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Record W2156696972 · doi:10.1109/biorob.2008.4762778

Wave variables based bilateral teleoperation of an active catheter

2008· article· en· W2156696972 on OpenAlexaff
Jagadeesan Jayender, Rajni V. Patel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsTeleoperationCatheterActuatorStrain gaugeComputer scienceControl theory (sociology)SimulationHaptic technologyPosition (finance)TransducerControl engineeringRobotEngineeringArtificial intelligenceSurgeryAcousticsControl (management)MedicineStructural engineeringPhysics

Abstract

fetched live from OpenAlex

In this paper, we develop a teleoperation framework to perform master-slave control of an active catheter instrumented with Shape Memory Alloy (SMA) actuators. The catheter is also instrumented with a 5-DOF magnetic sensor which provides feedback on the position of the distal end of the catheter while strain gauges on the catheter tip reflect the forces. SMAs demonstrate a hysteretic, non-linear and time-delayed behavior; therefore maintaining stability of the teleoperation algorithm is a prime requirement. The wave variables based approach provides a robust method to perform bilateral teleoperation of the active catheter. The clinician controls the position of the tip of the catheter from a remote location while precisely feeling the forces acting on the catheter tip. This enables the clinician to perform fine manipulations within the blood vessels, close to bifurcations and to the site of plaque buildup. In addition, a force control algorithm has been developed and implemented on the active catheter for enabling smooth guidance of the catheter into the vasculature and for application in cardiac ablation. Experimental results are presented for the proposed algorithms.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.513

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 head0.020
GPT teacher head0.199
Teacher spread0.179 · 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 designSimulation or modeling
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

Citations8
Published2008
Admission routes1
Has abstractyes

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