Skip to content

Research and Application Evaluation of Accurate Pressure Ulcer Area Measurement Technology Based on AI Grid Intelligent Recognition: A Self-controlled Study

Research and Application Evaluation of Accurate Pressure Ulcer Area Measurement Technology Based on AI Grid Intelligent Recognition: A Self-controlled Study

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07743385
Enrollment
100
Registered
2026-08-03
Start date
2026-07-14
Completion date
2026-12-30
Last updated
2026-08-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Pressure Injuries, Pressure Ulcers

Keywords

Wound Assessment, Wound Area Measurement, AI Image Recognition, Grid Counting, Wound Measurement Film

Brief summary

The goal of this clinical trial is to learn if AI grid image recognition can measure pressure ulcer wound area accurately and efficiently in adult patients with pressure ulcers. The main questions it aims to answer are: * Can AI grid image recognition shorten the single measurement time of pressure ulcer wound area? * Is the wound area measured by AI grid image recognition consistent with the result from traditional manual grid counting? Researchers will compare AI grid image recognition measurement with traditional manual grid counting measurement on the same pressure ulcer wound image collected at a single time point to see if AI recognition achieves comparable accuracy with less operation time. Participants will: * Have standardized transparent grid dressing applied on their pressure ulcer wound * Undergo one-time wound image collection * Receive sequential wound area measurement using both methods on the captured single wound image

Detailed description

This is a single-arm, self-controlled clinical trial enrolling adult inpatients with pressure ulcers. All enrolled subjects receive routine standardized wound care. A sterile transparent dressing printed with uniform standard grids will be applied onto the pressure ulcer wound surface for one-time image capture. Based on the single acquired wound image, two area measurement approaches will be performed sequentially: automated measurement via the AI grid image recognition system and manual measurement using the traditional grid counting method. The primary outcomes include single measurement operation time and the consistency of wound area results obtained from the two measurement techniques. All measurement data will be collected and statistically analyzed to verify whether AI grid recognition can achieve rapid and reliable area assessment of pressure ulcers in clinical settings.

Interventions

DIAGNOSTIC_TESTAI Grid Image Recognition Measurement

A sterile transparent grid measurement film (single grid area 0.25 cm²) is attached to the pressure ulcer wound. After wound image acquisition, the AI system automatically identifies grids covered by the wound to calculate pressure ulcer wound area.

DIAGNOSTIC_TESTTraditional Manual Grid Counting Measurement

Based on the same wound photo with transparent grid film, trained clinical staff manually count grids covered by pressure ulcer; grids covered more than half are counted, grids less than half covered are excluded to calculate wound area.

Sponsors

Affiliated Hospital of Nantong University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE

Masking description

This study adopts an open-label design. All participants, care providers, investigators and outcome assessors are aware of the measurement method being used. Blinding is not feasible due to the obvious differences in the operation procedures and implementation modes between the AI grid image recognition measurement and the traditional manual grid counting measurement.

Intervention model description

This is a single-arm self-controlled clinical trial. All enrolled participants are assigned to one single group. On the same pressure ulcer wound at a single time point, two wound area measurement methods are performed sequentially: AI grid image recognition measurement and traditional manual grid counting measurement. This design compares the operation efficiency and measurement consistency of the two methods within the same subject, eliminating inter-subject confounding factors.

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Inclusion Criteria: 1. Aged ≥18 years old; 2. Clinically diagnosed pressure injury of stage I-IV; 3. Patients or legal guardians sign informed consent; 4. Able to complete wound image acquisition.

Exclusion criteria

1. Wounds with severe bleeding, active infection or extensive necrotic tissue unsuitable for film attachment; 2. Patients with severe skin allergic diseases who cannot tolerate transparent grid film; 3. Patients unable to cooperate with image collection; 4. Pregnant women; 5. Patients participating in other concurrent wound intervention trials.

Design outcomes

Primary

MeasureTime frameDescription
Pressure injury wound areaBaselineTo compare pressure injury area values obtained by AI automatic grid recognition measurement and manual grid counting gold standard.

Secondary

MeasureTime frameDescription
Wound measurement operation durationBaselineTo compare the time consumed for completing one pressure injury area assessment between the AI measurement group and manual measurement group

Countries

China

Contacts

STUDY_DIRECTORHonglei Wu, postgraduate

Affiliated Hospital of Nantong University

PRINCIPAL_INVESTIGATORYajun Li, postgraduate

Hospital of Bengbu Medical University

STUDY_DIRECTORMeijuan Lan, postgraduate

Second Affiliated Hospital, Zhejiang University, School of Medicine

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 5, 2026