Computer-Vision Procedural Telemetry for Airway Guidance: A Public 30-Run Manikin Evidence-Package Audit

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Background

Computer vision-enabled airway workflows can turn airway video into timestamped model-observation fields, but later blinded review and training studies require source-video linkage, run identifiers, quality-control status, and app/model provenance.

Objective

To audit whether a public post-reconciliation 30-run manikin evidence package from a computer vision-enabled video laryngoscopy workflow preserved prespecified, video-linked procedural telemetry in structured JSON, while keeping detection accuracy, report quality, and reviewer agreement outside the current claim.

Methods

Thirty manikin runs were captured on a HEALTHIBLE Intubation Simulator using an IntuBlade device connected to an iPhone 15 Pro Max. Six predefined conditions were tested with five runs each in planned round-robin order by a board-certified emergency physician operator. The author-affiliated team analyzed corrected Study Metrics JSON exports, the video manifest, app/model metadata, QC fields, and the frozen package checker after reconciliation against the assigned run guide. Blinded video review, independent analysis, and report-quality adjudication were not performed.

Results

After reconciliation, all 30 rows contained parseable Study Metrics JSON, a companion videoFilename, run-named Drive video status, QC pass status, and corrected identifiers matching assigned row labels (30/30 for each completeness field; descriptive exact binomial 95% CI, 88.4% to 100.0%). App/model metadata were complete: appVersion 3.3.0 (75), source revision b94cd63, Navigation model, model version 31, and detection threshold 0.1. The exported JSON target-state flag was true in 25 of 25 target-condition rows (95% CI, 86.3% to 100.0%) and false in 5 of 5 no-target controls (95% CI, 47.8% to 100.0%), with zero glottic-detected frames and zero acceptable-view time in no-target controls. Among target-condition rows, median time to first model-detected glottic target was 2 seconds (IQR 1 to 3), median acceptable-view duration was 2.2 seconds (IQR 1.0 to 3.8), and median glottic visibility was 35.8% (IQR 25.8 to 45.6).

Interpretation

The corrected package supports a bounded formative claim: simulated airway video can be represented as specified, video-linked computer-vision procedural telemetry after documented reconciliation. It supports package completeness, traceability, and assigned-condition consistency only; it does not establish native uncorrected export reliability, computer-vision detection accuracy, report quality, reviewer agreement, training effectiveness, autonomous guidance, tube-placement confirmation, clinical efficacy, or patient outcomes.

Article activity feed