Apparatuses, systems and methods for constructing unique identifiers

• US 10,263,967 B2
• Filed: 09/01/2016
• Issued: 04/16/2019
• Est. Priority Date: 09/01/2015
• Status: Active Grant

• Current Assignee: Quantum Interface LLC
• Original Assignee: Quantum Interface LLC
• Inventors: Josephson, Jonathan, Strozier, Robert W.
• Primary Examiner(s): Avery, Jeremiah L
• Application Number:
  US15/255,107
• Publication Number:
  US 20170180336A1
• Time in Patent Office: 957 Days
• Field of Search: None
• CPC Class Codes: G06F 21/32 using biometric data, e.g. fingerprints, iris scans or voiceprints
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• 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 3/017 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 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/0485 Scrolling or panning
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• 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 63/06 for supporting key management in a packet data network cryptographic mechanisms or cryptographic arrangements for key management H04L9/08
• CPC Class Codes: H04L 63/083 using passwords cryptographic mechanisms or cryptographic arrangements for entity authentication using a predetermined code H04L9/3226
• 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: H04W 12/06 Authentication

Abstract

An apparatus for producing unique user specific identifiers including capturing user specific biometric data, kinetic data, biokinetic data, kinetic data and biometric data, biokinetic data and biometric data, and kinetic data, biokinetic data and biometric data and generating unique user specific identifiers.

Claims

1. A method implemented on an apparatus comprising:

(a) at least one sensor or at least one sensor array, (b) at least one processing unit, and (c) at least one user interface, wherein each sensor has an active zone, wherein the sensors and/or sensor arrays comprise biokinetic sensors or, kinetic sensors and/or biometric sensors, wherein the method comprises;

detecting biometric properties and movement properties from outputs from one or more of the sensors and/or sensor arrays;

testing the detected biometric properties and/or movement properties to determine if the detected biometric properties and/or movement properties meet or exceed biometric and/or movement threshold criteria;

if the biometric properties and/or movement properties fail the biometric and/or movement test, repeating the detecting and testing steps until the biometric properties and/or movement properties pass the biometric and/or movement test;

converting the biometric properties and movement properties into kinetic data, biokinetic data, and biometric data;

generating a user specific identifier, wherein the user specific identifier including some or all of the biometric data and the kinetic data and/or the biokinetic data; and

setting the generated user specific identifier for use in a user verification interface, program, website, or other verification system,

wherein the biometric data comprises whole body data and/or body part data,

wherein the kinetic and/or biokinetic data comprises variations, changes, and/or fluctuations of the whole body data and/or the body part data over a time period,

wherein the time period is a short time frame, a medium time frame, or a long time frame, or a very long time frame,

wherein the short time frame is a time duration between less than or equal to 1 ns and less than 1 μ

s,

wherein the medium time frame is a time duration between less than or equal to 1 μ

s and less than 1 ms,

wherein the long time frame is a time duration between less than or equal to about 1 ms and less than or equal to 1 s, and

wherein the very long time frame is a time duration greater than 1 s, but less than or equal to 1 minute.

2. The method of claim 1, further comprising:

before the setting step, uniqueness testing the generated user specific identifier in a uniqueness test;

if the generated user specific identifier fails the uniqueness test, repeating generating step and the uniqueness testing step until the generated user specific identifier passes the uniqueness test.

3. The method of claim 1, further comprising:

storing the generated user specific identifier and the outputs and/or the data in a database associated with the processing unit.

4. The method of claim 3, further comprising:

after storing step, detecting new biometric properties from outputs from one or more of the sensors and/or sensor arrays and/or new movement properties from outputs from one or more of the sensors and/or sensor arrays;

converting the new biometric properties and new movement properties from the sensor outputs into new biometric data, new kinetic data, and/or new biokinetic data;

comparing the new biometric data, the new kinetic data, and/or the new biokinetic data with the stored user specific identifier;

if comparison confirms user identity, then activating the user interface for further processing otherwise stopping further processing;

sensing a first motion within the active sensing zone of one or more of the sensors or sensor arrays;

producing an output signal based on the sensed first motion;

in response to the sensed first motion, displaying, on a display device in communication with the at least one processing unit, a plurality of objects or a menu or a list of items;

converting, via the at least one processing unit, the output signal into a scroll command;

processing the scroll command corresponding to traversal through the plurality of objects or to traversal through the list or menu of items until sensing, via the at least one sensor, a second motion that is non-collinear with respect to the first motion;

producing a second output signal based on the sensed second motion;

converting, via the at least one processing unit, the second output signal into a select command;

processing the selection command corresponding to selecting a particular object from the plurality of objects or a particular item from the list or menu of items responsive to the sensed second motion; and

if the particular object or item requires a user specific identifier, retrieving the user specific identifier from the database and activating the object using the user specific identifier.

