Design of miniaturized coil system using MEMS technology for eye movement measurement
Bibliographic record
Abstract
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 μm 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 RÉSUMÉ O Mesurer avec précision les mouvements oculaires constitue un élément essentiel dans ledomaine de la neuroscience.Par exemple, capter les mouvemets de l'oeil contribue à la compréhension de la relation entre les activités neuronales et le comportement oculaire.De meme, les irrégularités observées dans les mouvements des yeux aident à diagnostiquer et à surveiller le progrès de plusieurs troubles mentaux comme la démence.En plus, le tracement de la trajectoire oculaire peut être utilisé pour construire des interfaces homme-machine pour les personnes sévèrement handicapées.Bien que plusieurs techniques de tracement oculaire existent déjà, la bobine de recherche magnétique est fortement utilisée par les chercheurs.Elle offre une haute exactitude et une très bonne précision de mesure.La technique traditionnelle exige l'utilisation de grandes bobines de champs, nécessitant ainsi que la tête du sujet soit fixée en tout temps.En revanche, on propose l'utilisation d'un système de bobines miniaturisées construit avec la technologie MEMS.Les bobines ont été conçues à l'aide des logiciels CoventorWare et MagNet.Les micro-bobines ont été fabriquées dans le laboratoire de micro-fabrication Nanotools de l'Université McGill.On présente les résultats obtenus en utilisant des micro-bobines construites avec la solution solide de l'oxyde de l'étain et l'oxyde de l'indium (ITO).Le système de micro-bobine est capable d'identifier les déplacements dans les trois dimensions X, Y, et Z. La résolution du système dépend de la configuration utilisée.On a trouvé que la résolution peut être entre 20 et 40 μm.Le système proposé est très promettant mais plusieurs tests exhaustifs deraient encore être iv appliquées dans des environnements qui simulent de vrais mouvements oculaires.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".