Functional electrical stimulation using microstimulators to correct foot drop: a case study
Bibliographic record
Abstract
This paper presents a case study that tested the feasibility and efficacy of using injectable microstimulators (BIONs) in a functional electrical stimulation (FES) device to correct foot drop. Compared with surface stimulation of the common peroneal nerve, stimulation with BIONs provides more selective activation of specific muscles. For example, stimulation of the tibialis anterior (TA) and extensor digitorum longus (EDL) muscles with BIONs produces ankle flexion without excessive inversion or eversion of the foot (i.e., balanced flexion). Efficacy was assessed using a 3-dimensional motion analysis of the ankle and foot trajectories during walking with and without stimulation. Without stimulation, the toe on the affected leg drags across the ground. BION stimulation of the TA muscle and deep peroneal nerve (which innervates TA and EDL) elevates the foot such that the toe clears the ground by 3 cm, which is equivalent to the toe clearance in the less affected leg. The physiological cost index (PCI) measured effort during walking. The PCI equals the change in heart rate (from rest to activity) divided by the walking speed; units are beats per metre. The PCI is high without stimulation (2.29 +/- 0.37, mean +/- SD) and greatly reduced with surface (1.29 +/- 0.10) and BIONic stimulation (1.46 +/- 0.24). Also, walking speed increased from 9.4 +/- 0.4 m/min without stimulation to 19.6 +/- 2.0 m/min with surface and 17.8 +/- 0.7 m/min with BIONic stimulation. These results suggest that FES delivered by a BION is an alternative to surface stimulation and provides selective control of muscle activation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".