Accurate AI-based Characterisation of Surface Size, Depth and Tissue Composition in Hard-to-Hea Woundsl
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 25
- 试验地点
- 1
- 主要终点
- Accuracy
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 19 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Older than 18 years, men and women Difficult to heal wounds due to diabetes, VLU; Pressure wounds wound larger than 0.5 cm2
排除标准
- •Exclusion Criteria / Contraindications
- •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.
结局指标
主要结局
Accuracy
时间窗: During the study
Regular outcome measures for a Medical Device
Accurac, Precision, Mean absolute Error (MAE); Coefficient of Variation (CV); SD
时间窗: During the study
Regular outcome measures for a Medical Device
次要结局
未报告次要终点
研究者
Folke Sjoberg
Prof
University Hospital, Linkoeping