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Motor Neuroprostheses

2019· article· en· W4409143805 on OpenAlexaff
A. Procházka

Bibliographic record

VenueComprehensive physiology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
Fundersnot available
KeywordsNeuroscienceMedicineBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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.

Opus teacher head0.040
GPT teacher head0.262
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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