IP Library Granted Patent US 11,175,745
Granted Patent B2
US 11,175,745 · App. 16/777,906 · Granted Nov 16, 2021

System and method for application of piezo electric haptic keyboard personal typing profile

Inventors: Michiel Knoppert (Amsterdam, NL); Priyank Gajiwala (Austin, TX)
Assignee: Dell Products, LP
G06F3/0202G06F3/016G06F3/023G06N3/084G06N5/046G06N20/00H01H13/7065H01H13/85H03K17/967H01H2215/052
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Quick Facts
Patent No.
US 11,175,745
App. No.
16/777,906
Granted
Nov 16, 2021
Kind
B2
Abstract

A haptic keyboard typing profile personalization system of an information handling system comprising a processor to receive a plurality of haptic hardware typing behavior parameter values for a user via a piezo haptic keyboard controller and input the plurality of haptic hardware typing behavior parameter values into a personal typing profile comprising weight matrices of a machine learning neural network correlating the input with one or more haptic setting values defining haptic feedback movement one of a plurality of piezo electric elements of a haptic keyboard to identify an output describing the personal typing profile with learned, custom haptic setting values optimized for the user, and the piezo haptic keyboard controller applying a voltage of specific magnitude, polarity, or duration to the haptic keyboard to cause a piezo electric element to operate according to the personally typing profile learned, custom haptic setting values.

Claims (48)

1. A haptic keyboard typing profile personalization system of an information handling system comprising:

a processor executing machine readable code instructions to:

receive, over the period of time, a plurality of haptic hardware typing behavior parameter values for a user via a piezo haptic keyboard controller indicating keystrike force or duration of key strikes; and

input, as an input layer, the plurality of haptic hardware typing behavior parameter values for a personal typing profile into code instructions of a machine learning algorithm executing a neural network for correlating the input layer with one or more haptic setting values defining haptic feedback movement of one of a plurality of piezo electric elements of a haptic keyboard;

the processor executing the code instructions of the machine learning algorithm configured to identify an output layer describing the personal typing profile with learned, custom haptic setting values for the one or more haptic setting values optimized for the user; and

the piezo haptic keyboard controller applying a voltage of specific magnitude, polarity, or duration to a contact foil layer operably connecting the piezo haptic keyboard controller to a piezo electric element of the haptic keyboard to cause the piezo electric element to operate according to the personally typing profile learned, custom haptic setting values to detect keystrokes and provide haptic feedback to the haptic keyboard.

2. The haptic keyboard typing profile personalization system of claim 1 , wherein input layer of code instructions of the machine learning algorithm comprises weight matrices of the neural network and the processor forward propagates the input layer through the neural network to identify the output layer describing the personal typing profile with learned, custom haptic setting values.

3. The haptic keyboard typing profile personalization system of claim 1 , wherein one of the plurality of haptic hardware typing behavior parameter values includes an indication of a high level of keystrike force and the updated learned, custom haptic setting values is an increased force threshold setting to register a keystroke.

4. The haptic keyboard typing profile personalization system of claim 1 , wherein one of the plurality of haptic hardware typing behavior parameter values includes an indication of a high level of keystrike force and the updated learned, custom haptic setting values is an increased haptic movement intensity setting in a haptic feedback control signal for the haptic feedback to the haptic keyboard.

5. The haptic keyboard typing profile personalization system of claim 1 , wherein one of the plurality of haptic hardware typing behavior parameter values includes an indication of a short duration of keystrike and the updated learned, custom haptic setting values is a decreased force threshold setting to register a keystroke and a decreased haptic movement intensity setting in a haptic feedback control signal for the haptic feedback to the haptic keyboard.

6. The haptic keyboard typing profile personalization system of claim 1 further comprising:

the processor to receive, over a period of time, a plurality of user-defined haptic setting values defining haptic feedback movement of a plurality of piezo electric elements;

the processor determine if the plurality of user-defined haptic setting values defining haptic feedback movement of the plurality of piezo electric elements overrides the output layer describing the personal typing profile and providing updated learned, custom haptic setting values for the one or more haptic setting values according to the user-defined haptic setting values.

