Detection of Hand Extension Movements in the Context of a 3-State Asynchronous Brain Interface
Bibliographic record
Abstract
The low-frequency asynchronous switch design (LF-ASD) is a direct brain interface (BI) that detects the presence of a specific finger movement in the ongoing EEG. Asynchronous interfaces have the advantage of being operational at all times and not only at specific system-defined periods. In this paper, we present the design of a 3-state asynchronous BI for the detection of two different movements from the ongoing EEG. The proposed 3-state asynchronous BI detects right and left hand extensions. Using data collected from two able-bodied individuals, it is shown that the error characteristics of the new system in detecting the presence of movement are significantly better than the 2-state LF-ASD, with true positive rate increases of up to 22.4% for false positive rates in the 1-2% range. An average performance of 61.5% was achieved in differentiating between left and right hand movements
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".