A Smart Intra-Oral Wearable for Wireless Electroocoulogram Measurement
Bibliographic record
Abstract
Monitoring electrooculogram (EOG) signal alone is sufficient for accurate sleep-stage classification and thus can be useful for early diagnoses of many diseases. In this paper, we present a smart mouthguard that can monitor intra-oral EOG signals. The device acquires the EOG signal from the inner side and surroundings of the upper and lower lip areas. No previous work has reported intra-oral wearables for measuring EOG signals. The proposed smart mouthguard comprises of two sub-mouthguards, five soft conductive fabric electrodes, and an EOG measurement board implemented on a flexible substrate. The measurement system is battery-operated and sends EOG data wirelessly. The quality of the EOG signal acquired by the smart mouthguard is good enough to clearly determine and differentiate the processed intra-oral EOG signal patterns corresponding to different eye activities. With its comfort, low cost, and reliable wireless transmission, the EOG mouthguard has great potential for EOG-based sleep monitoring.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".