Name
Title | ||
|---|---|---|
Motion classification by epidural potential measurement of rat for low-invasive brain-machine interface |
Abstract | ||
|---|---|---|
A low-invasive method to record neural activity is required for safe and practical brain-machine interfaces (BMI). BMIs are expected to be used to reintegrate motor functions of physically disabled persons; however, conventional invasive methods require electrodes inside the dura mater. In this study, the authors used epidural electrodes, which are located between the skull and dura mater, to record rat neural activity for low-invasive BMI. The signals were analyzed using short-time Fourier transform, and the power spectra were classified into rat motions by an artificial neural network. The accuracy was approximately 70% in two-motion classifications according to the tested electrodes' locations and frequency bands. The results indicated the feasibility of low-invasive BMI using epidural electrodes. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ROBIO.2009.4913311 | ROBIO |
Keywords | Field | DocType |
Fourier transforms,biomedical electrodes,man-machine systems,neural nets,Fourier transform,artificial neural network,bio electrode,epidural potential measurement,low-invasive brain-machine interface,motion classification,pattern recognition,power spectra,rat motions,Artificial neural network,Bio electrode,Brain-machine interface,Pattern recognition | Biomedical engineering,Dura mater,Brain–computer interface,Neural activity,Engineering,Artificial neural network | Conference |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takeshi Uejima | 1 | 0 | 0.34 |
| Toshiyuki Fujii | 2 | 0 | 1.69 |
| Hiroshi Yokoi | 3 | 383 | 92.58 |
| Masatoshi Takita | 4 | 0 | 1.01 |