Name
Abstract | ||
|---|---|---|
We investigated the possibility of creating a temporal representation of brain activity from fNIRS signals. In an experiment, subjects performed isometric arm movements in four directions, and fNIRS signals were measured over the primary motor area in the left hemisphere of their brain. We estimated the direction of the arm force from the fNIRS signals by using two classifiers: sparse linear regression (SLR) and support vector machine(SVM). Classification accuracy was approximately 70% with SLR. The temporal distribution of the features selected with SLR was the same as those selected with SVM. The results indicated that the fNIRS signals possibly included information about arm force direction in 4-6 [s] after stimulus onset and offset. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IEMBS.2011.6091729 | EMBC |
Keywords | Field | DocType |
biomechanics,arm force direction,stimulus offset,primary motor area,brain activity,stimulus onset,sparse matrices,regression analysis,sparse linear regression,electroencephalography,medical signal processing,isometric arm movements,infrared spectra,feature extraction,support vector machine,fnirs signals,signal classification,temporal distribution,classifiers,temporal representation,left hemisphere,feature selection,eeg,support vector machines,force,estimation,linear regression,accuracy | Computer vision,Lateralization of brain function,Pattern recognition,Computer science,Support vector machine,Brain activity and meditation,Feature extraction,Atmospheric measurements,Artificial intelligence,Isometric exercise,Electroencephalography,Linear regression | Conference |
Volume | ISSN | ISBN |
2011 | 1557-170X | 978-1-4244-4122-8 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yasuyuki Muto | 1 | 0 | 0.34 |
| Taiki Ishii | 2 | 0 | 0.34 |
| Shuichi Matsuzaki | 3 | 0 | 0.34 |
| Yasuhiro Wada | 4 | 0 | 1.35 |