LOCAL USER AUTHENTICATION WITH NEURO AND NEURO-MECHANICAL FINGERPRINTS

• US 20170147803A1
• Filed: 02/02/2017
• Published: 05/25/2017
• Est. Priority Date: 02/04/2015
• Status: Active Grant

• Current Assignee: Aerendir Mobile Incorporated
• Original Assignee: Aerendir Mobile Incorporated
• Inventors: Zizi, Martin, Sharkey, Hugh
• Granted Patent: US 10,061,911 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/03547 Touch pads, in which fingers can move on a surface
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/19 Sensors therefor
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G06V 40/70 Multimodal biometrics, e.g. combining information from different biometric modalities
• CPC Class Codes: H04L 63/0807 using tickets, e.g. Kerberos cryptographic mechanisms or cryptographic arrangements for entity authentication using tickets or tokens H04L9/3213
• CPC Class Codes: H04L 63/0861 using biometrical features, e.g. fingerprint, retina-scan cryptographic mechanisms or cryptographic arrangements for entity authentication using biological data H04L9/3231
• CPC Class Codes: H04L 63/102 Entity profiles

Abstract

In accordance with one embodiment, a method for locally verifying the identification of a user with an electronic device is disclosed. The method includes regenerating a neuro-mechanical fingerprint (NFP) in response to a micro-motion signal sensed at a body part. In response to a plurality of authorized user calibration parameters, a match percentage of the neuro-mechanical fingerprint is determined. The match percentage is determined without the use of a calibration NFP that was previously used to generate the user calibration parameters. Access to the electronic device and its software applications is then controlled by the match percentage. If the match percentage is greater than or equal to an access match level, access to the electronic device is granted. If the match percentage is less than the access match level, access is denied. Subsequent access requires further regeneration of the NFP and a determination of its match percentage in response.

Claims

1-17. -17. (canceled)

18. An electronic device comprising:

one or more sensors to sense motions in a body part of a user and generate a motions signal in three dimensions, the motions signal including a micro-motion signal associated with the neuro-muscular micro-motions in the body part of the user;

a storage device to store machine readable instructions and authorized user calibration parameters;

a processor coupled to the sensor and the storage device, the processor to execute the machine readable instructions stored in the storage device to perform processes including

sampling the motions signal;

filtering the sampled motions signal with a band-pass filter response associated with the frequency range of the micro-motion signal associated with the neuro-muscular micro-motions;

extracting a set of values for a plurality of unique features from the micro-motion signal, the set of values for the plurality of unique features forming a neuro-mechanical fingerprint for the user; and

controlling user access to the electronic device in response to the neuro-mechanical fingerprint and the authorized user calibration parameters.

19. The electronic device of claim 18, wherein

the one or more sensors are one or more touch pad sensors to receive one or more touches of a finger to generate one or more control signals to further control the electronic device in response to user access to the electronic device.

20. The electronic device of claim 19, wherein the one or more touch pad sensors are a plurality of touch pad sensors to receive a number to further control the electronic device.

21. The electronic device of claim 20, the number is a personal identification number (PIN) to further control user access to the electronic device.

22. The electronic device of claim 20, the electronic device is a smart phone and the number is a telephone number to dial and make a telephone call with the smart phone.

23. The electronic device of claim 18, wherein

one of the one or more sensors is an image scanner to capture a user image of a finger, a hand, an eye iris, or a face and further control user access to the electronic device.

24. The electronic device of claim 18, wherein

one of the one or more sensors is a touch pad sensor to receive a signature to further control user access to the electronic device.

25. The electronic device of claim 18, wherein the processor executes further machine readable instructions stored in the storage device to perform further processes including

generating a match percentage of the neuro-mechanical fingerprint in response to authorized user calibration parameters;

wherein the user access is controlled in further response to the match percentage.

26. The electronic device of claim 25, wherein the processor executes further machine readable instructions stored in the storage device to perform further processes including

comparing the match percentage to an access match level;

and

denying access to unauthorized users with an associated match percentage less than the access match level.

27. The electronic device of claim 25, wherein the processor executes further machine readable instructions stored in the storage device to perform further processes including

comparing the match percentage to an access match level;

and

granting access to an authorized user with an associated match percentage greater than or equal to the access match level.

28. The electronic device of claim 27, wherein the processor executes further machine readable instructions stored in the storage device to perform further processes including

informing the authorized user to voluntarily recalibrate the authorized user calibration parameters in response to the match percentage being less than or equal to a voluntary recalibration level.

29. The electronic device of claim 27, wherein the processor executes further machine readable instructions stored in the storage device to perform further processes including

recalibrating the authorized user calibration parameters in response to the match percentage being less than or equal to an involuntary recalibration level.

30. The electronic device of claim 18, wherein

the one or more motion sensors are one or more accelerometers to sense three dimensional motions in the hand of the user, and

the processor executes further machine readable instructions stored in the storage device to perform further processes including

compensating for gravity;

and

compensating for axis orientation of the electronic device differing from a fixed earth axis.

31-33. -33. (canceled)

34. A method of generating a unique physiological identification of a user, the method comprising:

sensing three dimensional motion of a body part of a user to generate a three dimensional motion signal including macro-motions associated with large motions of the body part and neuro-muscular micro-motions associated with the motor control of the brain and the quality control of neuro-muscular system;

sampling the three dimensional motion signal over a predetermined sampling period with a predetermined sampling frequency;

filtering out unwanted signals in the three dimensional sampled motion signal to form a three dimensional sampled micro-motions signal representing the neuro-muscular micro-motions of the user; and

extracting a plurality of values for a predetermined plurality of features in the three dimensional sampled micro-motions signal to form a neuro-mechanical fingerprint that is unique to the user.

