Difficult to Heal WoundsSeeWound2NCT07211295
Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Heal Wounds
An observational study of Difficult to Heal Wounds, run by University Hospital, Linkoeping at 1 site in Sweden.
Trial 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… Read more about this study
- Who is it for?
- Ages 19 years and older
- Conditions the study is for
- Difficult to Heal Wounds
- How many people
- 25 participants
- Where
- 1 siteSweden
- Study dates
- 1 Jul 2025to 18 Sep 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: ntended Use / Target Population The intended target population for SeeWound 2 comprises patients with hard-to-heal wounds. The device is designed for use by qualified healthcare professionals for the clinical assessment, documentation, and monitoring of chronic and complex wounds, including but not limited to venous leg ulcers, diabetic foot ulcers, and pressure ulcers. SeeWound 2 is intended to support clinical decision-making by providing objective, non-invasive measurements of wound surface area and depth, and by enabling the classification and quantification of wound bed tissue composition (slough and necrosis). The product is not intended to replace clinical judgement but to serve as an adjunctive tool to standard wound care practice.
Who may be able to join
- Older than 18 years, men and women Difficult to heal wounds due to diabetes, VLU; Pressure wounds wound larger than 0.5 cm2
Who cannot join
- Use of SeeWound 2 is not intended for, or is contraindicated in, the following situations:
- Patients under 18 years of age. Wounds located in anatomical regions where the full wound surface and depth cannot be captured (e.g. deep fistulas, tunnels, or undermined areas not accessible through surface imaging).
- Wounds with excessive exudation or infection that prevents adequate visual assessment.
- Patients who are unable or unwilling to provide informed consent. Patients with a known allergy or adverse reaction to any component used in the image acquisition process (where applicable).
- Wounds with specific identifiable attributes (e.g. on the face, or containing birthmarks or tattoos) where ethical considerations regarding data handling apply.
Trial locations and contacts
1 site in 1 country.
Sweden1 site
BRIVA, Intensive Care for Burns,
Linköping, Östergötland County, 58185
About this study
Official title: Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Hea Woundsl
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.
Read the detailed description
SeeWound 2 is a software-based medical device that utilises artificial intelligence to classify and quantify wound tissue types, specifically fibrin covering (slough) and necrosis, as well as to measure wound surface area and depth through digital image analysis. The system operates as a mobile camera-based application, whereby healthcare professionals capture an image of a hard-to-heal wound. The software then automatically analyses the image using integrated AI models in combination with the LiDAR sensor technology embedded in the mobile camera hardware. The product's capability to automatically measure wound surface area, estimate wound depth in a non-invasive manner, and objectively quantify the proportion of slough and necrosis within the wound bed represents a novel functionality not currently available in clinical practice.
- Conditions
- Difficult to Heal Wounds
- Keywords
- VLU; difficult to heal wounds; diabete; ulcers;
- Medical subject headings
- Ulcer
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Cohort | cohort |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy
Regular outcome measures for a Medical Device
Measured: During the study
Accurac, Precision, Mean absolute Error (MAE); Coefficient of Variation (CV); SD
Regular outcome measures for a Medical Device
Measured: During the study
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Oct 2025
- Study start1 Jul 2025
- Primary completion18 Sep 2025
- Study completion18 Sep 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Difficult to Heal WoundsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 25 participants (actual)
Sponsor and investigators
- Lead sponsor
- University Hospital, Linkoeping
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Folke Sjoberg, University Hospital, Linkoeping
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07211295
- Sponsor's protocol ID
- CIP-MDR-SWD001-V1.0-2025, ver,
- Acronym
- SeeWound2
- Status last verified
- Sep 2025
- First submitted
- 31 Aug 2025
- Last updated
- 7 Oct 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Oct 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Hea Woundsl
- ClinicalTrials.gov ID
- NCT07211295
- Acronym / sponsor ID
- SeeWound2 / CIP-MDR-SWD001-V1.0-2025, ver,
- Conditions
- Difficult to Heal Wounds
- Keywords
- VLU; difficult to heal wounds; diabete; ulcers;
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 25 participants (actual)
- Lead sponsor
- University Hospital, LinkoepingUniversity, hospital or other
- Study start
- 1 Jul 2025 (actual)
- Primary completion
- 18 Sep 2025 (actual)
- Study completion
- 18 Sep 2025 (actual)
- First posted
- 7 Oct 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
SeeWound 2 is a software-based medical device that utilises artificial intelligence to classify and quantify wound tissue types, specifically fibrin covering (slough) and necrosis, as well as to measure wound surface area and depth through digital image analysis. The system operates as a mobile camera-based application, whereby healthcare professionals capture an image of a hard-to-heal wound. The software then automatically analyses the image using integrated AI models in combination with the LiDAR sensor technology embedded in the mobile camera hardware. The product's capability to automatically measure wound surface area, estimate wound depth in a non-invasive manner, and objectively quantify the proportion of slough and necrosis within the wound bed represents a novel functionality not currently available in clinical practice.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Cohort | – | –cohort |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- ntended Use / Target Population The intended target population for SeeWound 2 comprises patients with hard-to-heal wounds. The device is designed for use by qualified healthcare professionals for the clinical assessment, documentation, and monitoring of chronic and complex wounds, including but not limited to venous leg ulcers, diabetic foot ulcers, and pressure ulcers. SeeWound 2 is intended to support clinical decision-making by providing objective, non-invasive measurements of wound surface area and depth, and by enabling the classification and quantification of wound bed tissue composition (slough and necrosis). The product is not intended to replace clinical judgement but to serve as an adjunctive tool to standard wound care practice.
Key inclusion criteria (1 listed)
- Older than 18 years, men and women Difficult to heal wounds due to diabetes, VLU; Pressure wounds wound larger than 0.5 cm2
Key exclusion criteria (5 listed)
- Use of SeeWound 2 is not intended for, or is contraindicated in, the following situations:
- Patients under 18 years of age. Wounds located in anatomical regions where the full wound surface and depth cannot be captured (e.g. deep fistulas, tunnels, or undermined areas not accessible through surface imaging).
- Wounds with excessive exudation or infection that prevents adequate visual assessment.
- Patients who are unable or unwilling to provide informed consent. Patients with a known allergy or adverse reaction to any component used in the image acquisition process (where applicable).
- Wounds with specific identifiable attributes (e.g. on the face, or containing birthmarks or tattoos) where ethical considerations regarding data handling apply.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Accuracy
Time frame: During the study
Regular outcome measures for a Medical Device
Accurac, Precision, Mean absolute Error (MAE); Coefficient of Variation (CV); SD
Time frame: During the study
Regular outcome measures for a Medical Device
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Oct 2025.
- Individual participant dataSharing planned: No
Related trials for Difficult to Heal Wounds
Recruiting
Rapid Construction of Tissue-engineered Skin for Repairing Difficult-to-heal Wounds
Wounds and Injuries / Mortality
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Difficult to Heal Wounds, run by University Hospital, Linkoeping at 1 site in Sweden.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 7 Oct 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy (time frame: During the study). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Oct 2025.