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Record W6990386893

Design of miniaturized coil system using MEMS technology for eye movement measurement

2009· dissertation· en· W6990386893 on OpenAlexfundaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typedissertation
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsnot available
FundersMcGill University
KeywordsElectromagnetic coilVoice coilInductive sensorMicroelectromechanical systemsSearch coilEye movementGyroscopeEye tracking on the ISSEye tracking
DOInot available

Abstract

fetched live from OpenAlex

Application of eye movement measurement is especially significant in Neuroscience.Results from eye tracking can give valuable insight into the correlation between neural activity and eye movements.Abnormalities in the eye movements also provide information regarding diagnosis and progress of neurological diseases such as dementia.Another application is in developing human-computer interfaces as a means of communication for the severely handicapped.Although there are numerous eye tracking techniques available, the magnetic search coil method has been prominently used by researchers due to its high accuracy and precision.This technique typically requires the subjects head to be fixed for accurate measurements due to the use of large field coils.Here we propose a miniaturized coil system using MEMS technology for application in eye movement measurement.The coils were designed and modeled using CoventorWare and MagNet software.The microcoils were then fabricated in the McGill Nanotools microfabrication laboratory.We present the results for using the materials Indium Tin Oxide (ITO) and Aluminium for the fabrication of coils.We found that the resulting coil system is capable of identifying displacements along the X, Y and Z axis.The resolution of the system depends on the configuration of the system, it was calculated to be around 20-40 m on the plane of the coil and it increases near the centre of the coil.Although the proposed coil system holds significant potential, but further exhaustive testing needs to be performed in an environment simulating eye movements.iii RSUM O Mesurer avec prcision les mouvements oculaires constitue un lment essentiel dans ledomaine de la neuroscience.Par exemple, capter les mouvemets de l'oeil contribue la comprhension de la relation entre les activits neuronales et le comportement oculaire.De meme, les irrgularits observes dans les mouvements des yeux aident diagnostiquer et surveiller le progrs de plusieurs troubles mentaux comme la dmence.En plus, le tracement de la trajectoire oculaire peut tre utilis pour construire des interfaces homme-machine pour les personnes svrement handicapes.Bien que plusieurs techniques de tracement oculaire existent dj, la bobine de recherche magntique est fortement utilise par les chercheurs.Elle offre une haute exactitude et une trs bonne prcision de mesure.La technique traditionnelle exige l'utilisation de grandes bobines de champs, ncessitant ainsi que la tte du sujet soit fixe en tout temps.En revanche, on propose l'utilisation d'un systme de bobines miniaturises construit avec la technologie MEMS.Les bobines ont t conues l'aide des logiciels CoventorWare et MagNet.Les micro-bobines ont t fabriques dans le laboratoire de micro-fabrication Nanotools de l'Universit McGill.On prsente les rsultats obtenus en utilisant des micro-bobines construites avec la solution solide de l'oxyde de l'tain et l'oxyde de l'indium (ITO).Le systme de micro-bobine est capable d'identifier les dplacements dans les trois dimensions X, Y, et Z. La rsolution du systme dpend de la configuration utilise.On a trouv que la rsolution peut tre entre 20 et 40 m.Le systme propos est trs promettant mais plusieurs tests exhaustifs deraient encore tre iv appliques dans des environnements qui simulent de vrais mouvements oculaires.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
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 head0.261
Teacher spread0.221 · 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.

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

Citations0
Published2009
Admission routes2
Has abstractyes

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