System and method for embedded cognitive state metric system

• US 10,108,264 B2
• Filed: 03/02/2016
• Issued: 10/23/2018
• Est. Priority Date: 03/02/2015
• Status: Active Grant

• Current Assignee: EMOTIV Inc.
• Original Assignee: EMOTIV Inc.
• Inventors: Le, Tan, Mackellar, Geoffrey
• Primary Examiner(s): To, Jennifer N
• Assistant Examiner(s): Hoang, Amy P
• Application Number:
  US15/058,622
• Publication Number:
  US 20160259492A1
• Time in Patent Office: 965 Days
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 3/015 Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
• CPC Class Codes: G06F 3/0487 using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser

Abstract

An embodiment of a method for enabling content personalization for a user based on a cognitive state of the user includes providing an interface configured to enable a third party to request cognitive state data of the user as the user interacts with a content-providing source; establishing bioelectrical contact between a biosignal detector and the user; automatically collecting a dataset from the user; generating a cognitive state metric; receiving a request from the third party for cognitive state data; transmitting the cognitive state data to the third party device; and automatically collecting a dataset from the user as the user engaged tailored content.

Claims

1. A method for enabling content personalization for a user based on a cognitive state of the user, the method comprising:

providing an interface configured to enable a third party device to request cognitive state data of the user as the user interacts with a third party application managed by the third party;

establishing bioelectrical contact between an electroencephalogram (EEG) signal detector and the user, the EEG signal detector comprising;

a set of sensors configured to detect EEG signals from the user, each sensor in the set of sensors comprising a hydrogel, the set of sensors including an anterior frontal sensor, a temporal lobe sensor, and a central sensor;

an electronics subsystem configured to process EEG signals from the set of sensors;

a housing configured to be worn at a head region of the user and comprising a set of arms, configured to couple to the electronics subsystem, wherein the set of arms includes a first arm originating proximal a temporal bone of the user and that positions the anterior frontal sensor proximal an anterior portion of the frontal bone of the user and a second arm originating proximal the temporal bone of the user and that positions the temporal lobe sensor proximal the first temporal bone of the user, upon coupling of the system to the user; and

a set of sensor interfaces coupling the set of sensors to the electronics subsystem through the set of arms of the housing, each sensor interface in the set of sensor interfaces;

automatically collecting, at the EEG signal detector, a baseline EEG signal dataset from the user as the user engages reference content in a reference interaction;

generating a baseline cognitive state metric, indicative of a baseline cognitive state of the user in the reference interaction, from the baseline EEG signal dataset;

automatically collecting, at the EEG signal detector, a first EEG signal dataset from the user as the user engages the third party application in a first interaction;

generating a first cognitive state metric, indicative of the cognitive state of the user in the first interaction, from the first EEG signal dataset;

receiving a request from the third party device for cognitive state data comprising the baseline cognitive state metric and the first cognitive state metric;

in response to receiving the request, transmitting the cognitive state data to the third party device; and

upon detection that the user is engaging the third party application in a second interaction, the third party application presenting tailored content to the user based on processing of the baseline cognitive state metric and the first cognitive state metric;

automatically collecting, at the EEG signal detector, a second EEG signal dataset.

2. The method of claim 1, further comprising

automatically collecting, at the EEG signal detector, a supplemental EEG signal dataset over a first timeframe;

generating a second cognitive state metric based on the supplemental EEG signal data set; and

associating the second cognitive state metric with a content stream corresponding to the first timeframe, the content stream associated with the user,

wherein the tailored content is further based on the second cognitive state metric, the content stream, and the association between the second cognitive state metric and the content stream.

3. The method of claim 2, wherein the content stream comprises at least one of:

a video, an audio recording, and a social network content stream.

4. The method of claim 2, wherein associating the cognitive state metric with the content stream comprises tagging the content stream with a cognitive state indicated by the cognitive state metric.

5. The method of claim 1, further comprising, in response to the difference between the baseline cognitive state metric and the first cognitive state metric exceeding a threshold, notifying the third party device.

6. The method of claim 1, wherein the tailored content is further based on processing a supplemental dataset comprising at least one of:

sensor data of a user device associated with the third party application, a user interface action at the user device, and motion sensor data collected at the EEG signal detector as the user engages the third party application in the first interaction.

