Bibliographic record
Abstract
Neuroprostheses (NPs) are electrical stimulators that activate nerves, either to provide sensory input to the central nervous system (sensory NPs), or to activate muscles (motor NPs: MNPs). The first MNPs were belts with inbuilt batteries and electrodes developed in the 1850s to exercise the abdominal muscles. They became enormously popular among the general public, but as a result of exaggerated therapeutic claims they were soon discredited by the medical community. In the 1950s, MNPs reemerged for the serious purpose of activating paralyzed muscles. Neuromuscular electrical stimulation (NMES), when applied in a preset sequence, is called therapeutic electrical stimulation (TES). NMES timed so that it enhances muscle contraction in intended voluntary movements is called functional electrical stimulation (FES) or functional neuromuscular stimulation (FNS). It has been 50 years since the first FES device, a foot-drop stimulator, was described and 40 years since the first implantable version was tested in humans. A commercial foot-drop stimulator became available in the 1970s, but for various reasons, it failed to achieve widespread use. With advances in technology, such devices are now more convenient and reliable. Enhancing upper limb function is a more difficult task, but grasp-release stimulators have been shown to provide significant benefits. This chapter deals with the technical aspects of NMES, the therapeutic and functional benefits of TES and FES, delayed-onset and carryover effects attributable to "neuromodulation" and the barriers and opportunities in this rapidly developing field. © 2019 American Physiological Society. Compr Physiol 9:127-148, 2019.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.017 |
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".