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基于非负矩阵分解的脊髓损伤患者坐姿压力与压疮风险关系分析

Nonnegative matrix factorization for the identification of pressure ulcer risks from seating interface pressures in people with spinal cord injury.

机构信息

Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Champaign, IL, USA.

Program in Computational Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

出版信息

Med Biol Eng Comput. 2020 Jan;58(1):227-237. doi: 10.1007/s11517-019-02081-z. Epub 2019 Dec 12.

Abstract

The purpose of this study was to predict and visualize pressure ulcer risks by using a novel approach of extracting computational features from seating interface pressures in people with spinal cord injury (SCI). In conventional clinical practice, seating interface pressure assessments rely on descriptive statistics of pressure magnitude. In this study, rank-2 nonnegative matrix factorization (NMF) was applied to the seating interface pressure maps during loading and pressure-relieving conditions in 16 people with SCI. The NMF basis images were used for visual interpretation and computational prediction of pressure ulcer risks. The two NMF basis images encapsulated pressure concentration and pressure dispersion, respectively. The first basis converged on the ischial tuberosity under both seating conditions, whereas the second basis converged anterior to the ischial tuberosity during loading and converged on the coccyx during unloading. The classification yielded 81.25% overall accuracy. In general, higher ulceration risk was associated with higher and lower activations of the first and second bases, respectively. The NMF pipeline yielded promising performance. Basis visualization affirmed the importance of lower ischial pressure and higher distribution dispersion while also revealing that clinical practice may currently be underestimating the importance of coccygeal pressure in response to pressure-relieving activities. Graphical abstract.

摘要

本研究旨在通过从脊髓损伤(SCI)患者的坐姿界面压力中提取计算特征,预测和可视化压疮风险。在传统的临床实践中,坐姿界面压力评估依赖于压力大小的描述性统计。在这项研究中,我们将秩 2 非负矩阵分解(NMF)应用于 16 名 SCI 患者的加载和减压条件下的坐姿界面压力图。NMF 基图像用于压力溃疡风险的视觉解释和计算预测。这两个 NMF 基图像分别表示压力集中和压力分散。第一个基在两种坐姿条件下都收敛到坐骨结节,而第二个基在加载时收敛到坐骨结节前方,在减压时收敛到尾骨。分类得到 81.25%的总体准确率。一般来说,较高的溃疡风险与第一和第二基的较高和较低的激活有关。NMF 管道的性能表现很有前景。基的可视化证实了坐骨压力较低和分布分散性较高的重要性,同时也表明临床实践可能目前低估了尾骨压力在减压活动中的重要性。图摘要。

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引用本文的文献

本文引用的文献

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