A FUZZY SET THEORETICAL APPROACH TO AUTOMATIC-ANALYSIS OF NYSTAGMIC EYE-MOVEMENTS
A FUZZY SET THEORETICAL APPROACH TO AUTOMATIC-ANALYSIS OF NYSTAGMIC EYE-MOVEMENTS
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DOI：
10.1109/10.35304
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发表时间：
1989-09-01
影响因子：
4.6
通讯作者：
MAGNIN, M
中科院分区：
文献类型：
--
作者：
ARZI, M;MAGNIN, M
开发了一种对前庭眼 (VOR) 和视动 (OKN) 反射中眼球震颤眼球运动进行计算机分析的方法。模糊集理论方法用于通过消除眼动信号中的快速分量（扫视）来构建慢速累积眼位置（SCEP）曲线。当人类操作员区分眼球运动的快速和慢速阶段时，这些程序能够自动执行经典交互程序中传统上使用的一些模式识别任务。算法的结构如下。形成慢速和快速阶段的模糊簇。使用迭代方法逐步细化慢相的隶属函数，直到获得足够区分的隶属函数。眼跳被检测并从眼睛位置信号中去除。然后通过在慢速阶段之间进行插值来构建 SCEP。进行加权最小二乘曲线拟合。加权系数是从迭代产生的最后一个隶属函数中获得的。曲线拟合参考SCEP，使用最后一条曲线计算VOR和OKN的参数。< >
A method for computer analysis of nystagmic eye movements in vestibulo-ocular (VOR) and optokinetic (OKN) reflexes is developed. A fuzzy set theoretical approach is used to construct the slow cumulative eye position (SCEP) curve by eliminating fast components (saccades) from the eye movement signal. These procedures are able to perform automatically some pattern recognition tasks traditionally used in classical interactive programs when human operators distinguish between fast and slow phases of eye movements. The structure of the algorithm is as follows. A fuzzy clusters of slow and fast phases is made. An iterative method is used to refine the membership function of slow-phases, step by step, until a sufficiently discriminating membership function is obtained. Saccades are detected and removed from the eye position signal. SCEP is then built by interpolating between slow phases. A weighted least-squares curve fitting is made. Weighting coefficients are obtained from the last membership function resulting from the iterations. The curve fitting is referenced to the SCEP, and the parameters of VOR and OKN are calculated using this last curve.< >