IP Library Granted Patent US 12,230,060
Granted Patent B2
US 12,230,060 · App. 17/794,748 · Granted Feb 18, 2025

System and method for determining human emotions

Inventors: Kanat Sultanbekov (New York, NY); Viktor Ivanov (Moscow, RU)
Assignee: Gleenr Inc.
G06V40/174A61B5/0261G06V40/193
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,230,060
App. No.
17/794,748
Granted
Feb 18, 2025
Kind
B2
Abstract

The present invention provides a system and method for determining human emotions. The system includes an input device for receiving at least one image of a human face and at least one processor for: processing the at least one image to generate a heat map of the at least one image as a first identifying data; processing the heat map to generate a second identifying data relating to emotional conditions based on heat; processing the at least one image to generate a third identifying data relating to emotional conditions based on muscle movement; and processing the at least one image to generate a fourth identifying data relating to truthfulness. The first, second, third and fourth identifying data are then collectively processed to generate a final emotion identifier for display on an output device.

Claims (45)

1. A system comprising:

an input device for receiving at least one image of a human face;

a transdermal imaging processor, executing at least one predetermined software application, for processing the at least one image by: mapping topography of blood vessels and muscles underlying exposed skin and tissues of the human face based on light reflected in the at least one image, applying a digital monochrome filter to remove red, green and blue colors from the at least one image to determine hemoglobin movement intensity, and applying a digital heat filter to generate a heat map of the at least one image as a first identifying data;

a heat map processor, executing the at least one predetermined software application, for processing the heat map by comparing the heat map with an emotional condition database to generate a second identifying data, wherein the emotional condition database comprises a plurality of predetermined emotional conditions corresponding to respective predetermined heat patterns of a human;

a facial muscle processor, executing the at least one predetermined software application, for processing the at least one image by comparing the at least one image with a motion unit database to generate a third identifying data, the motion unit database comprising a plurality of predetermined motion units corresponding to respective predetermined motion unit numbers, and predetermined degrees of intensity;

an oculomotor reaction processor, executing the at least one predetermined software application, for processing the at least one image by comparing the at least one image with an oculomotor database to generate a fourth identifying data, the oculomotor database comprising a plurality of oculomotor parameters corresponding to respective oculomotor characteristics to determine a characteristic of truthfulness;

a main processor, executing the at least one predetermined software application, for receiving and processing the first, second, third and fourth identifying data, and generating a final emotion identifier; and

an output device for receiving and displaying the final emotion identifier.

2. The system of claim 1 , further comprising an image processor, executing the at least one predetermined software application, for processing the at least one image captured by video and generating at least one static image.

3. The system of claim 1 , wherein the plurality of emotional conditions is selected from a group comprising: anger, fear, aversion, happiness, sorrow, wonder, tranquility, anxiety, love, depression, contempt, pride, shame and envy.

4. The system of claim 1 , wherein the motion units are movements on a human face and a human head.

5. The system of claim 1 , wherein the motion unit database further comprises predetermined emotional conditions corresponding to predetermined patterns based on combinations of motion unit numbers and degrees of intensity.

6. The system of claim 1 , wherein the oculomotor characteristics are characteristics and movements of a human eye.

7. A method comprising the steps of:

capturing at least one image of a human face with an input device;

executing at least one predetermined software application using a transdermal imaging processor for processing the at least one image by: mapping topography of blood vessels and muscles underlying exposed skin and tissues of the human face based on light reflected in the at least one image, applying a digital monochrome filter to remove red, green and blue colors from the at least one image to determine hemoglobin movement intensity, and applying a digital heat filter to generate a heat map of the at least one image as a first identifying data;

executing the at least one predetermined software application using a heat map processor for processing the heat map by comparing the heat map with an emotional condition database to generate a second identifying data, wherein the emotional condition database comprises a plurality of predetermined emotional conditions corresponding to respective predetermined heat patterns of a human;

executing the at least one predetermined software application using a facial muscle processor for processing the at least one image by comparing the at least one image with a motion unit database to generate a third identifying data, the motion unit database comprising a plurality of predetermined motion units corresponding to respective predetermined motion unit numbers, and predetermined degrees of intensity;

executing the at least one predetermined software application using an oculomotor reaction processor, for processing the at least one image by comparing the at least one image with an oculomotor database to generate a fourth identifying data, the oculomotor database comprising a plurality of oculomotor parameters corresponding to respective oculomotor characteristics to determine a characteristic of truthfulness;

executing the at least one predetermined software application using a main processor for receiving and processing the first, second, third and fourth identifying data, and generating a final emotion identifier; and

receiving and displaying the final emotion identifier on an output device.

