SYSTEMS AND METHODS FOR COLLECTING, ANALYZING, AND SHARING BIO-SIGNAL AND NON-BIO-SIGNAL DATA

• US 20150199010A1
• Filed: 09/16/2013
• Published: 07/16/2015
• Est. Priority Date: 09/14/2012
• Status: Active Grant

• Current Assignee: InteraXon Inc.
• Original Assignee: InteraXon Inc.
• Inventors: Coleman, Trevor Ce, Aimone, Christopher Allen, Garten, Ariel Stephanie, Pino, Locillo (Lou) Giuseppe, Baranowski, Paul Harrison, Rupsingh, Raul Rajiv, Vidyarthi, Kapil Jay Mishra
• Granted Patent: US 9,983,670 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• 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: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: H04L 12/16 Arrangements for providing special services to substations
• CPC Class Codes: H04L 67/01 Protocols

Abstract

A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.

Claims

1. A system comprising:

at least one client computing device;

at least one bio-signal sensor at and in communication with the at least one client computing device; and

at least one computer server in communication with the at least one computing device over a communications network;

the at least one client computing device configured to;

receive time-coded bio-signal data of a user from the at least one bio-signal sensor;

transmit the time-coded bio-signal data and acquired time-coded feature event data to the at least one computer server;

receive from the at least one computer server a user-response classification of at least part of the time-coded bio-signal data based on an identified pattern of correspondence between the at least part of the time-coded bio-signal data and at least part of the time-coded feature event data at at least one respective time code;

in accordance with a received input confirming the user-response classification, update a bio-signal interaction profile at the at least one client computing device with the user-response classification, the at least part of the time-coded bio-signal data, and the at least part of the time-coded feature event data at the at least one respective time code.

2. The system of claim 1 wherein the at least one client computing device is further configured to transmit a confirmation of the user-response classification to the at least one computer server.

3. The system of claim 2 wherein the at least one computer server is configured to update a bio-signal interaction profile associated with the user at the at least one computer server with the user-response classification, the at least part of the time-coded bio-signal data, and the at least part of the time-coded feature event data at the at least one respective time code.

4. The system of claim 3 wherein the bio-signal interaction profile associated with the user is anonymized.

5. The system of claim 3 wherein the at least one computer server is configured to identify a correspondence between the at least part of the time-coded feature event data stored in the bio-signal interaction profile stored at the at least one computer server with time-coded feature event data received from at least one second client computing device associated with a second user.

6. The system of claim 5 wherein the at least one computer server is configured to classify at least part of time-coded bio-signal data received from the at least one second client computing device corresponding to the time-coded feature event data received from the at least one second client computing in accordance with the user-response classification.

7. The system of claim 6 wherein the at least one computer server is configured to update a bio-signal interaction profile associated with the second user with the classification of the at least part of the time-coded bio-signal data received from the at least one second client computing device, the at least part of the time-coded bio-signal data received from the at least one second client computing device, and the at least part of the time-coded feature event data received from the at least one second client computing device, in accordance with a received confirmation of the user-response classification from the at least one second client computing device.

8. The system of claim 7 wherein the acquired time-coded feature event data comprises an identification of playback of a particular media, the user-response classification comprises a determination of the user having liked the particular media;

the at least one computer server configured to transmit a recommendation of at least one other particular media to the at least one second client computing device.

9. The system of claim 1 further comprising at least one non-bio-signal sensor at and in communication with the at least one client computing device, the at least one client computing device configured to:

receive time-coded non-bio-signal sensor data from the at least one non-bio-signal sensor;

wherein the acquired time-coded feature event data is based at least partly on the received time-coded non-bio-signal sensor data.

10. The system of claim 1 wherein the acquired time-coded feature event data is based at least partly on calendar data stored on the at least one client computing device.

11. The system of claim 1 wherein the acquired time-coded feature event data is based at least partly on event data input from the user.

12. The system of claim 1 wherein the at least one bio-signal sensor comprises a head-mountable brainwave sensor, and the time-coded bio-signal sensor data comprises brainwave data of the user.

13. The system of claim 1 wherein the at least one client computing device is configured to transmit at least part of the bio-signal sensor data to at least one second client computing device for use as input by the at least one second client computing device.

14. The system of claim 1 wherein the at least one client computing device is configured to transmit the user-response classification to at least one second client computing device for use as input by the at least one second client computing device.

15. The system of claim 4 wherein the at least one computer server is configured to transmit at least part of the bio-signal sensor data to at least one second client computing device for use as input by the at least one second client computing device.

16. The system of claim 4 wherein the at least one computer server is configured to transmit the user-response classification to at least one second client computing device for use as input by the at least one second client computing device.

17. The system of claim 1 wherein the at least one client computing device is configured to update notification settings of the at least one client computing device in accordance with an identification of subsequently-received time-coded bio-signal data corresponding to the user-response classification.

18. The system of claim 1 wherein the computer server is configured to determine the user-response classification based at least partly on a type of the at least one bio-signal sensor.

