ArticleJournal of biomedical optics2019
Digitalization versus immersion: performance and subjective evaluation of 3D perception with emulated accommodation and parallax in digital microsurgery.
Article in Journal of biomedical optics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Saliency-Aware Subtle Augmentation Improves Human Visual Search Performance in VR.Brain sciences · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the visually challenging situation of microsurgery with many altered depth cues, digitalization of surgical systems disrupts two further depth cues, namely focus and parallax. Although in purely optical surgical systems accommodation and eye movements induce expected focus and parallax changes, they become statically fixed through digitalization. Our study evaluates the impact of static focus and parallax onto performance and subjective 3D perception. Subjects reported decreased depth realism under static parallax and focus. Thus surgeons’ depth perception is impacted further through digitalization of microsurgery, increasing the potential of artificial stereo-induced fatigue.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.