7. The method of claim 6, wherein the tailored content is further based on processing the supplemental dataset, further comprising input device data associated with interactions between the user and input devices that the user engages when interacting with the third party application.

8. The method of claim 1, wherein automatically collecting the first bioelectrical signal dataset is in response to detecting a first login to a user account associated with the user and the third party application, and wherein automatically collecting the second bioelectrical signal dataset is in response to a second login to the user account.

9. The method of claim 1, further comprising:

automatically collecting, at the EEG signal detector, a third EEG signal dataset from the user as the user engages an additional application different from the third party application; and

storing a user profile generated based on the baseline, the first, the second, and the third EEG signal datasets, wherein the tailored content is further based on the user profile.

10. The method of claim 1, wherein the third party application is a web application, and wherein the interface is an application programming interface.

11. A method for enabling content personalization for a first user based on a cognitive state of the user, the method comprising:

providing an interface configured to enable a third party device to request cognitive state data of the first user as the first user interacts with a content-providing source managed by the third party;

establishing bioelectrical contact between a first biosignal detector and the first user, the first biosignal detector comprising;

a set of sensors configured to detect EEG signals from the user, each sensor in the set of sensors comprising a hydrogel, the set of sensors including an anterior frontal sensor, a temporal lobe sensor, and a central sensor;

an electronics subsystem configured to process EEG signals from the set of sensors;

a housing configured to be worn at a head region of the user and comprising a set of arms, configured to couple to the electronics subsystem, wherein the set of arms includes a first arm originating proximal a temporal bone of the user and that positions the anterior frontal sensor proximal an anterior portion of the frontal bone of the user and a second arm originating proximal the temporal bone of the user and that positions the temporal lobe sensor proximal the first temporal bone of the user, upon coupling of the system to the user; and

a set of sensor interfaces coupling the set of sensors to the electronics subsystem through the set of arms of the housing, each sensor interface in the set of sensor interfaces;

automatically collecting, at the first biosignal detector, a first bioelectrical signal dataset from the first user as the first user engages content of the content-providing source in a first interaction;

generating a cognitive state metric, indicative of the cognitive state of the user in the first interaction, from the first bioelectrical signal dataset;

receiving a first request from the third party device for cognitive state data comprising the cognitive state metric;

in response to receiving the first request, transmitting the cognitive state data to the third party device; and

automatically collecting, at the first biosignal detector, a second bioelectrical signal dataset from the user as the user engages tailored content of the content-providing source in a second interaction, wherein the tailored content is based on a third party analysis of the cognitive state data.

12. The method of claim 11, wherein the first and the second interactions are within a same user session with the content-providing source.

13. The method of claim 11, wherein the cognitive state of the user is a negative emotional state, and wherein the tailored content is tailored to induce a positive emotional state of the user.

14. The method of claim 13, further comprising generating an emotion improvement metric based on the second bioelectrical signal dataset, the emotion improvement metric indicative of emotional state improvement from the first interaction to the second interaction.

15. The method of claim 11, further comprising:

automatically collecting, at a second biosignal detector, a first additional bioelectrical signal dataset from a second user as the second user engages the content;

generating an additional cognitive state metric based on the first additional bioelectrical signal dataset; and

in response to receiving a second request from the third party device for additional cognitive state data comprising the additional cognitive state metric, transmitting the additional cognitive state data to the third party device.

16. The method of claim 15, wherein the tailored content is tailored for a user group comprising the first and the second users, the user group defined by the third party based on the cognitive state metric and the additional cognitive state metric.

17. The method of claim 16, further comprising, automatically collecting, at the second biosignal detector, a second additional bioelectrical signal dataset from the second user as the second user engages the tailored content.

18. The method of claim 11, further comprising associating the cognitive state metric with a user interface action at a user device presenting the content engaged by the first user, wherein the cognitive state data comprises the association between the cognitive state metric and the user interface action.

19. The method of claim 11, further comprising automatically collecting, at the first biosignal detector, a supplemental motion sensor dataset from the user as the user engages the content, wherein the cognitive state data comprises the supplemental motion sensor dataset.

20. The method of claim 11, further comprising:

associating the cognitive state metric with a content stream corresponding to a time frame associated with the first bioelectrical signal dataset, the content stream associated with the first user,

wherein the tailored content is further based on the content stream and the association between the cognitive state metric and the content stream.

21. The method of claim 11, wherein the interface is an application programming interface.