Student Competition (Technology Innovation) ID 1984861
Bibliographic record
Abstract
Backgrounds/Objective Intraspinal microstimulation (ISMS) is a neuromodulation technique for restoring walking after spinal cord injury. The objective of this study was to fabricate a stretchable ISMS device suitable for pigs, a clinically-relevant animal model. Methods Polyimide-insulated microwires (50µm, Pt-Ir, 80%/20%) were used for fabrication of electrodes. Their tips were de-insulated (∼0.15mm 2 ) and sharpened using nanosecond and femtosecond UV lasers. Microcoils were fabricated from 25μm microwires (Pt-Ir, 80%/20%) to add stretchability to the lead wires. Sixteen microelectrode-leads were connected to a custom, wirelessly controlled stimulator using Medtronic extension cables (Model 37081). The implants were tested in seven domestic pigs and current pulse trains were delivered to various rostro-caudal regions of the lumbar spinal cord (1s, 40Hz, 50µA-300µA) to activate locomotor-related muscle synergies. The kinematics and isometric joint forces of the evoked hindlimb responses were recorded. Results Graded joint movements were evoked with increasing stimulus amplitude. Changes in the hip, knee, and ankle joints angles evoked by ISMS at 300µA were 17.9±1˚, 28.1±1˚, and 21.6±2˚, respectively. Isometric joint forces evoked by ISMS at 300µA were 12.21±0.91N, 7.4±0.71N, and 1.7±0.15N for knee extension, hip flexion, and ankle flexion, respectively. Conclusion The movements evoked using the developed ISMS implant could generate full ranges of motion in the joints. The graded responses imply a near-physiological recruitment order of motoneurons, which is necessary for achieving long walking distances without muscle fatigue. The results show the capability of the developed ISMS device in generating movements in pigs, and the implants’ potential for future use in humans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.875 | 0.723 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".