IP Library › Granted Patent US 12,147,514
Granted Patent B2
US 12,147,514 · App. 17/567,530 · Granted Nov 19, 2024

Method and system for providing a brain computer interface

Inventors: Daniel Furman (San Francisco, CA); Eitan Kwalwasser (Tel Aviv, IL)
Assignee: Arctop LTD
G06F21/32G06F3/015G06F21/34G06N3/045G06N3/08G06N3/084G06N3/088G06N20/10G06N20/20G06N3/044G06N3/047G06N3/126G06N5/01G06N5/025G06N5/048G06N7/01
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Quick Facts
Patent No.
US 12,147,514
App. No.
17/567,530
Granted
Nov 19, 2024
Kind
B2
Abstract

A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Claims (57)

1. A method for authenticating a user with a brain computer interface comprising:

training, in a first time window, a calibration model comprising:

providing a first series of stimuli to the user from the brain computer interface;

measuring a first set of neural signals of the user including responses to the first series of stimuli;

extracting features from the first set of neural signals that temporally align with the first series of stimuli; and

training the calibration model with the features and the first series of stimuli;

receiving, in a second time window, an input from the user to perform an action with the brain computer interface;

in response to the input, performing a verification session comprising:

providing a second series of stimuli to the user from the brain computer interface, wherein the second series of stimuli includes at least one stimulus that is different from the first series of stimuli;

measuring a second set of neural signals of the user during the second time window, wherein the second set of neural signals includes responses to the second series of stimuli and a response to at least one free-form event of an imagined stimulus not part of the second series of stimuli; and

applying the calibration model to the second set of neural signals to authenticate the user; and

in response to authenticating the user, performing the action in the input from the user.

2. The method of claim 1 , wherein the brain computer interface is one of a headset or a head-mounted wearable device.

3. The method of claim 1 , wherein the second series of stimuli includes an auditory stimulus.

4. The method of claim 3 , wherein the auditory stimulus includes one or more of a music sample, a speech sample, or a cacophonous sound sample.

5. The method of claim 3 , wherein the auditory stimulus is an audio sample including between 5% and 30% randomization factor in comparison to an un-modified version of the audio sample.

6. The method of claim 1 , wherein performing the action comprises providing personalized digital content to the user.

7. The method of claim 1 , wherein performing the action comprises at least one of: delivering digital content and adjusting operation of a user device in coordination with detection of a brain state of the user.

8. The method of claim 1 , wherein performing the action comprises populating a password in an input box.

9. A non-transitory computer-readable medium comprising instructions for authenticating a user with a brain computer interface, the instructions, when executed by a computing system, causing the computing system to perform operations including:

training, in a first time window, a calibration model comprising:

providing a first series of stimuli to the user from the brain computer interface;

measuring a first set of neural signals of the user including responses to the first series of stimuli;

extracting features from the first set of neural signals that temporally align with the first series of stimuli; and

training the calibration model with the features and the first series of stimuli;

receiving, in a second time window, an input from the user to perform an action with the brain computer interface;

in response to the input, performing a verification session comprising:

providing a second series of stimuli to the user from the brain computer interface, wherein the second series of stimuli includes at least one stimulus that is different from the first series of stimuli;

measuring a second set of neural signals of the user during the second time window, wherein the second set of neural signals includes responses to the second series of stimuli and a response to at least one free-form event of an imagined stimulus not part of the second series of stimuli; and

applying the calibration model to the second set of neural signals to authenticate the user; and

in response to authenticating the user, performing the action in the input from the user.

10. The non-transitory computer-readable medium of claim 9 , wherein the brain computer interface is one of a headset or a head-mounted wearable device.

11. The non-transitory computer-readable medium of claim 9 , wherein the second series of stimuli includes an auditory stimulus.

12. The non-transitory computer-readable medium of claim 11 , wherein the auditory stimulus includes one or more of a music sample, a speech sample, or a cacophonous sound sample.

13. The non-transitory computer-readable medium of claim 9 , wherein performing the action comprises populating a password in an input box.

14. A system for authenticating a user with a brain computer interface comprising:

at least one processor; and

a non-transitory computer readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including:

training, in a first time window, a calibration model comprising:

providing a first series of stimuli to the user from the brain computer interface;

measuring a first set of neural signals of the user including responses to the first series of stimuli;

extracting features from the first set of neural signals that temporally align with the first series of stimuli; and

training the calibration model with the features and the first series of stimuli;

receiving, in a second time window, an input from the user to perform an action with the brain computer interface;

in response to the input, performing a verification session comprising:

providing a second series of stimuli to the user from the brain computer interface, wherein the second series of stimuli includes at least one stimulus that is different from the first series of stimuli;

measuring a second set of neural signals of the user during the second time window, wherein the second set of neural signals includes responses to the second series of stimuli and a response to at least one free-form event of an imagined stimulus not part of the second series of stimuli; and

applying the calibration model to the second set of neural signals to authenticate the user; and

in response to authenticating the user, performing the action in the input from the user.

15. The system of claim 14 , wherein the brain computer interface is one of a headset or a head-mounted wearable device.

16. The system of claim 14 , wherein the second series of stimuli includes an auditory stimulus.

17. The system of claim 16 , wherein the auditory stimulus includes one or more of a music sample, a speech sample, or a cacophonous sound sample.

18. The system of claim 14 , wherein performing the action comprises populating a password in an input box.

19. The method of claim 1 , wherein the imagined stimulus of the free-form event includes an imagined audio stimulus, an imagined olfactory stimulus, an imagined taste stimulus, or a memory of the user.

20. The method of claim 1 , wherein performing the verification session comprises:

extracting a second set of features from the second set of neural signals aligned with the second series of stimuli and the free-form event of the imagined stimulus,

wherein applying the calibration model to authenticate the user comprises applying the calibration model to the second set of features from the second set of neural signals.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 6, 2022
From: FURMAN, DANIEL; KWALWASSER, EITAN
To: ARCTOP, INC.
Reel/Frame 058581/0854 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 6, 2022
From: ARCTOP, INC.
To: ARCTOP LTD
Reel/Frame 058585/0739 →
Continuity (6)
Continuation 16872924 · May 12, 2020
Continuation 15645169 · Jul 10, 2017
Provisional Application 62382445 · Sep 1, 2016
Provisional Application 62382433 · Sep 1, 2016
Provisional Application 62360640 · Jul 11, 2016
Related Publication 20220350871A1 · Nov 3, 2022