Low-end haptic devices for knee bone drilling in a serious game
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the application of low-end, low-fidelity (gaming/consumer-level) haptic devices for medical-based, surgical skills development (surgical bone-based drilling in particular) with serious games and virtual simulations as an affordable training solution with the potential of complementing current and traditional training methods. Design/methodology/approach The authors present the adaptation of two low-end haptic devices (Novint Falcon and Geomagic 3D Touch) to simulate a surgical drill drilling through bone for a serious game developed for total knee arthroplasty training. The implementation was possible through the analysis of the bone drilling mechanics. The authors provide a quantitative comparison of both haptic devices with respect to forces, movements, and development. Findings Although further testing is required, the initial results demonstrate that the low-end, consumer-level haptic devices can be incorporated into virtual environments/serious games to allow for the simulation of surgical drilling. The authors also believe that the results will generalize and allow these devices to be used to simulate a variety of technical-based medical procedures. Originality/value In contrast to previous work where the focus is placed on cost-prohibitive haptic devices, this approach considers affordable consumer-level solutions that can be easily incorporated into a variety of serious games and virtual simulations. This holds promise that haptic-based virtual simulation and serious games become more widespread, ultimately ensuring that medical trainees are better prepared before exposure to live patients.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".