Feasibility of Triboelectric Energy Harvesting and Load Sensing in Total Knee Replacement
Bibliographic record
Abstract
The main goal of this paper is to investigate the feasibility of a triboelectric mechanism to harvest electrical energy for powering a knee implant load measurement sensor under walking activity of daily living. A triboelectric energy harvester is proposed to be placed in between the tibial tray and the UHMWPE bearing of the TKR. To characterize the triboelectric generator, the walking tibiofemoral axial load is approximated as a 1 Hz sine wave signal. An MTS 858 II servo-hydraulic load frame setup is used to transfer the axial load to the triboelectric generator. The optimal resistance is extracted experimentally and found to be 58MΩ. With an applied cyclic load of 2.3 kN at 1 Hz, which is equivalent to the load from normal walking, the generator generated a maximum output of 18 V, and 6 μW of power at the optimal resistance. A power management and digitization circuit is designed based on the harvester output that consumes about 4.74 μW power, which is less than the generated power. Thus, the power harvested from the triboelectric energy harvester can power the load sensing circuitry.
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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 | 0.001 |
| 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) | 0.001 | 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 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".