WoundPrint AI
WOUND INTELLIGENCE COCKPIT
Open Cockpit
Multimodal · Explainable · Prototype

WoundPrint AI
Wound intelligence,
at signal speed.

Multimodal wound intelligence cockpit for smart-bandage risk mapping. Fuse wound imaging, simulated smart-bandage chemistry, symptom context, and public medical evidence into one explainable monitoring report.

Computer VisionSmart BandageRisk FusionWound TwinPublic Medical APIsNot a Diagnostic Device
Live Signal Fusion
CH-04 · 60Hz · LOCAL
VISUAL STREAM60%
BIOCHEMICAL STREAM95%
SYMPTOM STREAM96%
EVIDENCE STREAM99%
NORMALIZE
SEGMENT
FUSE
Safety notice. WoundPrint AI is a student prototype for risk awareness and documentation. It is not a diagnosis and does not replace medical care. Always consult a qualified clinician for wound assessment and treatment.
01 · Scan Cockpit

Capture. Fuse. Explain.

Wound Photo
Smart-Bandage Strip
Upload a photo of a colorimetric strip or use the Smart Strip Lab below.
Symptom Checklist
Notes
Medication
Evidence Query
02 · Smart Strip Lab

Synthesize a colorimetric bandage strip.

Generate a demo smart-bandage strip with controllable pads. Use presets for quick low/moderate/high scenarios.

pHnormal
heatnormal
exudatenormal
inflammationnormal
Decoded strip
pH
20
HEAT
22
EXUDATE
20
INFLAM
25
WP-STRIP v0.4
pH severity
20
Heat
22
Exudate
20
Inflammation
25
03 · Fusion Dashboard

The Wound Twin.

FUSED RISK
0
/100
Low
Formula finalRisk = 0.50·visual + 0.35·biomarker + 0.15·symptom
Visual
0
Biomarker
22
Symptom
0
Visual scan
VISUAL RISK SIGNAL: --/100
Awaiting wound signal — run a scan to populate visual feature matrix.
Biomarker severity
pH
20
HEAT
22
EXUDATE
20
INFLAM
25
WP-STRIP v0.4
Top risk drivers (signal contribution)
Awaiting wound signal.
Wound Twin · 7-day monitoring forecast
Simulated
Simulated monitoring forecast — not a clinical prediction.
04 · Evidence Layer

Public medical context.

Query
Medication
PubMed Evidence
demo
  • Wound bed preparation in chronic wounds — review (2023)
  • CRP biomarkers for diabetic foot infection (2022)
  • Smart wearable wound sensors meta-analysis (2024)
ClinicalTrials.gov
demo
  • NCT0518xxxx — Smart bandage exudate monitoring
  • NCT0612xxxx — pH sensor for chronic ulcers
  • NCT0701xxxx — Telehealth wound triage RCT
NIH Clinical Terms
demo
  • Cellulitis
  • Diabetic ulcer
  • Surgical site infection
  • Necrotizing fasciitis (red flag)
openFDA Drug Label
demo
  • Enter medication for label context
  • Adverse events: GI, rash
  • Indications: bacterial skin infections
Live evidence request unavailable in this environment. Demo evidence layer is showing structured placeholder results.
05 · Clinician Report

Clinician-ready handoff.

# WoundPrint AI — Clinician-Ready Monitoring Report Generated: 5/22/2026, 1:32:18 AM ⚠ DISCLAIMER WoundPrint AI is a student prototype for risk awareness and documentation. This is NOT a diagnosis and does not replace clinical evaluation. ──────────────────────────────────── RISK SUMMARY ──────────────────────────────────── Fused risk score : 0/100 Risk category : Low VISUAL WOUND FEATURES (no scan run yet) SMART STRIP BIOMARKER READINGS pH severity : 20/100 Heat : 22/100 Exudate : 20/100 Inflammation : 25/100 REPORTED SYMPTOMS (none selected) TOP RISK DRIVERS (run scan) IMAGE QUALITY NOTES (n/a) WOUND TWIN FORECAST (7d, simulated) D0: 0 (band 0–4) D1: 0 (band 0–5) D2: 0 (band 0–6) D3: 0 (band 0–8) D4: 0 (band 0–9) D5: 0 (band 0–10) D6: 0 (band 0–11) D7: 0 (band 0–12) EVIDENCE QUERY Query : diabetic foot ulcer infection Medication : (none) NOTES (none) RECOMMENDED NEXT STEPS Consider professional medical review if symptoms worsen or if high-risk signs are present (spreading redness, fever, red streaks, foul odor, worsening pain, drainage, or systemic symptoms). LIMITATIONS • Image lighting and skin-tone variability not calibrated. • Smart-strip chemistry is simulated for prototype use. • Forecast is a simulated monitoring trajectory, not a clinical prediction. • This system is not a medical device.
06 · About · Future · Submission

Why WoundPrint matters.

Why this is different

Most wound apps focus only on photos. WoundPrint is different because it combines visual wound analysis with smart-bandage biochemical signals, symptom context, and evidence retrieval. The result is not a black-box diagnosis but an explainable monitoring workflow.

Real-world use cases
  • Home wound monitoring
  • Diabetic foot ulcer awareness
  • Post-surgical follow-up
  • Nursing home documentation
  • Low-resource telehealth
  • Rural clinic support
Future scalability
  • Real smart-bandage sensor integration
  • Longitudinal wound tracking
  • Lighting / skin-tone calibration
  • Clinician dashboard
  • Secure patient history
  • PDF/EHR export
  • Federated learning
  • Clinical validation
  • Real calibration curves
  • Wound-size estimation
Ethical boundaries
  • Not a diagnosis
  • Not a medical device
  • Does not replace clinicians
  • Image quality / lighting limitations
  • Simulated smart-strip chemistry
  • Validation required before real clinical use
Architecture · Smart-bandage to risk map
Wound fluid contactLAYER 1Capillary routingLAYER 2Sensor arrayLAYER 3Optical referenceLAYER 4Phone scannerLAYER 5Risk map + scoreLAYER 6
Team WoundPrint
Ajsel
Project concept · product design · risk model · UI direction · demo preparation.
Open seat
Clinical validation collaborator.
Open seat
Sensor / hardware partner.
Hackathon Submission Snapshot

Judge-ready in 7 cards.

Title
WoundPrint AI
Description
Multimodal wound intelligence cockpit for image + smart-bandage risk mapping.
Problem
Wounds worsen between visits and patients lack structured monitoring tools.
Solution
Fuse wound photo, colorimetric strip, symptoms, and evidence into an explainable report.
Prototype
Interactive web app: upload, scan, charts, forecast, report export.
Technical Stack
Web app, browser image analysis, strip simulation, transparent risk model, charts, public medical APIs.
Impact
Earlier awareness, better documentation, stronger telehealth handoff.
Use Case
Home monitoring, diabetic foot ulcers, post-surgical follow-up, nursing home, telehealth triage.