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A Wearable High-Voltage Functional Electrical Stimulator with Sub-20 ns Switching Time for Stimulation with Reduced Pain

2024· article· en· W4405709508 on OpenAlexaff
R. Tang, Haiduo Wang, Bruno Leitão-Almeida, Xilin Liu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStimulationFunctional electrical stimulationWearable computerMaterials scienceVoltageElectrical engineeringOptoelectronicsComputer scienceBiomedical engineeringMedicineEmbedded systemPsychologyEngineeringNeuroscience

Abstract

fetched live from OpenAlex

This paper presents a wearable high-voltage functional electrical stimulation (FES) device. Compared to conventional FES devices, the proposed design aims to offer users a more comfortable therapeutic experience. This is enabled by achieving a sub- 20 ns fast switching time, activating muscles but fewer pain receptors. The FES device is equipped with a high compliance voltage up to 135 V, designed to accommodate different muscle groups and is suitable for users with varying skin conductance levels. At the core of the FES system is a switched capacitor (SC) stimulator for fast switching, and a flyback converter responsible for stepping up the battery voltage. The system incorporates only off-the-shelf components, which significantly lowers the prototyping cost. The proposed design methods are applicable across a wide range of applications in neural rehabilitation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.231
Teacher spread0.214 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes1
Has abstractyes

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