5. The method of claim 1, wherein the user specific identifier comprises a signature, a user name, a password, a verifier, an authenticator, or any combination thereof.

6. The method of claim 4, wherein the activating the user interface comprises logging into a virtual reality (VR) or an augmented reality (AR) environment and further comprises:

displaying the virtual reality (VR) or the augmented reality (AR) environment; and

interacting with the virtual reality (VR) or the augmented reality (AR) environment based on sensed motion from one or more of the sensors or sensor arrays.

7. The method of claim 1, wherein the whole body data comprises internal whole body structural data and/or external whole body structure data and wherein the body part data comprises internal body part structural data and/or external body part structure data.

8. The method of claim 7, wherein the internal whole body structural data comprises skeletal data, blood circulation data, muscular data, EEG data, EKG data, ratio of internal body parts, location of internal body parts, forms of internal body parts, structures of internal body parts, or mixtures and combinations thereof and wherein the internal body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, or mixtures and combinations thereof.

9. The method of claim 7, wherein the external whole body structural data comprises height, weight, posture, size, location, structure, form, orientation, texture, color, coloring, features, ratio of body parts, location of body parts, forms of body parts, structures of body parts, brain waves, brain wave patterns, temperature distributions, aura data, bioelectric and/or biomagnetic data, or mixtures and combinations thereof and wherein the external body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, auditory data, retinal data, finger print data, palm print data, or mixtures and combinations thereof.

10. The method of claim 9, wherein the body part or the body parts are selected from the group consisting of a leg, an arm, a hand, a wrist, a finger, a foot, a toe, an eyes, a mouth, a joint, an ear, a face, a lip, a shoulder, a head, an iris, a cheek, a tongue, a thumb, and combinations thereof.

11. The method of claim 1, wherein:

the whole body data comprises internal whole body structural data and/or external whole body structure data,

the body part data comprises internal body part structural data and/or external body part structure data,

the body part or the body parts are selected from the group consisting of a leg, an arm, a hand, a wrist, a finger, a foot, a toe, an eyes, a mouth, a joint, an ear, a face, a lip, a shoulder, a head, an iris, a cheek, a tongue, a thumb, and combinations thereof.

12. The method of claim 11, wherein:

the internal whole body structural data comprises skeletal data, blood circulation data, muscular data, EEG data, EKG data, ratio of internal body parts, location of internal body parts, forms of internal body parts, structures of internal body parts, or mixtures and combinations thereof and

the internal body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, or mixtures and combinations thereof.

13. The method of claim 11, wherein:

the external whole body structural data comprises height, weight, posture, size, location, structure, form, orientation, texture, color, coloring, features, ratio of body parts, location of body parts, forms of body parts, structures of body parts, brain waves, brain wave patterns, temperature distributions, aura data, bioelectric and/or biomagnetic data, or mixtures and combinations thereof and

the external body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, auditory data, retinal data, finger print data, palm print data, or mixtures and combinations thereof.

14. The method of claim 1, wherein:

the body parts comprise two fingers held tightly together and gaps between the tightly held fingers, and

the kinetic and/or biokinetic data comprise variation, changes or fluctuation of the is the fingers and gaps of the time period.

19. The apparatus of claim 1, wherein the first input is received from the one sensor or sensor array of a plurality of sensors or sensor arrays and wherein the second input is received from a second input device that is distinct from the one sensor or senor array or a plurality of sensors or sensor arrays.

15. An apparatus comprising:

an interface including one sensor or sensor array or a plurality of sensors or sensor arrays, at least one processor, and a display device, and configured to;

detect biometric properties and movement properties by one or more of the sensors and/or sensor arrays;

test the detected biometric properties and/or movement properties to determine if the detected biometric properties and/or movement properties meet or exceed biometric and/or movement threshold criteria;

if the detected biometric properties and/or movement properties fail the biometric and/or movement test, then repeat the detect and the test until the biometric properties and/or movement properties pass the biometric and/or movement test, wherein the biometric properties and movement properties comprise kinetic data and/or biokinetic data, and biometric data; and

the at least one processor is configured to;

generate a user specific identifier, where the user specific identifier including some or all of the biometric data, kinetic data, and biokinetic data;

set the generated user specific identifier for use in a virtual reality (VR) or augmented reality (AR) environment; and

log into, take control of, or interact with the virtual reality (VR) or augmented reality (AR) environment using the user specific identifier,

wherein the biometric data comprises whole body data and/or body part data,

wherein the kinetic and/or biokinetic data comprises variations, changes, and/or fluctuations of the whole body data and/or body part data over a time period,

wherein the time period is a short time frame, a medium time frame, a long time frame, or a very long time frame,

wherein the short time frame is a time duration between less than or equal to 1 ns and less than 1 μ

s,

wherein the medium time frame is a time duration between less than or equal to 1 μ

s and less than 1 ms,

wherein the long time frame is a time duration between less than or equal to about 1 ms and less than or equal to 1 s, and

wherein the very long time frame is a time duration greater than 1 s, but less than or equal to 1 minute.

