An Ultralow-Power Crystal-Free Batteryless TDD Radio for Medical Implantable Applications
Bibliographic record
Abstract
This article presents an event-driven ultralowpower radio intended for miniaturized biomedical implants. In its powerlink, the system employs an RF-to-dc converter to scavenge energy from the electromagnetic waves in the 2.4-GHz unlicensed industrial, scientific, and medical (ISM) band. The bidirectional time-division datalink is realized by exploiting the 915-MHz ISM band, and its operation is coordinated by a smart control module, where the cyclic redundancy check is conducted to switch the system between monitoring and interrogation modes. A proof-of-concept radio is fabricated in a 0.13-μm CMOS process with the chip area of 1.4 mm2. Without employing any external components, the radio is robust to process, supply voltage, and body temperature variations, leading to a low-cost and highly integrated wireless solution. During the monitoring mode, the downlink data reception and demodulation are realized by a receiver that consumes 27.5 μW while achieving a sensitivity of -69 and -59 dBm at the data rates of 1 and 100 kb/s, respectively. Dissipating peak power of 49.5 μW in the interrogation mode, the data transmitter delivers an output power of -30.6 dBm with a data rate of 2.5 Mb/s.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".