7. The haptic keyboard typing profile personalization system of claim 1 further comprising:

the processor to receive, over a period of time, a plurality of user-defined haptic setting values defining haptic feedback movement of a plurality of piezo electric elements;

the processor to input as an input layer, the plurality of user-defined haptic setting values defining haptic feedback movement of the plurality of piezo electric elements into the personal typing profile and updating the output layer describing the personal typing profile with updated learned, custom haptic setting values for the one or more haptic setting values optimized for the user.

8. The haptic keyboard typing profile personalization system of claim 1 further comprising:

the processor to receive, over the period of time, a plurality of physical surrounding indicator values via an operably connected environmental sensor and a plurality of application usage data values via a software application operating on the information handling system;

the processor to input as an input layer, the plurality of physical surrounding indicator values and the plurality of application usage data values into the personal typing profile and updating the output layer describing the personal typing profile with updated learned, custom haptic setting values for the one or more haptic setting values optimized for the user.

9. The haptic keyboard typing profile personalization system of claim 8 , wherein one of the plurality of physical surrounding indicator values includes an indication of low ambient noise and the updated learned, custom haptic setting values is a decreased force threshold setting.

10. A haptic keyboard typing profile personalization system of an information handling system comprising:

a processor executing machine readable code instructions to:

receive, over the period of time, a plurality of haptic hardware typing behavior parameter values for a user via a piezo haptic keyboard controller indicating keystrike force or duration of key strikes;

receive, a plurality of user-defined haptic setting values defining haptic feedback movement of a plurality of piezo electric elements; and

input, as an input layer, the plurality of haptic hardware typing behavior parameter values and user-defined haptic setting values for a personal typing profile into code instructions for a machine learning algorithm executing a neural network for correlating the input layer with one or more haptic setting values defining haptic feedback movement of the plurality of piezo electric elements of a haptic keyboard;

the processor executing the code instructions of the machine learning algorithm configured to identify an output layer describing the personal typing profile with learned, custom haptic setting values for the one or more haptic setting values optimized for the user; and

the piezo haptic keyboard controller applying a voltage of specific magnitude, polarity, or duration to a contact foil layer operably connecting the piezo haptic keyboard controller to a piezo electric element of the haptic keyboard to cause the piezo electric element to operate according to the personally typing profile learned, custom haptic setting values to detect keystrokes and provide haptic feedback to the haptic keyboard.

11. The haptic keyboard typing profile personalization system of claim 10 , wherein input layer of the code instructions for the machine learning algorithm comprises weight matrices of the neural network and the processor forward propagates the input layer through the neural network to identify the output layer describing the personal typing profile with learned, custom haptic setting values.

12. The haptic keyboard typing profile personalization system of claim 10 , wherein one of the plurality of haptic hardware typing behavior parameter values includes an indication of a high level of keystrike force and the updated learned, custom haptic setting values is an increased force threshold setting to register a keystroke.

13. The haptic keyboard typing profile personalization system of claim 10 , wherein one of the plurality of user-defined haptic setting values defining haptic feedback movement of a plurality of piezo electric elements includes a setting for increased keystrike force threshold to decrease sensitivity and errors in typing and the updated learned, custom haptic setting values yields an increased force threshold and an increased haptic movement intensity setting in a haptic feedback control signal for the haptic feedback to the haptic keyboard.

14. The haptic keyboard typing profile personalization system of claim 10 further comprising:

the processor to receive, over the period of time, a plurality of physical surrounding indicator values via an operably connected environmental sensor and a plurality of application usage data values via a software application operating on the information handling system;

the processor to input as an input layer, the plurality of physical surrounding indicator values and the plurality of application usage data values into the personal typing profile and updating the output layer describing the personal typing profile with updated learned, custom haptic setting values for the one or more haptic setting values optimized for the user.

15. The haptic keyboard typing profile personalization system of claim 10 , wherein one of the plurality of physical surrounding indicator values includes an indication the user is engaged in a conversation and the updated learned, custom haptic setting values is a decreased force threshold setting.

