IP Library Granted Patent US 12,197,668
Granted Patent B2
US 12,197,668 · App. 18/450,771 · Granted Jan 14, 2025

Systems and methods for touch sensing on devices including regions with and without touch electrodes

Inventors: Dor Shaviv (Fremont, CA); Behrooz Shahsavari (Hayward, CA); David S. Graff (San Francisco, CA); Baboo V. Gowreesunker (Mountain View, CA); Nima Ferdosi (San Jose, CA); Yash S. Agarwal (San Francisco, CA); Sai Zhang (Sunnyvale, CA)
Assignee: Apple Inc.
G06F3/0412G06F3/04186G06F2203/04101
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Quick Facts
Patent No.
US 12,197,668
App. No.
18/450,771
Granted
Jan 14, 2025
Kind
B2
Abstract

Touch sensor panels/screens can include a first region having a plurality of touch electrodes and a second region without touch electrodes. In some examples, to improve touch sensing performance, a first algorithm or a second algorithm is applied to determine whether an object corresponding to the touch patch is in contact with the touch screen. Whether to apply the first algorithm or the second algorithm is optionally dependent on the location of the touch patch.

Claims (44)

1. An electronic device, comprising:

a touch screen comprising:

a first region including a plurality of touch electrodes and a second region including an area without electrodes that can detect touch, wherein a first plurality of touch nodes of the touch screen is in the first region and a second plurality of touch nodes is at least partially in the second region; and

a processing circuitry configured to:

detect a touch patch on the touch screen;

in accordance with a determination that the touch patch is in the first region, apply a first algorithm to determine a location of the touch patch within the first region of the touch screen; and

in accordance with a determination that the touch patch is in the second region, apply a second algorithm, different from the first algorithm, to determine a location of the touch patch within the second region of the touch screen.

2. The electronic device of claim 1 , wherein the first algorithm applies a threshold to a first feature computed from a touch image and wherein the second algorithm includes a machine learning model.

3. The electronic device of claim 2 , wherein the machine learning model is configured to apply a linear model or a non-linear model to a plurality of features computed from the touch image and from the touch patch.

4. The electronic device of claim 1 , wherein the second region is in a same plane as the first region.

5. The electronic device of claim 1 , wherein the second region is surrounded by the first region.

6. The electronic device of claim 1 , further comprising:

one or more routing traces along a periphery of the second region, wherein the one or more routing traces electrically couple one or more of a first plurality of touch electrode segments in a first of the second plurality of touch nodes to one or more of a second plurality of touch electrode segments in a second of the second plurality of touch nodes.

7. The electronic device of claim 1 , wherein:

the first plurality of touch nodes of the touch screen includes a first plurality of touch electrode segments that are configured to sense a touch signal;

the second plurality of touch nodes of the touch screen includes a second plurality of touch electrode segments that are configured to sense a touch signal; and

an area of the second plurality of touch electrode segments of one of the second plurality of touch nodes is smaller than an area of the first plurality of touch electrode segments of one of the first plurality of touch nodes.

8. The electronic device of claim 1 , wherein the second algorithm includes as input an output of a segmentation process or one or more features extracted from the output of the segmentation process.

9. The electronic device of claim 8 , wherein the one or more extracted features include patch level features.

10. The electronic device of claim 1 , wherein the second algorithm includes as input an output of a post-segmentation process or one or more features extracted from the output of the post-segmentation process.

11. The electronic device of claim 10 , wherein the second algorithm includes a second feature computed from the output of the post-segmentation process that is not used input for the first algorithm.

12. The electronic device of claim 1 , wherein the second algorithm includes a boosted decision tree classifier, a logistic regression classifier, or a support vector machine.

13. The electronic device of claim 1 , wherein applying the second algorithm in the second region reduces a rate misclassifying a patch corresponding to a hovering object as a touch compared with the first algorithm.

14. The electronic device of claim 1 , wherein applying the second algorithm in the second region reduces a rate of misclassifying a patch corresponding to a touching object as a hover compared with the first algorithm.

15. The electronic device of claim 1 , wherein the second region corresponds to an optical sensor.

16. The electronic device of claim 1 , wherein the second region is without display pixels.

17. The electronic device of claim 1 , the touch screen further comprising a third region including a second area without touch electrodes, wherein the area of the second region is a different size than the second area of the third region, and wherein the second plurality of touch nodes is partially in the second region or at least partially in the third region.

18. The electronic device of claim 1 , wherein:

the first plurality of touch nodes of the touch screen includes a first plurality of touch electrodes segments that are configured to sense one or more first touch signals;

the second plurality of touch nodes of the touch screen includes a second plurality of touch electrode segments that are configured to sense one or more second touch signals; and

the one or more first touch signals corresponding to an object touching the first plurality of touch nodes is greater than the one or more second touch signals corresponding to an object touching the second plurality of touch nodes.

19. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device including a touch screen comprising a first region including a plurality of touch electrodes and a second region including an area without electrodes that can detect touch, cause the electronic device to:

detect a touch patch on the touch screen;

in accordance with a determination that the touch patch is in the first region, apply a first algorithm to determine a location of the touch patch within the first region of the touch screen; and

in accordance with a determination that the touch patch is in the second region, apply a second algorithm including a machine learning model, different from the first algorithm, to determine a location of the touch patch within the second region of the touch screen.

20. The non-transitory computer readable storage medium of claim 19 , wherein the first algorithm applies a threshold to a first feature computed from a touch image.

21. The non-transitory computer readable storage medium of claim 20 , wherein the machine learning model is configured to apply a linear model or a non-linear model to a plurality of features computed from the touch image and from the touch patch.

22. The non-transitory computer readable storage medium of claim 19 , wherein the second region is in a same plane as the first region and the second region is surrounded by the first region.

23. A method comprising:

at an electronic device including one or more processors and a touch screen comprising a first region including a plurality of touch electrodes and a second region including an area without electrodes that can detect touch:

detecting a touch patch on the touch screen;

in accordance with a determination that the touch patch is in the first region, applying a first algorithm to determine a location of the touch patch within the first region of the touch screen; and

in accordance with a determination that the touch patch is in the second region, applying a second algorithm, different from the first algorithm, to determine a location of the touch patch within the second region of the touch screen.

24. The method of claim 23 , wherein the first algorithm applies a threshold to a first feature computed from a touch image and wherein the second algorithm includes a machine learning model.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 16, 2023
From: ZHANG, SAI; SHAHSAVARI, BEHROOZ; GRAFF, DAVID S.; GOWREESUNKER, BABOO V.; FERDOSI, NIMA; AGARWAL, YASH S.; SHAVIV, DOR
To: APPLE INC.
Reel/Frame 064612/0617 →
Continuity (2)
Provisional Application 63374744 · Sep 6, 2022
Related Publication 20240077965A1 · Mar 7, 2024
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