The ruler and the guess
Most practices still measure wounds with a disposable ruler, a tracing, and a photograph. The result is subjective, inconsistent between providers, and has proven inadequate under Medicare audit.
StrataMetric AI turns a four-second iPhone LiDAR scan into an objective, reproducible 3D wound measurement — length, width, true depth, wound bed and peri-wound area — with audit-defensible documentation generated in minutes, at the point of care.
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LiDAR depth frames per 4-second burst
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measurements from a single scan
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automated engine tests, six validation layers
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of reports carry full provenance + methodology
The gap between what current tools provide and what CMS now requires has created a clear opening for an objective, instrument-based measurement platform.
Most practices still measure wounds with a disposable ruler, a tracing, and a photograph. The result is subjective, inconsistent between providers, and has proven inadequate under Medicare audit.
Photograph-based tools can't capture depth — the dimension most clinically significant for wound severity and product sizing. Claims built on 2D documentation have faced denials when the billed graft area couldn't be substantiated.
Medicare payment for wound graft procedures has declined substantially per square centimeter. Accurate documentation of dimensions — especially depth and peri-wound area — is now directly material to revenue and audit defensibility.
“The same measurement every time the same wound is scanned — by any clinician, on any day. That reproducibility is what makes documentation audit-defensible.”
The full pipeline runs end-to-end on AWS — from LiDAR frames on the device to a defensible measurement report in the portal, typically inside five minutes.
Stage 01 — iPhone · ARKit + LiDAR
A clinician positions an iPhone over the wound. The app captures a burst of 60 LiDAR depth frames in four seconds, with live motion and fiducial feedback guiding the hold.
Every measurement report pairs structured numbers with visual diagrams and a plain-language narrative scoped strictly to objective data — the methodology is disclosed on every page.
measurement_report · MSR-2031 · v1.0
Quality AValues shown are from the bundled synthetic demonstration mesh (~40 × 40 × 12 mm Gaussian wound bed). Hover a metric to highlight it on the diagram.
Not a video. The workspace below is the same component clinicians use in the authenticated portal, rendering the engine’s synthetic demonstration mesh. Orbit, toggle depth and tissue layers, cut a cross-section, open the analytics tab.
Synthetic demonstration mesh (~40 × 40 × 12 mm Gaussian wound bed) — no patient data. Inside the portal, this same workspace renders real captures with full measurement history.
Every layer — capture, fusion, segmentation, geometry, provenance — is engineered for reproducibility first, because reproducibility is what auditors, partners, and regulators actually test.
Designed and validated with AWS partner engineering: serverless ingestion, an automated processing pipeline, managed AI services for segmentation and narration, and encrypted, lifecycle-managed storage — the same architecture that carries forward into production.
Serverless ingest
scales with scan volume, no idle cost
Managed AI services
segmentation + narration with guardrails
Encryption everywhere
KMS-managed keys, TLS in transit
SwiftUI + ARKit guided capture with live feedback, probe auto-detect, boundary annotation with ML proposal, and a 15-minute idle session timeout.
Python FastAPI service — 13 subpackages covering capture, fusion, geometry, quality, ML, storage, and output — with an async worker for heavy fusion jobs.
The Next.js dashboard behind this site: TOTP MFA sign-in, wound trajectory charts, phantom calibration, admin and audit tooling, hardened security headers.
StrataMetric AI was engineered from the first commit for the pathway ahead — internal clinical-decision-support use now, commercial clearance later, with no rewrite in between.
Operates today under the 21st Century Cures Act §3060 CDS exemption: the clinician retains decision authority, no diagnostic claims are made, and the measurement methodology is transparently displayed in every report.
Designed to support an FDA 510(k) submission without rewrite: a bidirectional regulatory traceability matrix, versioned algorithms, and a comprehensive validation harness are part of the codebase — not an afterthought.
TOTP multi-factor authentication, role-based access, tamper-evident audit hash chain, encryption at rest and in transit with managed key rotation, and hardened security headers across the portal.
Object-locked storage with six-year retention, multi-AZ encrypted databases, VPC isolation with flow logs, and continuous monitoring via CloudWatch, GuardDuty, and Security Hub in the production architecture.
For clinical decision support only. Not for diagnostic use. Clinician retains decision authority. Methodology disclosed in every measurement report.
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Objective, instrument-derived measurements create documentation that substantiates billed wound dimensions under CMS audit scrutiny — reducing the claim-denial risk that has hit practices relying on manual tracing.
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Non-rectangular wound bed area, true depth, and peri-wound area in a single scan — the full three-dimensional wound profile, captured at the point of care. No consumer or clinical smartphone tool offers this today.
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One scan replaces manual measurement, photography, diagram drawing, and manual entry. Automated measurement and diagram generation hands hours back to clinicians and documentation staff every week.
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A working, AWS-validated demonstration of LiDAR wound measurement is concrete technical evidence — for fundraising, clinical partnerships, and the regulatory conversations that follow a successful proof of concept.
Providers with an account can sign in to the portal now. If you’d like access — or a guided walkthrough for your practice, network, or investment team — we’ll set it up.