8. The method of claim 7 , wherein the at least one image is captured by video.

9. The method of claim 8 , further comprising the step of executing the at least one predetermined software application using an image processor for processing the at least one image captured by video and generating at least one static image.

10. The method of claim 7 , wherein the plurality of emotional conditions is selected from a group comprising: anger, fear, aversion, happiness, sorrow, wonder, tranquility, anxiety, love, depression, contempt, pride, shame and envy.

11. The method of claim 7 , wherein the motion units are movements on a human face and a human head.

12. The method of claim 7 , wherein the motion unit database further comprises predetermined emotional conditions corresponding to predetermined patterns based on combinations of motion unit numbers and degrees of intensity.

13. The method of claim 7 , wherein the oculomotor characteristics are characteristics and movements of a human eye.

14. A non-transitory computer readable medium storing instructions executable by a processor, the stored instructions implementing a method comprising the steps of:

receiving, at an input device, at least one image of a human face;

executing, by a processor, a predetermined program for determining human emotions by:

processing the at least one image by: mapping topography of blood vessels and muscles underlying exposed skin and tissues of the human face based on light reflected in the at least one image, applying a digital monochrome filter to remove red, green and blue colors from the at least one image to determine hemoglobin movement intensity, and applying a digital heat filter to generate a heat map of the at least one image as a first identifying data,

processing the heat map by comparing the heat map with an emotional condition database to generate a second identifying data, wherein the emotional condition database comprises a plurality of predetermined emotional conditions corresponding to respective predetermined heat patterns of a human,

processing the at least one image by comparing the at least one image with a motion unit database to generate a third identifying data, the motion unit database comprising a plurality of predetermined motion units corresponding to respective predetermined motion unit numbers, and predetermined degrees of intensity,

processing the at least one image by comparing the at least one image with an oculomotor database to generate a fourth identifying data, the oculomotor database comprising a plurality of oculomotor parameters corresponding to respective oculomotor characteristics to determine a characteristic of truthfulness, and

receiving and processing the first, second, third and fourth identifying data, and generating a final emotion identifier; and

outputting, at an output device, the final emotion identifier.

15. The non-transitory computer readable medium of claim 14 , wherein the at least one image is captured by video.

16. The non-transitory computer readable medium of claim 15 , further comprising the step of processing the at least one image captured by video and generating at least one static image.

17. The non-transitory computer readable medium of claim 15 , wherein the plurality of emotional conditions is selected from a group comprising: anger, fear, aversion, happiness, sorrow, wonder, tranquility, anxiety, love, depression, contempt, pride, shame and envy.

18. The non-transitory computer readable medium of claim 15 , wherein the motion units are movements on a human face and a human head.

19. The non-transitory computer readable medium of claim 15 , wherein the motion unit database further comprises predetermined emotional conditions corresponding to predetermined patterns based on combinations of motion unit numbers and degrees of intensity.

20. The non-transitory computer readable medium of claim 15 , wherein the oculomotor characteristics are characteristics and movements of a human eye.

21. The system of claim 1 , wherein the input device is non-wearable.

22. The method of claim 7 , wherein the input device is non-wearable.

23. The non-transitory computer readable medium of claim 14 , wherein the input device is non-wearable.

Assignments (2)
CORRECTIVE ASSIGNMENT TO CORRECT THE THE APPLICATION NUMBER PREVIOUSLY RECORDED AT REEL: 66406 FRAME: 268. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Feb 15, 2024
From: GLEENR APP INC.
To: GLEENR INC.
Reel/Frame 066601/0161 →
CHANGE OF NAME Recorded Feb 1, 2024
From: UTEST APP INC.
To: GLEENR APP INC.
Reel/Frame 066405/0722 →
Continuity (2)
Provisional Application 62964776 · Jan 23, 2020
Related Publication 20230111692A1 · Apr 13, 2023
References Cited (7)
US 10117588B2 · Lee et al. · 2018 [cited by applicant]
US 10376192B2 · Lee et al. · 2019 [cited by applicant]
US 10694988B2 · Lee et al. · 2020 [cited by applicant]
US 20160098592A1 · Lee · 2016 [cited by examiner]
US 20160360970A1 · Tzvieli et al. · 2016 [cited by applicant]
US 20190384392A1 · Aimone · 2019 [cited by examiner]
ISA/US, International Search Report and Written Opinion, PCT/US21/14536, Mar. 31, 2021. [cited by applicant]