A 0.9 V, Ultra-Low-Power OTA with Low NEF and High CMRR for Batteryless Biomedical Front-Ends
Bibliographic record
Abstract
This paper presents a new operational transconductance amplifier (OTA) design for batteryless biomedical front-ends. The proposed OTA operates in the subthreshold region and utilizes self-cascode devices to achieve ultra-low power, low noise, and a high common-mode rejection ratio (CMRR). Post-layout simulations in Cadence, using 45 nm CMOS technology with 0.9 V supply voltage, show a power consumption of 49.3 nW, a CMRR of 144.9 dB, an input-referred noise of 4.51 μVrms integrated over 0.5–208 Hz, and a noise efficiency factor of 1.023 with a core silicon area of 0.00138 mm2. Using the proposed OTA, we implemented a 10-channel neural recording amplifier for Local Field Potentials (LFPs) based on a capacitively coupled, capacitive-feedback (CC-CF) topology with a body-driven pseudo-resistor high-pass path. The system achieves a total CMRR ≥ 70 dB and an estimated power of 494.2 nW for 10 channels. Compared with prior art, the proposed OTA offers competitive noise efficiency and common-mode rejection at lower power, making it a viable building block for batteryless neural and biomedical sensing front-ends.
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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".