New functional electrical stimulation approaches to standing and walking
Bibliographic record
Abstract
Spinal cord injury (SCI) is a devastating neurological trauma that is prevalent predominantly in young individuals. Several interventions in the areas of neuroregeneration, pharmacology and rehabilitation engineering/neuroscience are currently under investigation for restoring function after SCI. In this paper, we focus on the use of neuroprosthetic devices for restoring standing and ambulation as well as improving general health and wellness after SCI. Four neuroprosthetic approaches are discussed along with their demonstrated advantages and their future needs for improved clinical applicability. We first introduce surface functional electrical stimulation (FES) devices for restoring ambulation and highlight the importance of these devices for facilitating exercise activities and systemic physiological activation. Implanted muscle-based FES devices for restoring standing and walking that are currently undergoing clinical trials are then presented. The use of implanted peripheral nerve intraneural arrays of multi-site microelectrodes for providing fine and graded control of force during sit-to-stand maneuvers is subsequently demonstrated. Finally, intraspinal microstimulation (ISMS) of the lumbosacral spinal cord for restoring standing and walking is introduced and its results to date are presented. We conclude with a general discussion of the common needs of the neuroprosthetic devices presented in this paper and the improvements that may be incorporated in the future to advance their clinical utility and user satisfaction.
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 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".