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Record W2042595775 · doi:10.1109/biocas.2007.4463300

Long-term monitoring of electrochemical parameters from stimulated neural tissues

2007· article· en· W2042595775 on OpenAlexaff
Fayçal Mounaïm, Guillaume Lesbros, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCMOSElectrical impedanceTelemetryMaterials scienceDielectric spectroscopyElectronic engineeringIntegrated circuitCyclic voltammetryElectrical engineeringElectrodeOptoelectronicsComputer scienceElectrochemistryEngineeringChemistryTelecommunications

Abstract

fetched live from OpenAlex

The electrode-tissues interface (ETI) is one of the key issues for the safety, reliability and efficiency of implantable devices such as stimulators and sensors. The aim of this paper is to report an implantable telemetry device, based on a full custom integrated circuit (IC) to monitor the ETI. The proposed system performs various types of measurements, such as impedance spectroscopy, cyclic voltammetry, and galvanostatic double pulse method. Hence, the evolution of various electrochemical parameters of the ETI such as complex impedance, faradic resistance, double layer capacity, rheobase current, and chronaxy time, could be monitored long time after implantation. The full custom IC has been designed and fabricated with the CMOS 0.18μm technology. The circuit occupies a silicon area of 2mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and consumes less than 3mW. Characterisation and in-vitro experimental results validate the full functionalities of the implantable monitoring system including the custom IC.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.512

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)0.0000.000

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 head0.040
GPT teacher head0.304
Teacher spread0.264 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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