16. The apparatus of claim 15, wherein:

the interface is further configured to;

sense a first input corresponding to a first sensed movement within an active zone of one of the sensors or arrays; and

produce an output signal corresponding to the first sensed movement; and

the processor is further configured to;

initiate the display device and display the virtual reality (VR) or the augmented reality (AR) environment,

display a first menu or a plurality of selectable objects in response to the first input, the first menu including the one or a plurality of selectable items; and

initiate, at the display device, an indication that a particular selectable object or item has been selected and activated based on the first input.

17. The apparatus of claim 16, further comprising:

an input device, and/or

wherein the interface is further configured to;

sense a further input corresponding to a further sensed movement; and

produce an output signal corresponding to the further sensed movement; and

the processor is further configured to;

prior to activating the particular selectable object or item, confirm the selection the particular selectable object or item,

wherein the further input is received from the motion sensors or sensor arrays or from an input device.

18. The apparatus of claim 17, wherein the input device and at least one of the motion sensors comprises an eye tracking device.

20. The apparatus of claim 15, wherein:

the whole body data comprises internal whole body structural data and/or external whole body structure data,

the body part data comprises internal body part structural data and/or external body part structure data,

the body part or the body parts are selected from the group consisting of a leg, an arm, a hand, a wrist, a finger, a foot, a toe, an eyes, a mouth, a joint, an ear, a face, a lip, a shoulder, a head, an iris, a cheek, a tongue, a thumb, and combinations thereof.

21. The apparatus of claim 20, wherein:

the internal whole body structural data comprises skeletal data, blood circulation data, muscular data, EEG data, EKG data, ratio of internal body parts, location of internal body parts, forms of internal body parts, structures of internal body parts, or mixtures and combinations thereof and

the internal body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, or mixtures and combinations thereof.

22. The apparatus of claim 20, wherein:

the external whole body structural data comprises height, weight, posture, size, location, structure, form, orientation, texture, color, coloring, features, ratio of body parts, location of body parts, forms of body parts, structures of body parts, brain waves, brain wave patterns, temperature distributions, aura data, bioelectric and/or biomagnetic data, or mixtures and combinations thereof and

the external body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, auditory data, retinal data, finger print data, palm print data, or mixtures and combinations thereof.

23. A method comprising:

detecting biometric properties and movement properties by one sensor and/or sensor array or a plurality of the sensors and/or sensor arrays associated with a mobile device including a touch screen or a display device;

testing the detected biometric properties and/or movement properties to determine if the detected biometric properties and/or movement properties meet or exceed biometric property and/or movement property threshold criteria;

if the detected biometric properties and/or movement properties fail the biometric and/or movement test, then repeating the detecting and testing steps until the biometric properties and/or movement properties pass the biometric and/or movement test, wherein the biometric properties and the movement properties include kinetic data, biokinetic data, and biometric data;

generating a user specific identifier, wherein the user specific identifier including some or all of biometric data, kinetic data, and biokinetic data;

setting and storing, in a database associated with the at least one processing unit, the generated user specific identifier;

logging into a virtual reality (VR) or augmented reality (AR) environment using the user specific identifier;

receiving first input at the touchscreen of the mobile device;

displaying a first menu on the touchscreen in response to the first input, the first menu including a plurality of selectable items;

receiving, at the touchscreen while the first menu is displayed on the touchscreen, a second input corresponding to a particular biometric property and/or movement in a particular direction; and

determining, based on the particular biometric property or the particular direction, that the second input corresponds to a selection of a particular selectable item of the plurality of selectable items and/or attributes,

wherein the biometric data comprises whole body data and/or body part data,

wherein the kinetic and/or biokinetic data comprises variations, changes, and/or fluctuations of the whole body data and/or body part data over a time period,

wherein the time period is a short time frame, a medium time frame, a long time frame, or a very long time frame,

wherein the short time frame is a time duration between less than or equal to 1 ns and less than 1 μ

s,

wherein the medium time frame is a time duration between less than or equal to 1 μ

s and less than 1 ms,

wherein the long time frame is a time duration between less than or equal to about 1 ms and less than or equal to 1 s, and

wherein the very long time frame is a time duration greater than 1 s, but less than or equal to 1 minute.

