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:
Feb. 16, 2021

Filed:

May. 09, 2018
Applicant:

Affectiva, Inc., Boston, MA (US);

Inventors:

Rana el Kaliouby, Milton, MA (US);

Abdelrahman N. Mahmoud, Somerville, MA (US);

Seyedmohammad Mavadati, Watertown, MA (US);

Panu James Turcot, Pacifica, CA (US);

Assignee:

Affectiva, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); A61B 5/00 (2006.01); G06K 9/46 (2006.01); G16H 50/20 (2018.01); G06N 3/08 (2006.01); B60W 50/14 (2020.01); G06N 5/04 (2006.01); B60W 50/08 (2020.01); A61B 5/18 (2006.01); A61B 5/16 (2006.01); G06K 9/62 (2006.01); A61B 5/11 (2006.01); A61B 5/107 (2006.01); G16H 30/40 (2018.01); G06N 3/04 (2006.01); G16H 50/30 (2018.01); G06N 3/02 (2006.01); A61B 5/024 (2006.01); A61B 5/0531 (2021.01); A61B 5/01 (2006.01); A61B 5/08 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00845 (2013.01); A61B 5/1079 (2013.01); A61B 5/1128 (2013.01); A61B 5/165 (2013.01); A61B 5/18 (2013.01); A61B 5/6893 (2013.01); A61B 5/7267 (2013.01); A61B 5/746 (2013.01); B60W 50/082 (2013.01); B60W 50/14 (2013.01); G06K 9/00228 (2013.01); G06K 9/00302 (2013.01); G06K 9/00369 (2013.01); G06K 9/4628 (2013.01); G06K 9/627 (2013.01); G06N 3/0454 (2013.01); G06N 3/084 (2013.01); G06N 5/046 (2013.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 5/0022 (2013.01); A61B 5/01 (2013.01); A61B 5/02405 (2013.01); A61B 5/02416 (2013.01); A61B 5/0531 (2013.01); A61B 5/0816 (2013.01); A61B 5/4266 (2013.01); A61B 2503/22 (2013.01); A61B 2576/00 (2013.01); B60W 2050/143 (2013.01); G06N 3/02 (2013.01);
Abstract

Disclosed embodiments provide cognitive state evaluation for vehicle navigation. The cognitive state evaluation is accomplished using a computer, where the computer can perform learning using a neural network such as a deep neural network (DNN) or a convolutional neural network (CNN). Images including facial data are obtained of a first occupant of a first vehicle. The images are analyzed to determine cognitive state data. Layers and weights are learned for the deep neural network. Images of a second occupant of a second vehicle are collected and analyzed to determine additional cognitive state data. The additional cognitive state data is analyzed, and the second vehicle is manipulated. A second imaging device is used to collect images of a person outside the second vehicle to determine cognitive state data. The second vehicle can be manipulated based on the cognitive state data of the person outside the vehicle.


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