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Identification of saccadic components in spinocerebellar ataxia applying an independent component analysis algorithm

机译:应用独立分量分析算法识别脊髓小脑共济失调中的跳动分量

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Anomalies in the oculomotor system are well known symptoms in different neurodegenerative diseases. It has been found that patients suffering from severe spino cerebellar ataxia type 2 show deterioration in the main parameters used to describe saccadic movements, specifically the slowing of horizontal saccadic eye movements. Besides, a combination of two components, named pulse and step, constitutes an accepted model of the saccadic generation system. In the present work, independent component analysis is applied in order to separate both pulse and step components, revealing significant differences in several parameters related to the morphology of these components between patients and control responses. Ten electro-oculographic records of spino cerebellar ataxia type 2 patients and ten control subjects were processed with the proposed algorithm with the aim of obtaining a correct diagnosis. The results obtained from these real experiments reveal the validity of the proposed approach as a classification tool for the diagnosis of this disease.
机译:动眼系统的异常是不同神经退行性疾病中众所周知的症状。已经发现患有严重的2型脊髓小脑共济失调的患者显示出用于描述扫视运动的主要参数恶化,特别是水平扫视眼的运动减慢。此外,由脉冲和阶跃这两个分量组成的组合构成了声纳产生系统的公认模型。在本工作中,应用独立的成分分析以分离脉冲成分和阶跃成分,从而揭示了与患者和对照反应之间这些成分的形态有关的几个参数之间的显着差异。用该算法处理了10例2型脊髓型小脑性共济失调患者的眼电记录和10例对照对象,以期获得正确的诊断。从这些实际实验中获得的结果表明,该方法可作为诊断该疾病的分类工具。

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