Mechanical Analysis of Human DBS Electrodes
Bibliographic record
Abstract
Deep brain stimulation (DBS) electrodes have been proved to be effective in treating neural related diseases in rodents. These devices were successfully extended to the field of human neuro therapy. Many different electrodes exist. However, no quantitative ranking criterion is available to allow meaningful comparison of the various DBS electrodes to aid the designer. This paper presents a novel Figure of Merit (FOM) dedicated to DBS electrodes. The proposed optimization performance takes into account safety factors of mechanical analysis and the estimated fabrication cost of some materials. The FOM is used to rank several DBS electrode designs. Finite Element Models (FEM) analysis for several electrode layouts are conducted. FEM shows the effects of different design parameters on the electrode mechanical performance. These parameters include electrode dimensions, geometry, and materials. The electrodes mechanical analysis is evaluated from different points of view including: linear buckling analysis, stationary analysis with axial and shear loading. The safety factors are calculated for several designs with different materials (brittle and ductile materials). The results obtained from FEM mechanical analysis for the various electrodes prototypes are presented, which provide guidelines for different electrode designs and material choice. A proposed fabrication process along with an estimated fabrication cost is also introduced.
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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 | 0.002 |
| 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".