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Identification of the Causative Disease of Intermittent Claudication through Walking Motion Analysis: Feature Analysis and Differentiation

机译:通过步行运动分析鉴定间歇性跛行的致病性疾病:特征分析与分化

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摘要

Intermittent claudication is a walking symptom. Patients with intermittent claudication experience lower limb pain after walking for a short time. However, rest relieves the pain and allows the patient to walk again. Unfortunately, this symptom predominantly arises from not 1 but 2 different diseases: LSS (lumber spinal canal stenosis) and PAD (peripheral arterial disease). Patients with LSS can be subdivided by the affected vertebra into 2 main groups: L4 and L5. It is clinically very important to determine whether patients with intermittent claudication suffer from PAD, L4, or L5. This paper presents a novel SVM- (support vector machine-) based methodology for such discrimination/differentiation using minimally required data, simple walking motion data in the sagittal plane. We constructed a simple walking measurement system that is easy to set up and calibrate and suitable for use by nonspecialists in small spaces. We analyzed the obtained gait patterns and derived input parameters for SVM that are also visually detectable and medically meaningful/consistent differentiation features. We present a differentiation methodology utilizing an SVM classifier. Leave-one-out cross-validation of differentiation/classification by this method yielded a total accuracy of 83%.
机译:间歇性跛行是一种行走症状。在短时间内行走后,患有间歇性跛行的患者在走路后的痛苦较低。然而,休息缓解疼痛,让患者再次走路。不幸的是,这种症状主要来自1而不是2种不同的疾病:LSS(木材脊柱管狭窄)和垫(外周动脉疾病)。 LSS患者可以被受影响的椎骨细分为2个主要组:L4和L5。临床上是非常重要的是,确定间歇性跛行是否患有垫,L4或L5患者。本文介绍了基于SVM-(支持向量机)的基于SVM-(支持向量机)的方法,用于这种歧视/差异使用最小所需的数据,在矢状平面中简单的步行运动数据。我们构建了一种简单的行走测量系统,易于设置和校准,适用于小空间中的非专心人员使用。我们分析了所获得的步态模式和SVM的输入参数,该参数也在视觉上可检测和医学上有意义/一致的差异化特征。我们利用SVM分类器提出了一种差异化方法。这种方法的分化/分类的休留交叉验证产生了83%的总精度。

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