mmSkin: An Over-Gauze Wound Assessment System Using Radio Frequency Technologies

IF 8.9 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Internet of Things Journal Pub Date : 2025-03-19 DOI:10.1109/JIOT.2025.3553057
Xiaoyu Zhang;Zhengxiong Li;Yanda Cheng;Chenhan Xu;Chuqin Huang;Emma Zhang;Ye Zhan;Wei Bo;Jun Xia;Wenyao Xu
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Abstract

Skin wounds are often covered with gauze to protect the injury and support the healing process. Accurate wound assessment is essential for monitoring healing progress and guiding treatment decisions. However, existing assessment methods typically require direct exposure of the wound, necessitating the removal of gauze when present. This process disrupts the healing environment and increases the risk of secondary infections. In this paper, we introduce mmSkin, an innovative over-gauze wound assessment system that utilizes millimeter-wave (mmWave) radar technology to evaluate wound characteristics without the need to remove the gauze. Central to this system is the principle that variations in skin moisture, a critical indicator of wound health, significantly influence mmWave signal strength. By analyzing these variations, mmSkin accurately identifies skin moisture levels, thereby enabling precise assessment of wound conditions. To achieve reliable sensing, mmSkin incorporates a denoised mmWave imaging algorithm designed to reduce motion noise and effectively distinguish between signals reflected from the target skin and those from surrounding environmental interference. Additionally, the system integrates a physics-based model to guide the training of its moisture derivation model. This integration ensures that mmSkin can accurately estimate moisture distribution across the wound area, making it a powerful tool for noninvasive wound assessment. Extensive experiments validate the system’s high accuracy in over-gauze wound moisture distribution estimation, achieving a mean moisture error of approximately 0.5% in both wound phantom and invivo tests. Additionally, the system demonstrates a structural similarity index measure (SSIM) of about 0.9 compared to groundtruth moisture distributions in both test scenarios. These results highlight mmSkin’s potential to revolutionize noninvasive wound assessment and improve patient outcomes.
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mmSkin:使用射频技术的纱布伤口评估系统
皮肤伤口通常用纱布覆盖,以保护伤口并支持愈合过程。准确的伤口评估对于监测愈合进展和指导治疗决策至关重要。然而,现有的评估方法通常需要直接暴露伤口,当纱布存在时需要去除。这一过程破坏了愈合环境,增加了继发感染的风险。在本文中,我们介绍了mmSkin,这是一种创新的纱布覆盖伤口评估系统,它利用毫米波(mmWave)雷达技术来评估伤口特征,而无需移除纱布。该系统的核心原理是皮肤湿度的变化,伤口健康的关键指标,显著影响毫米波信号强度。通过分析这些变化,mmSkin可以准确识别皮肤水分水平,从而精确评估伤口状况。为了实现可靠的传感,mmSkin采用了降噪毫米波成像算法,旨在减少运动噪声,并有效区分来自目标皮肤的反射信号和来自周围环境干扰的信号。此外,该系统还集成了一个基于物理的模型来指导其水分推导模型的训练。这种集成确保mmSkin可以准确地估计伤口区域的水分分布,使其成为非侵入性伤口评估的强大工具。大量的实验验证了该系统在纱布上伤口水分分布估计方面的高精度,在伤口模拟和体内测试中,平均水分误差约为0.5%。此外,在两个测试场景中,该系统的结构相似指数(SSIM)与真实湿度分布相比约为0.9。这些结果突出了mmSkin在非侵入性伤口评估和改善患者预后方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Internet of Things Journal
IEEE Internet of Things Journal Computer Science-Information Systems
CiteScore
17.60
自引率
13.20%
发文量
1982
期刊介绍: The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.
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