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Record W2073594263 · doi:10.1109/iembs.2011.6090834

First permanent human implant of the Stimulus Router System, a novel neuroprosthesis: Preliminary testing of a polarity reversing stimulation technique

2011· article· en· W2073594263 on OpenAlexafffund
Liu Shi Gan, Einat Ravid, Jan Kowalczewski, Michel Gauthier, Jaret L. Olson, Michael Morhart, A. Procházka

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsReversingNeuroprostheticsStimulationStimulus (psychology)Polarity (international relations)RouterComputer scienceImplantNeuroscienceEngineeringPsychologyMedicineChemistryCognitive psychologyComputer networkMechanical engineering

Abstract

fetched live from OpenAlex

Neuroprostheses (NPs) are electrical stimulators that help to restore sensory or motor functions lost as a result of neural damage. The Stimulus Router System (SRS) is a new type of NP developed in our laboratory. The system uses fully implanted, passive leads to "capture" and "route" some of the current flowing between pairs of surface electrodes to the vicinity of the target nerves, hence eliminating the need for an implanted stimulator. In June 2008, 3 SRS leads were implanted in a tetraplegic man for restoration of grasp and release. To reduce the size of the external wristlet and thereby optimize usability, we recently implemented a polarity reversing stimulation technique that allowed us to eliminate a reference electrode. Selective activation of three target muscles was achieved by switching the polarities of the stimulus current delivered between pairs of surface electrodes located over the pick-up terminals of the implanted leads and reducing the amplitude of the secondary phases of the stimulus pulses.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.081
GPT teacher head0.251
Teacher spread0.170 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2011
Admission routes2
Has abstractyes

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