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Record W103553833

Design of a Haptic Interface for Medical Applications using Magneto-Rheological Fluid based Actuators

2014· article· en· W103553833 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScholarship@Western (Western University) · 2014
Typearticle
Languageen
FieldEngineering
TopicElevator Systems and Control
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHaptic technologyActuatorInterface (matter)MagnetoRheologyComputer scienceMagnetorheological fluidMechanical engineeringControl engineeringSimulationHuman–computer interactionMaterials scienceEngineeringArtificial intelligenceComposite materialMagnetBubble
DOInot available

Abstract

fetched live from OpenAlex

This thesis reports on the design, construction, and evaluation of a prototype two degrees-of-freedom (DOF) haptic interface, which takes advantage of Magneto-Rheological Fluid (MRF) based clutches for actuation. Haptic information provides important cues in teleoperated systems and enables the user to feel the interaction with a remote or virtual environment during teleoperation. The two main objectives in designing a haptic interface are stability and transparency. Indeed, deficiencies in these factors in haptics-enabled telerobotic systems has the introduction of haptics in medical environments where safety and reliability are prime considerations. An actuator with poor dynamics, high inertia, large size, and heavy weight can significantly undermine the stability and transparency of a teleoperated system. In this work, the potential benefits of MRF-based actuators to the field of haptics in medical applications are studied. Devices developed with such fluids are known to possess superior mechanical characteristics over conventional servo systems. These characteristics significantly contribute to improved stability and transparency of haptic devices. This idea is evaluated and verified through both theoretical and experimental points of view. The design of a small-scale MRF-based clutch, suitable for a multi-DOF haptic interface, is discussed and its performance is compared with conventional servo systems. This design is developed into four prototype clutches. In addition, a closed-loop torque control strategy is presented. The feedback signal used in this control scheme comes from the magnetic field acquired from embedded Hall sensors in the clutch. The controller uses this feedback signal to compensate for the nonlinear behavior using an estimated model, based on Artificial Neural Networks. Such a control strategy eliminates the need for torque sensors for providing feedback signals. The performance of the developed design and the effectiveness of the proposed modeling and control techniques are experimentally validated. Next, a 2-DOF haptic interface based on a distributed antagonistic configuration of MRF-based clutches is constructed for a class of medical applications. This device is incorporated in a master-slave teleoperation setup that is used for applications involving needle insertion and soft-tissue palpation. Phantom and in vitro animal tissue were used to assess the performance of the haptic interface. The results show a great potential of MRF-based actuators for integration in haptic devices for medical interventions that require reliable, safe, accurate, highly transparent, and stable force reflection.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.063
GPT teacher head0.288
Teacher spread0.224 · 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