16. A haptic keyboard typing profile personalization system of an information handling system comprising:

a processor executing machine readable code instructions to:

the processor to receive, over a period of time, a plurality of user-defined haptic setting values defining haptic feedback movement of a plurality of piezo electric elements;

the processor to set the plurality of user-defined haptic setting values defining haptic feedback movement of the plurality of piezo electric elements as a personal typing profile and providing learned, custom haptic setting values for the one or more haptic setting values according to the user-defined haptic setting values; and

the piezo haptic keyboard controller applying a voltage of specific magnitude, polarity, or duration to a contact foil layer operably connecting the piezo haptic keyboard controller to a piezo electric element of the haptic keyboard to cause the piezo electric element to operate according to the personally typing profile learned, custom haptic setting values to detect keystrokes and provide haptic feedback to the haptic keyboard.

17. The haptic keyboard typing profile personalization system of claim 16 further comprising:

receive, over the period of time, a plurality of haptic hardware typing behavior parameter values for a user via a piezo haptic keyboard controller indicating keystrike force or duration of keystrikes;

input, as an input layer, the plurality of haptic hardware typing behavior parameter values and the plurality of user-defined haptic setting values for a personal typing profile into code instructions of a machine learning algorithm executing a neural network for correlating the input layer with one or more haptic setting values defining haptic feedback movement one of a plurality of piezo electric elements of a haptic keyboard;

the code instructions of the machine learning algorithnm to identify an output layer describing the personal typing profile with updated learned, custom haptic setting values for the one or more haptic setting values optimized for the user.

18. The haptic keyboard typing profile personalization system of claim 17 , wherein the output layer of the code instructions of machine learning algorithm updates the personal typing profile with updated learned, custom haptic setting values for the one or more haptic setting values optimized for the user is suggested to the user via a haptic setting graphical user interface.

19. The haptic keyboard typing profile personalization system of claim 16 further comprising:

the processor to receive, over the period of time, a plurality of physical surrounding indicator values via an operably connected environmental sensor and a plurality of application usage data values via a software application operating on the information handling system;

the processor to adjust the personal typing profile and provide updated learned, custom haptic setting values for the one or more haptic setting values according to the plurality of physical surrounding indicator values and the plurality of application usage data values according to the personal typing profile.

20. The haptic keyboard typing profile personalization system of claim 16 , wherein the plurality of user-defined haptic setting values defining haptic feedback movement of the plurality of piezo electric elements includes force threshold detection level setting, haptic feedback intensity settings, haptic feedback duration settings or haptic feedback sharpness settings.

Assignments (9)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053311/0169) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
Reel/Frame 060438/0742 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053546/0001) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL MARKETING L.P. (ON BEHALF OF ITSELF AND AS SUCCESSOR-IN-INTEREST TO CREDANT TECHNOLOGIES, INC.); DELL INTERNATIONAL L.L.C.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; DELL MARKETING CORPORATION (SUCCESSOR-IN-INTEREST TO FORCE10 NETWORKS, INC. AND WYSE TECHNOLOGY L.L.C.); EMC IP HOLDING COMPANY LLC
Reel/Frame 071642/0001 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (052216/0758) Recorded Jun 23, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 060438/0680 →
RELEASE OF SECURITY INTEREST AF REEL 052243 FRAME 0773 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 058001/0152 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 31, 2021
From: KNOPPERT, MICHIEL; GAJIWALA, PRIYANK; VAN VALKENHOEF, FRANK
To: DELL PRODUCTS, LP
Reel/Frame 055789/0313 →
SECURITY INTEREST Recorded Jun 5, 2020
From: DELL PRODUCTS L.P.; EMC CORPORATION; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 053311/0169 →
SECURITY AGREEMENT Recorded Apr 22, 2020
From: CREDANT TECHNOLOGIES INC.; DELL INTERNATIONAL L.L.C.; DELL MARKETING L.P.; DELL PRODUCTS L.P.; DELL USA L.P.; EMC CORPORATION; FORCE10 NETWORKS, INC.; WYSE TECHNOLOGY L.L.C.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A.
Reel/Frame 053546/0001 →
SECURITY AGREEMENT Recorded Mar 26, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 052243/0773 →
PATENT SECURITY AGREEMENT (NOTES) Recorded Mar 24, 2020
From: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS COLLATERAL AGENT
Reel/Frame 052216/0758 →