The Pocket Pelvis: Developing an Augmented Reality App for Better Understanding of Pelvis Anatomy
Bibliographic record
Abstract
The human pelvis is one of the more complicated anatomical regions for students to understand due to its complex 3D geometry, the layered pelvic walls, and the differences between male and female pelvises. In order to facilitate the 3D learning of the pelvis we developed an augmented reality application that allows the learner to visualize structures of the pelvis on a 3D printed pelvis model. The 3D printed pelvis model was created based on volumetric reconstruction of the NIH Visible Human dataset. Pelvis structures, such as muscles and neurovasculature, were created using Blender 3D modeling software. The application was created using Unity, and Vuforia was used for the augmented reality image recognition. The app was programmed for use on Android or iOS devices. The aim of this app was not to re‐create an anatomical model, but rather to create a teaching tool that is both accurate and conceptual in nature. Iterative design of the user interface and the user experience led to an educational experience where students can manipulate the 3D printed pocket‐sized pelvis and have control over which structures they can view in the augmented reality app. This approach has led to a set of best practices for this type of augmented reality app: The 3D printed object needs to be generated using a filament that is not too shiny to minimize glare, the tags recognized by Vuforia for adding the augmented reality structures need to be unique and their size needs to be a compromise between optimal recognition and non‐interference with the anatomy. The user interface needs to be clearly structured and allow the user to interact with the augmented reality structures and their device seamlessly and simultaneously. The combination of a physical object that can be freely turned with augmented reality structures that can be turned on and off by the user leads to a user experience that combines a haptic experience with visual cues – a combination that is a foundation for a deep anatomical understanding of the pelvis. Support or Funding Information Supported by the Strategic Investment Fund from the UBC Faculty of Medicine and the UBC Teaching and Learning Enhancement Fund This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".