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Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Heal Wounds

NCT07211295 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 25

Last updated 2025-10-07

No results posted yet for this study

Summary

This study aims to determine and evaluate the clinical accuracy, precision, and safety of SeeWound 2, an AI-driven wound assessment application, designed for the measurement of wound surface area (cm²), wound depth (mm), and the estimation of the proportion of fibrin covering (slough) and necrosis (%) in real-world clinical settings for patients with hard-to-heal wounds. The study also seeks to validate the non-invasive method for measuring wound depth, as current standard care involves invasive probing of the wound to estimate depth - a practice that this investigational device is intended to replace with a digital, contact-free measurement approach.

Conditions

  • Difficult to Heal Wounds

Sponsors & Collaborators

  • University Hospital, Linkoeping

    lead OTHER

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-07-01
Primary Completion
2025-09-18
Completion
2025-09-18

Countries

  • Sweden

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07211295 on ClinicalTrials.gov