Algorithms for the Clinical Analysis of Nystagmus Eye Movements
Algorithms for the Clinical Analysis of Nystagmus Eye Movements
复制标题
眼球震颤眼动临床分析算法
DOI：
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发表时间：
1981
影响因子：
4.6
通讯作者：
F. Black
中科院分区：
文献类型：
--
作者：
C. Wall;F. Black
描述了眼球震颤临床分析中使用的两种算法。它们的发展是由于前庭和视动刺激的系统识别类型响应的眼球震颤波形更加复杂，而对步进输入的响应不太复杂。临床应用的实际考虑也影响了它们的发展。第一个算法将眼球震颤数据转换为慢相速度 (SPV) 的定期采样估计，慢相速度是信号的一个重要特征。它使用一套新的快速相位检测条件，允许自动处理眼球震颤方向的反转并实现临床数据的广泛可变性。第二种算法使用基于数据与刺激相比的总体“噪声”测量的自适应标准来检测该 SPV 估计中的噪声引起的尖峰。
Two algorithms used in the clinical analysis of nystagmus are described. Their development was necessitated by the greater complexity of the nystagmus waveforms in response to system identification types of vestibular and optokinetic stimuli as compued to the less complex response to a step input. Practical considerations for clinical application also influenced their development. The first algorithm converts nystagmus data into a regulary sampled estimate of slow phase velocity (SPV), an important feature of the signal. It uses a new set of fast phase detection conditions which allow for automatic processing of reversals in nystagmus direction and for wide variability for clinical data. The second algorithm detects noise induced spikes in this SPV estimate using an adaptive criterion based upon a measure of the overall "noisiness" of the data compared to the stimulus.