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An Instrumented Measurement Scheme for the Assessment of Upper Limb Function in Individuals with Friedreich Ataxia

机译:一种仪器测量方案,用于评估弗里德莱希共济失调中的个体上肢功能

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Continuous and objective assessment is essential for accurate monitoring of the progression of neurodegenerative conditions such as Friedreich ataxia. However, current clinical assessments predominantly rely on the ability of the affected individual to complete specific clinical tests which may not capture the intricate kinematic details associated with ataxia Moreover, such testing often consists of a level of subjectivity of the assessing clinician. In this paper, we propose an objective measuring instrument, in the form of a spoon, equipped with the Internet-of-Things (IoT) based system and relevant machine learning techniques to quantitatively assess impairment levels while engaged in routine daily activity. In a clinical study involving individuals diagnosed with Friedreich ataxia, movement patterns during a simulated eating task were captured and kinematic biomarkers were extracted that were consistent with the frequently-used clinical rating scales. Multivariate analysis of these biomarkers allows us to accurately classify individuals with Friedreich ataxia and control subjects to an accuracy of 91%. Furthermore, the kinematic information captured from the spoon can be used to introduce an alternative assessment scheme with a greater sensitivity to ataxic movements and with less inter-rater discrepancy.
机译:连续和客观的评估是神经变性疾病如弗里德共济失调进展的准确的监测是必不可少的。然而,目前的临床评估主要依赖于受影响的个体来完成特定的临床试验可能无法捕捉与共济失调而且相关的复杂运动细节的能力,这种测试通常由医师评估的主观性的水平。在本文中,我们提出了一个客观的测量仪器,在勺的形式,配备了同时从事例行的日常活动互联网的-事(物联网)的系统和相关的机器学习技术的定量评估减值水平。在临床研究中,涉及诊断患有弗里德赖希共济失调的个体,一个模拟进食任务中的运动模式被抓获,并提取运动生物标志物是与常用的临床量表一致。这些生物标志物的多元分析使我们能够准确地分类个体弗里德共济失调和对照组,以91%的准确度。此外,从勺子中捕获的运动信息可以被用来与到共济失调运动的更大的敏感性,并用少评估者间差异引入的替代评估方案。

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