24. The method of claim 23, wherein:

the whole body data comprises internal whole body structural data and/or external whole body structure data,

the body part data comprises internal body part structural data and/or external body part structure data,

the body part or the body parts are selected from the group consisting of a leg, an arm, a hand, a wrist, a finger, a foot, a toe, an eyes, a mouth, a joint, an ear, a face, a lip, a shoulder, a head, an iris, a cheek, a tongue, a thumb, and combinations thereof.

25. The method of claim 24, wherein:

the internal whole body structural data comprises skeletal data, blood circulation data, muscular data, EEG data, EKG data, ratio of internal body parts, location of internal body parts, forms of internal body parts, structures of internal body parts, or mixtures and combinations thereof and

the internal body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, or mixtures and combinations thereof.

26. The method of claim 24, wherein:

the external whole body structural data comprises height, weight, posture, size, location, structure, form, orientation, texture, color, coloring, features, ratio of body parts, location of body parts, forms of body parts, structures of body parts, brain waves, brain wave patterns, temperature distributions, aura data, bioelectric and/or biomagnetic data, or mixtures and combinations thereof and

the external body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, auditory data, retinal data, finger print data, palm print data, or mixtures and combinations thereof.

27. A mobile device comprising:

a touchscreen; and

a processor configured to;

detect biometric properties and movement properties by one sensor and/or sensor array or a plurality of the sensors and/or sensor arrays associated with the mobile device and/or the touchscreen;

test the detected biometric properties and/or movement properties to determine if the detected biometric properties and/or movement properties meet or exceed biometric property and/or movement property threshold criteria;

if the detected biometric properties and/or movement properties fail the threshold criteria test, then repeat the detect and test until the biometric properties and/or movement properties pass the biometric and/or movement threshold criteria test,

wherein the biometric properties and movement properties include kinetic data, biokinetic data, and biometric data;

generate a user specific identifier, wherein the user specific identifier including some or all of the biometric data, kinetic data, and biokinetic data;

set the generated user specific identifier;

store the generated user specific identifier in a user identifier database; and

use the stored user specific identifier to log into, take control of, or interact with a virtual reality (VR) or an augmented reality (AR) environment,

wherein the biometric data comprises whole body data and/or body part data,

wherein the kinetic and/or biokinetic data comprises variations, changes, and/or fluctuations of the whole body data and/or body part data over a time period,

wherein the time period is a short time frame, a medium time frame, a long time frame, or a very long time frame,

wherein the short time frame is a time duration between less than or equal to 1 ns and less than 1 μ

s,

wherein the medium time frame is a time duration between less than or equal to 1 μ

s and less than 1 ms,

wherein the long time frame is a time duration between less than or equal to about 1 ms and less than or equal to 1 s, and

wherein the very long time frame is a time duration greater than 1 s, but less than or equal to 1 minute.

28. The mobile device of claim 27, wherein:

the processor is further configured to be;

responsive to first input at the touchscreen, initiate display of or interaction with a first menu, object(s), or attribute(s) on the touchscreen, the first menu including a plurality of selectable items; and

responsive to second input corresponding to movement in a particular direction while the first menu is displayed on the touchscreen, determine based on the particular direction that the second input corresponds to a selection of a particular selectable item of the plurality of selectable items.

29. The mobile device of claim 27, wherein the touchscreen and the processor are integrated into a mobile phone, or wherein the touchscreen and the processor are integrated into a tablet computer, or the touchscreen and the processor are integrated into a wearable device.

30. The mobile device of claim 27, wherein:

the whole body data comprises internal whole body structural data and/or external whole body structure data,

the body part data comprises internal body part structural data and/or external body part structure data, and

the body part or the body parts are selected from the group consisting of a leg, an arm, a hand, a wrist, a finger, a foot, a toe, an eyes, a mouth, a joint, an ear, a face, a lip, a shoulder, a head, an iris, a cheek, a tongue, a thumb, and combinations thereof.

31. The mobile device of claim 30, wherein:

the internal whole body structural data comprises skeletal data, blood circulation data, muscular data, EEG data, EKG data, ratio of internal body parts, location of internal body parts, forms of internal body parts, structures of internal body parts, or mixtures and combinations thereof and

the internal body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, or mixtures and combinations thereof.

32. The mobile device of claim 30, wherein:

the external whole body structural data comprises height, weight, posture, size, location, structure, form, orientation, texture, color, coloring, features, ratio of body parts, location of body parts, forms of body parts, structures of body parts, brain waves, brain wave patterns, temperature distributions, aura data, bioelectric and/or biomagnetic data, or mixtures and combinations thereof and

the external body part structural data comprises body part shape, size, location, structure, form, orientation, texture, color, coloring, features, auditory data, retinal data, finger print data, palm print data, or mixtures and combinations thereof.