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Precision and accuracy of consumer-grade motion tracking system for pedicle screw placement in pediatric spinal fusion surgery

2017· article· en· W2624515510 on OpenAlexafffund
Andrew Chan, Janelle Aguillon, Doug Hill, Edmond Lou

Bibliographic record

VenueMedical Engineering & Physics · 2017
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsGlenrose Rehabilitation HospitalAlberta Health ServicesUniversity of Alberta HospitalUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsTranslation (biology)Rotation (mathematics)Accuracy and precisionSpinal fusionRotation around a fixed axisMedicineArtificial intelligenceComputer visionComputer scienceSurgeryMathematicsPhysics

Abstract

fetched live from OpenAlex

Adolescent idiopathic scoliosis (AIS) is a 3-dimensional spinal deformity involving lateral curvature and axial rotation. Surgical intervention involves insertion of pedicle screws into the spine, requiring accuracies of 1mm and 5° in translation and rotation to prevent neural and vascular complications. While commercial CT-navigation is available, the significant cost, bulk and radiation dose hinders their use in AIS surgery. The objective of this study was to evaluate a commercial-grade Optitrack Prime 13W motion capture cameras to determine if they can achieve adequate accuracy for screw insertion guidance in AIS. Static precision, camera and tracked rigid body configurations, translational and rotational accuracy were investigated. A 1-h camera warm-up time was required to achieve precisions of 0.13mm and 0.10°. A three-camera system configuration with cameras at equal height but staggered depth achieved the best accuracy. A triangular rigid body with 7.9mm markers had superior accuracy. The translational accuracy for motions up to 150mm was 0.25mm while rotational accuracy was 4.9° for rotations in two directions from 0° to 70°. Required translational and rotational accuracies were achieved using this motion capture system as well as being comparable to surgical-grade navigators.

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.

How this classification was reachedexpand

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.476

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 integrity0.0000.000
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 head0.042
GPT teacher head0.314
Teacher spread0.272 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2017
Admission routes2
Has abstractyes

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