Design of a low electrode offset and high CMRR instrumentation amplifier for ECG acquisition systems
Bibliographic record
Abstract
A current feedback instrumentation amplifier (CFIA) for electrocardiogram (ECG) acquisition systems is proposed in this paper. In order to reduce the electrode offset (EOS) and baseline drift, an electrode offset cancellation module is used. Right leg drive (RLD) module is added to improve the common mode rejection ratio (CMRR), suppress common mode interference. An operational transconductance amplifier-capacitor (OTA-C) low-pass filter is integrated at the output of the CFIA to filter out high-frequency noise caused by the ambient environment. The circuit is designed and simulated using a 0.18 μm CMOS process. The circuit operates at 2V and consumes a total current of 47μA. Simulation results show that the CMRR of the circuit can reach 129dB, and the canceled electrode offset voltage is ±200mV.
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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".