Design and Implementation of a Wearable, Wireless EEG Recording System
Bibliographic record
Abstract
Biosensor monitoring systems have been attracted great interest, stimulated by recent, significant advances in electronic, communications and information technologies. For instance, electroencephalography (EEG) is the most studied potential non-invasive interface in brain-computer interface (BCI), a hot topic aiming at creating a direct link between the brain and a computer. However, most BCI systems use bulky and wired EEG measurements, which is uncomfortable and inconvenient for users to perform daily-life tasks in. To address this concern, in this paper, we develop a wearable, wireless EEG acquisition and recording system, including a data acquisition unit and a data transmission and receiving unit. Our testing results show that the proposed design is effective with high common-mode rejection ratio (CMRR). The developed EEG system is suitable for biomedical applications such as patient monitoring and BCI.
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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 | 0.000 |
| 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".