze the breathing data to determine a breathing pattern, predict, in response to an analysis of the breathing data, the emotional state of the user using the personalized emotion predictive model, and output the emotional state of the user.


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