19. The system of claim 1 comprising the at least one client computing device configured to process at least part of the time-coded bio-signal data in accordance with the bio-signal interaction profile at the client computing device, and transmit the processed time-coded bio-signal data to the at least one computer server, wherein the user-response classification is based at least partly on the processed time-coded bio-signal data.

20. A method, performed by at least one client computing device in communication with at least one bio-signal sensor at the at least one client computing device, the at least one client computing device in communication with at least one computer server over a communications network, the method comprising:

receiving time-coded bio-signal data of a user from the at least one bio-signal sensor;

transmitting the time-coded bio-signal data and acquired time-coded feature event data to the at least one computer server;

receiving from the at least one computer server a user-response classification of at least part of the time-coded bio-signal data based on an identified pattern of correspondence between the at least part of the time-coded bio-signal data and at least part of the time-coded feature event data at at least one respective time code;

in accordance with a received input confirming the user-response classification, updating a bio-signal interaction profile at the at least one client computing device with the user-response classification, the at least part of the time-coded bio-signal data, and the at least part of the time-coded feature event data at the at least one respective time code.

21. The method of claim 20 comprising transmitting a confirmation of the user-response classification to the at least one computer server.

22. The method of claim 21 wherein the at least one computer server is configured to update a bio-signal interaction profile associated with the user at the at least one computer server with the user-response classification, the at least part of the time-coded bio-signal data, and the at least part of the time-coded feature event data at the at least one respective time code.

23. The method of claim 22 wherein the bio-signal interaction profile associated with the user is anonymized.

24. The method of claim 22 wherein the at least one computer server is configured to identify a correspondence between the at least part of the time-coded feature event data stored in the bio-signal interaction profile stored at the at least one computer server with time-coded feature event data received from at least one second client computing device associated with a second user.

25. The method of claim 24 wherein the at least one computer server is configured to classify at least part of time-coded bio-signal data received from the at least one second client computing device corresponding to the time-coded feature event data received from the at least one second client computing in accordance with the user-response classification.

26. The method of claim 25 wherein the at least one computer server is configured to update a bio-signal interaction profile associated with the second user with the classification of the at least part of the time-coded bio-signal data received from the at least one second client computing device, the at least part of the time-coded bio-signal data received from the at least one second client computing device, and the at least part of the time-coded feature event data received from the at least one second client computing device, in accordance with a received confirmation of the user-response classification from the at least one second client computing device.

27. The method of claim 26 wherein the acquired time-coded feature event data comprises an identification of playback of a particular media, the user-response classification comprises a determination of the user having liked the particular media;

the at least one computer server configured to transmit a recommendation of at least one other particular media to the at least one second client computing device.

28. The method of claim 20 wherein at least one non-bio-signal sensor is located at and is in communication with the at least one client computing device, the method comprising:

receiving time-coded non-bio-signal sensor data from the at least one non-bio-signal sensor;

wherein the acquired time-coded feature event data is based at least partly on the received time-coded non-bio-signal sensor data.

29. The method of claim 20 wherein the acquired time-coded feature event data is based at least partly on calendar data stored on the at least one client computing device.

30. The method of claim 20 wherein the acquired time-coded feature event data is based at least partly on event data input from the user.

31. The method of claim 20 wherein the at least one bio-signal sensor comprises a head-mountable brainwave sensor, and the time-coded bio-signal sensor data comprises brainwave data of the user.

32. The method of claim 20 comprising transmitting at least part of the bio-signal sensor data to at least one second client computing device for use as input by the at least one second client computing device.

33. The method of claim 20 comprising transmitting the user-response classification to at least one second client computing device for use as input by the at least one second client computing device.

34. The method of claim 23 wherein the at least one computer server is configured to transmit at least part of the bio-signal sensor data to at least one second client computing device for use as input by the at least one second client computing device.

35. The method of claim 23 wherein the at least one computer server is configured to transmit the user-response classification to at least one second client computing device for use as input by the at least one second client computing device.

36. The method of claim 20 comprising updating notification settings of the at least one client computing device in accordance with an identification of subsequently-received time-coded bio-signal data corresponding to the user-response classification.

37. The method of claim 20 wherein the computer server is configured to determine the user-response classification based at least partly on a type of the at least one bio-signal sensor.

38. The method of claim 20 comprising processing at least part of the time-coded bio-signal data in accordance with the bio-signal interaction profile at the client computing device, and transmitting the processed time-coded bio-signal data to the at least one computer server, wherein the user-response classification is based at least partly on the processed time-coded bio-signal data.

39. A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided comprising:

(a) one or more server computers linked to the Internet, and enabling one or more computer implemented utilities providing;

(i) a brain computer interface for connecting to one or more applications for enabling one or more biofeedback computer systems, the brain computer interface linking to one or more sensors that include at least one brain wave sensor and optionally a non-bio-signal data sensor;

(ii) an intelligent bio-signal processing system that is operable to;

(A) capture bio-signal data and in addition optionally non-bio-signal data; and

(B) analyze the bio-signal data and non-bio-signal data, if any, so as to;

(I) extract one or more features related to at least one individual interacting with the biofeedback computer system;

(II) classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and

(III) access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems.