Recognizing gestures from forearm EMG signals
US8447704B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 26, 2008 |
| Grant date | May 21, 2013 |
| Priority date | — |
| Expiry date | Jun 8, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F3/017
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine learning model is trained by instructing a user to perform proscribed gestures, sampling signals from EMG sensors arranged arbitrarily on the user's forearm with respect to locations of muscles in the forearm, extracting feature samples from the sampled signals, labeling the feature samples according to the corresponding gestures instructed to be performed, and training the machine learning model with the labeled feature samples. Subsequently, gestures may be recognized using the trained machine learning model by sampling signals from the EMG sensors, extracting from the signals unlabeled feature samples of a same type as those extracted during the training, passing the unlabeled feature samples to the machine learning model, and outputting from the machine learning model indicia of a gesture classified by the machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.