System and machine learning method for detecting input device distance from touch sensitive surfaces
US11287926B1 · kind B1 · utility
8Cited by
7References
20Claims
0Family size
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Key dates
| Filing date | Jan 28, 2021 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Jan 28, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2203/04101
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some examples, an electronic device can use machine learning techniques, such as convolutional neural networks, to estimate the distance between a stylus tip and a touch sensitive surface (e.g., stylus z-height). A subset of stylus data sensed at electrodes closest to the location of the stylus at the touch sensitive surface including data having multiple phases and frequencies can be provided to the machine learning algorithm. The estimated stylus z-height can be compared to one or more thresholds to determine whether or not the stylus is in contact with the touch sensitive surface.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.