An integrated low-power asynchronous epileptic seizure detector
Bibliographic record
Abstract
In this paper, we present a new asynchronous seizure detector that is part of an implantable integrated device intended to identify onset seizure and trigger focal treatment to block seizure progression. The proposed system eliminates the unnecessary clock gating during normal neural activity monitoring mode and reduces the total power consumption. The proposed detector includes analog and digital building blocks with a variable time frame and four concurrent variable voltage window detectors to extract seizure onset information. The algorithm is validated in Matlab and the system is implemented in standard 0.13 μm CMOS process. Based on post-layout simulation results, the input referred noise of bioamplifier and the total power consumption of system are 4.4 μVrms and 7.1 μW, respectively. An accurate detection is achieved and no false alarms are recorded during analyzing the iEEG signals of two patients. The average detection delay of 9.5 sec is obtained after seizure onset.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".