MétaCan
Menu
Back to cohort
Record W3210931027 · doi:10.3390/mti5110066

Virtual and Augmented Reality Direct Ophthalmoscopy Tool: A Comparison between Interactions Methods

2021· article· en· W3210931027 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMultimodal Technologies and Interaction · 2021
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Health Research
Canadian institutionsYork UniversityOntario Tech University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsUsabilityComputer scienceVirtual realityOphthalmoscopyFundus (uterus)Augmented realityController (irrigation)Human–computer interactionOphthalmologyMedicine

Abstract

fetched live from OpenAlex

Direct ophthalmoscopy (DO) is a medical procedure whereby a health professional, using a direct ophthalmoscope, examines the eye fundus. DO skills are in decline due to the use of interactive diagnostic equipment and insufficient practice with the direct ophthalmoscope. To address the loss of DO skills, physical and computer-based simulators have been developed to offer additional training. Among the computer-based simulations, virtual and augmented reality (VR and AR, respectively) allow simulated immersive and interactive scenarios with eye fundus conditions that are difficult to replicate in the classroom. VR and AR require employing 3D user interfaces (3DUIs) to perform the virtual eye examination. Using a combination of a between-subjects and within-subjects paradigm with two groups of five participants, this paper builds upon a previous preliminary usability study that compared the use of the HTC Vive controller, the Valve Index controller, and the Microsoft HoloLens 1 hand gesticulation interaction methods when performing a virtual direct ophthalmoscopy eye examination. The work described in this paper extends our prior work by considering the interactions with the Oculus Quest controller and Oculus Quest hand-tracking system to perform a virtual direct ophthalmoscopy eye examination while allowing us to compare these methods without our prior interaction techniques. Ultimately, this helps us develop a greater understanding of usability effects for virtual DO examinations and virtual reality in general. Although the number of participants was limited, n = 5 for Stage 1 (including the HTC Vive controller, the Valve Index controller, and the Microsoft HoloLens hand gesticulations), and n = 13 for Stage 2 (including the Oculus Quest controller and the Oculus Quest hand tracking), given the COVID-19 restrictions, our initial results comparing VR and AR 3D user interactions for direct ophthalmoscopy are consistent with our previous preliminary study where the physical controllers resulted in higher usability scores, while the Oculus Quest’s more accurate hand motion capture resulted in higher usability when compared to the Microsoft HoloLens hand gesticulation.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.233
GPT teacher head0.568
Teacher spread0.336 · 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