35. The method of claim 34, further comprising:

signal processing the three dimensional sampled micro-motions signal to determine the predetermined plurality of features to extract from the three dimensional sampled micro-motions signal.

36. The method of claim 34, wherein

the signal processing is an inverse spectral analysis of the three dimensional sampled micro-motions signal from which to select the predetermined features for extraction.

37. The method of claim 34, wherein

the predetermined features for extraction are the frequencies in the micro-motions signal at which the first N peaks occur in the inverse spectral analysis of the three dimensional sampled micro-motions signal, wherein N is greater than or equal to three.

38. The method of claim 34, wherein

the predetermined features for extraction are the times in the micro-motions signal at which the first N peaks occur in the inverse spectral analysis of the three dimensional sampled micro-motions signal, wherein N is greater than or equal to three.

39. The method of claim 34, wherein

the first N peaks represent a large variance in peak to peak amplitude of the micro-motions signal.

40. The method of claim 34, wherein

the signal processing is a chaos algorithm of the three dimensional sampled micro-motions signal from which to select features for extraction.

41. The method of claim 34, wherein the unwanted signals include a macro-motion signal associated with the large motions of the body part.

42. The method of claim 34, wherein the unwanted signals include one or more tremor signals associated with a neurological disease in the user.

43. The method of claim 34, wherein the body part is a finger.

44. The method of claim 34, wherein the motion of the body part is sensed by a sensor with axes that can change orientation and generate an angle of orientation with respected to a fixed axis, and the method further comprises:

compensating the sampled micro-motions signal for the angle of orientation of the sensor axes with respect to the fixed axis.

45. The method of claim 44, wherein the sensor is an accelerometer that is influenced by the gravitational force of the earth, and the method further comprises:

compensating the sampled micro-motions signal for the influence of the gravitational force.

46. The method of claim 45, wherein the body part is a hand.

47. A method of authenticating a user, the method comprising

concurrently receiving a first user identifier of a user and sensing motions of the user with a sensor to generate a motion signal;

generating a neuro-mechanical fingerprint that is unique to the user in response to the motion signal;

evaluating the neuro-mechanical fingerprint of the user over a database of N user calibration parameters respectively associated with N authorized users to determine a maximum match percentage; and

in response to the maximum match percentage, determining if the user is an authorized user to a system or an application by comparing the maximum match percentage to an authorized user percentage.

48. The method of claim 47, further comprising:

granting access to the system or application in response to the first user identifier and the neuro-mechanical fingerprint authenticating the user.

49. The method of claim 47, further comprising:

generating a token in response to the first user identifier and the neuro-mechanical fingerprint authenticating the user; and

transmitting the token to a server to gain access to the server.

50. The method of claim 47, wherein the first user identifier of the user is a personal identification number.

51. The method of claim 47, wherein the first user identifier of the user is a fingerprint.

52. A method comprising:

selecting one or more touch sensitive devices of a user interface of an electronic device;

authenticating the user to the electronic device with a neuro-mechanical fingerprint in response to the selection of the one or more touch sensitive devices of the user interface; and

controlling the electronic device in response to the authentication of the user and the selection of the one or more touch sensitive devices of the user interface.

53. The method of claim 52, wherein the selection of the one or more touch sensitive devices of the user interface includes at least one of selection of a power button, selection of a function button, and selection of a plurality of buttons to enter a number.

54. The method of claim 53, wherein the selection of the plurality of buttons is to enter a personal identification number to further authenticate the user to the electronic device.

55. The method of claim 53, wherein the selection of the plurality of buttons is to enter a telephone number to control the electronic device to make a telephone call.

56. The method of claim 52, wherein

the selection of the one or more touch sensitive devices of the user interface is a selection of a function button;

the function button includes an image scanner; and

the method further comprises authenticating the user to the electronic device with an image of a finger.

57. The method of claim 52, wherein the authentication of the user to the electronic device with the neuro-mechanical fingerprint includes

sensing three dimensional motion in a finger of the user with at least one of the one or more touch sensitive devices of the user interface to generate a three dimensional motion signal;

generating the neuro-mechanical fingerprint in response to the three dimensional motion signal;

evaluating the neuro-mechanical fingerprint of the user to determine a maximum match percentage; and

comparing the maximum match percentage to an authorized user percentage to authenticate the user to the electronic device.

58. A method of logging into a system or application, the method comprising

authenticating a user with a first authentication means;

further authenticating the user in response to a neuro-mechanical fingerprint generated from motions of the user captured by a sensor, the neuro-mechanical fingerprint being unique to the user; and

granting access to the system or application in response to the first authentication means and the neuro-mechanical fingerprint authenticating the user.

59. The method of claim 58, wherein the further authenticating of the user with the neuro-mechanical fingerprint includes:

sensing three dimensional motion of a body part of a user to generate a three dimensional motion signal;

in response to the three dimensional motion signal, generating the neuro-mechanical fingerprint that is unique to the user;

receiving the neuro-mechanical fingerprint as a login identification;

evaluating the neuro-mechanical fingerprint of the user over a database of N user calibration parameters respectively associated with N authorized users to determine a maximum match percentage; and

in response to the maximum match percentage, determining if the user is an authorized user to the system or application by comparing the maximum match percentage to an authorized user percentage.

60. The method of claim 59, further comprising:

in response to the maximum match percentage, identifying the user through the N authorized user associations with the N user calibration parameters, and

allowing the identified user as one of the N authorized users to use the system or the application.

61. The method of claim 58, wherein the first authentication means is an image scanner and the user is further authenticated by an image of a finger, a hand, an iris of an eye, or a face.

62. The method of claim 58, wherein the first authentication means is a touch pad sensor and the user is further authenticated by one or more keystrokes or a signature.

63. The method of claim 58, wherein the first authentication means is a microphone and the user is further authenticated by voice.