Comparison of Classification Accuracies Between Different Brain Areas During a Two-Class Motor Imagery in a fNIRS Based BCI
Bibliographic record
Abstract
This study examined functional near infrared spectroscopy (fNIRS) data from 29 participants to determine whether the classification accuracy associated with a motor imagery task depended on different areas of the brain. The fNIRS was used to measure concentration changes of oxy- (HbO) and deoxyhemoglobin (HbR). The averages of HbO (mHbO) and HbR (mHbR) were used as features, and linear discriminant analysis (LDA) and support vector machine (SVM) were used as classifiers. The results showed significantly higher classification accuracies for the motor cortex than both frontal and occipital areas, but less accuracy compared to all channels. Furthermore, while SVM resulted in higher accuracy than LDA, mHbO and mHbR led to similar accuracies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".