User-customizable machine-learning in radar-based gesture detection
US11080556B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 6, 2016 |
| Grant date | Aug 3, 2021 |
| Priority date | — |
| Expiry date | Oct 12, 2038 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04Q2209/883
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various embodiments dynamically learn user-customizable input gestures. A user can transition a radar-based gesture detection system into a gesture-learning mode. In turn, the radar-based gesture detection system emits a radar field configured to detect a gesture new to the radar-based gesture detection system. The radar-based gesture detection system receives incoming radio frequency (RF) signals generated by the outgoing RF signal reflecting off the gesture, and analyzes the incoming RF signals to learn one or more identifying characteristics about the gesture. Upon learning the identifying characteristics, the radar-based gesture detection system reconfigures a corresponding input identification system to detect the gesture when the one or more identifying characteristics are next identified, and transitions out of the gesture-learning mode.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.