Brain Decoding
Motor Brain Decoding is fundamental task for building motor brain computer interfaces (BCI).
Progress in predicting finger movements based on brain activity allows us to restore motor functions and improve rehabilitation process of patients.
Papers
Showing 71–80 of 118 papers
All datasetsBCI Competition IV: ECoG to Finger MovementsStanford ECoG library: ECoG to Finger Movements
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FingerFlex | Pearson Correlation | 0.67 | — | Unverified |
| 2 | Gradient boosted trees on Riemannian features | Pearson Correlation | 0.53 | — | Unverified |
| 3 | Multi purpose CNN | Pearson Correlation | 0.52 | — | Unverified |
| 4 | CNN-LSTM | Pearson Correlation | 0.52 | — | Unverified |
| 5 | Linear regression based on band-specific ECoG | Pearson Correlation | 0.48 | — | Unverified |
| 6 | Interpretable Compact CNN | Pearson Correlation | 0.45 | — | Unverified |
| 7 | Switching linear models | Pearson Correlation | 0.43 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FingerFlex | Pearson Correlation | 0.49 | — | Unverified |