Systems, articles, and methods for gesture identification in wearable electromyography devices
US9389694B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 21, 2014 |
| Grant date | Jul 12, 2016 |
| Priority date | — |
| Expiry date | Dec 17, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Systems, articles, and methods perform gesture identification with limited computational resources. A wearable electromyography (“EMG”) device includes multiple EMG sensors, an on-board processor, and a non-transitory processor-readable memory that stores data and/or processor-executable instructions for performing gesture identification. The wearable EMG device detects and determines features of signals when a user performs a physical gesture, and processes the features by performing a decision tree analysis. The decision tree analysis invokes a decision tree stored in the memory, where storing and executing the decision tree may be managed by limited computational resources. The outcome of the decision tree analysis is a probability vector that assigns a respective probability score to each gesture in a gesture library. The accuracy of the gesture identification may be enhanced by performing multiple iterations of the decision tree analysis across multiple time windows of the EMG signal data and combining the resulting probability vectors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.