High-CMRR Low-Noise Fully Integrated Front-End for EEG Acquisition Systems
Bibliographic record
Abstract
We present in this paper a fully integrated low-noise high common-mode rejection ratio (CMRR) logarithmic programmable gain amplifier (LPGA) and chopped LPGA circuits for EEG acquisition systems. The proposed LPGA is based on a rail-to-rail true logarithmic amplifier (TLA) stage. The high CMRR achieved in this work is a result of cascading three amplification stages to construct the LPGA in addition to the lower common-mode gain of the proposed logarithmic amplification topology. In addition, the 1 / f noise and the inherent DC offset voltage of the input transistors are reduced using a chopper stabilization technique. The CMOS 180 nm standard technology is used to implement the circuits. Experimental results for the integrated LPGA show a CMRR of 140 dB, a differential gain of 37 dB, an input-referred noise of 0.754 μ Vrms, a 189 μ W power consumption from 1.8 V power supply and occupies an active area of 0.4 mm 2 .
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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".