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

Overview

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

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.