Touch input force estimation using machine learning
US12346516B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 2, 2024 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Jan 2, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Examples are disclosed herein relating to simulating force-sensing functionality for a touch interface using a machine-learning model that is trained based at least on training data generated by a training touch interface including a plurality of force sensors. In one example, a computing system includes a touch interface configured to output a touch heatmap based at least on touch input detected by a plurality of touch sensors of the touch interface. The computing system is configured to execute a machine-learning model that is configured to receive the touch heatmap, output a force estimation of the touch input based at least on analyzing the touch heatmap, and execute a computing operation based at least on the force estimation. The machine-learning model is trained based at least on training data generated by a training touch interface including a plurality of force sensors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.