Name
Abstract | ||
|---|---|---|
With attention to voluntary tongue motion, which is capable of communicating the intentions of a person with a disability, we estimated the position and contact force of the tongue simultaneously using EMG signals of the underside of the jaw. We affixed a multi-channel electrode with nine electrodes to the underside of the jaw. Then, deriving many EMG signals using monopolar leads, we calculated 36 (= 9C2) channel EMG signals between any two of the nine electrodes. Associating these EMG signals and tongue movement using a neural network, we confirmed our ability to estimate the tongue position and contact force with precision, with a correlation coefficient greater than 0.9 and RMS error less than 10%. Furthermore, building a neural network estimating deglutition, yawning, and mouth opening, which are potential origins of false estimation, and introducing mask processing to reduce estimation error in voluntary tongue movement more than 95%, we suggest precise extraction of only the signal of that movement from EMG signals obtainable from the underside of the jaw. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MHS.2011.6102222 | Micro-NanoMechatronics and Human Science |
Keywords | Field | DocType |
biomechanics,biomedical electrodes,electromyography,neural nets,EMG signals,RMS error,deglutition,mouth opening,multichannel electrode,neural network,suprahyoid muscle activity,tongue movement,tongue position,voluntary tongue motion,yawning | Computer vision,Suprahyoid muscles,Contact force,Electromyography,Speech recognition,Control engineering,Artificial intelligence,Biomechanics,Tongue movement,Materials science,Tongue | Conference |
ISSN | ISBN | Citations |
Pending | 978-1-4577-1360-6 | 5 |
PageRank | References | Authors |
0.78 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minoru Sasaki | 1 | 78 | 18.29 |
| Tetsuo Arakawa | 2 | 46 | 6.93 |
| Atsushi Nakayama | 3 | 10 | 2.27 |
| G Obinata | 4 | 15 | 4.16 |