Name
Title | ||
|---|---|---|
Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks |
Abstract | ||
|---|---|---|
As a promising non-invasive technique, functional near-infrared spectroscopy(fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery(MI)based on fNIRS. 10 healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex(PFC). The combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis(ICA) method was used to solve the signal-noise frequency spectrum aliasing issues caused by Mayer wave(0.1Hz), then the signal means(SM) features were extracted as an input of Support Vector Machine(SVM) classifier. The average accuracies of 4 directions, up-down and left-right were 40.55%, 73.05%, 70.7% respectively using Hbo2(8-21s). This study demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/BIBM.2017.8217676 | 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) |
Keywords | DocType | ISSN |
cortical brain activities,multiclass classification,multichannel continuous-wave fNIRS equipment,Mayer wave,orbitofrontal cortex,motor imagery tasks,functional near-infrared spectroscopy,prefrontal cortex,Ensemble Empirical Mode Decomposition,Independent Component Analysis,Support Vector Machine,fNIRS signal single-trial classification,ICA method,signal-noise frequency spectrum,SVM classifier,feature extraction,frequency 0.1 Hz | Conference | 2156-1125 |
ISBN | Citations | PageRank |
978-1-5090-3051-4 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hong Peng | 1 | 81 | 11.42 |
| Jinlong Chao | 2 | 0 | 1.69 |
| Yongzong Wang | 3 | 0 | 0.34 |
| Bin Hu | 4 | 778 | 107.21 |
| Dennis Majoe | 5 | 68 | 10.20 |