Vibroarthrographic signals for the low-cost and computationally efficient classification of aging and healthy knees

Vibroarthrographic signals for the low-cost and computationally efficient classification of aging and healthy knees
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用于对老化和健康膝盖进行低成本且计算高效分类的振动关节描记信号

DOI:
10.1016/j.bspc.2021.103003
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发表时间:
2021
影响因子:
5.1
通讯作者:
Susumu Ota
Susumu Ota
中科院分区:
工程技术2区
文献类型:
--
作者:
Rui Gong;Hajime Ohtsu;Kazunori Hase;Susumu Ota

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膝关节疾病是一种常见但容易被忽视的疾病,通常由自然或早期衰老引起。然而,在老化过程中,患者很难自我诊断,直到病情恶化为骨关节炎(OA)。关节振动成像(VAG)信号使衰老过程可见,并可能有助于减少因延误医疗诊断而导致的残疾发生率。近年来,虽然有很多研究利用VAG信号诊断膝关节疾病,但尚未将其用于膝关节老化的诊断。本文提出了一种通过VAG信号分析来观察膝关节老化过程的方法。该方法对自然老化膝关节和健康膝关节的分类准确率为0.9275,受试者工作特征曲线下面积为0.8928。填补了利用VAG信号诊断膝关节自然老化过程的空白,为早期膝关节老化的无创诊断奠定了基础。
Knee disorders are a common but easily overlooked disease and are often caused by natural or early aging. However, the aging process is difficult for the patient to self-diagnose until it deteriorates to osteoarthritis (OA). Vibroarthrographic (VAG) signals make the aging process visible and may contribute to reducing the incidence of disability caused by delayed medical diagnosis. Recently, although many studies have used VAG signals to diagnose knee joint disease, they have not yet been used in the diagnosis of knee aging. In this paper, a method is proposed to observe the aging process of the knee through VAG signal analysis. The accuracy of classifying naturally aging and healthy knees with this method is 0.9275, and the area under the receiver operating characteristic curve is 0.8928. The paper has filled the gap of using VAG signal to diagnose the natural knee aging process and laid the foundation for the non-invasive diagnosis of early knee aging.
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