Use of a genetic algorithm for the analysis of eye movements from the linear vestibulo-ocular reflex.
Use of a genetic algorithm for the analysis of eye movements from the linear vestibulo-ocular reflex.
复制标题
使用遗传算法分析线性前庭眼反射的眼球运动。
DOI：
10.1114/1.1376390
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发表时间：
2001
影响因子：
3.8
通讯作者：
Shelhamer,M
中科院分区：
文献类型：
--
作者：
Shelhamer,M
在前庭和眼科测试中，通常使用单频（正弦）或频率组合[西内斯和（SOS）]刺激头部或目标运动。所得到的眼球运动通常包含平滑跟踪分量，其跟随刺激，其中穿插快速眼球运动（扫视或快速阶段）。平滑跟踪的参数-每个分量频率的振幅和相位-是感兴趣的;已经设计了许多方法，试图从平滑中识别和去除快速眼球运动。我们描述了一种新的方法来解决这个问题，量身定制的单频和总和的西内斯刺激的人的线性前庭眼反射。近似导数用于识别快速运动，然后从进一步分析中省略。剩余的点形成一系列平滑的跟踪段。遗传算法用于将这些段拟合在一起，以通过迭代地去除由于丢失的快速相位而导致的偏差来形成平滑（但断开）的波形。遗传算法是一个迭代优化过程，它提供了一个基础，将这种方法扩展到更复杂的刺激反应的情况。在SOS情况下，遗传算法估计分量频率的幅度和相位值以及去除偏差。©2001生物医学工程学会. PAC 01：8719 St，8780 Tq
It is common in vestibular and oculomotor testing to use a single-frequency (sine) or combination of frequencies [sum-of-sines (SOS)] stimulus for head or target motion. The resulting eye movements typically contain a smooth tracking component, which follows the stimulus, in which are interspersed rapid eye movements (saccades or fast phases). The parameters of the smooth tracking — the amplitude and phase of each component frequency — are of interest; many methods have been devised that attempt to identify and remove the fast eye movements from the smooth. We describe a new approach to this problem, tailored to both single-frequency and sum-of-sines stimulation of the human linear vestibulo-ocular reflex. An approximate derivative is used to identify fast movements, which are then omitted from further analysis. The remaining points form a series of smooth tracking segments. A genetic algorithm is used to fit these segments together to form a smooth (but disconnected) wave form, by iteratively removing biases due to the missing fast phases. A genetic algorithm is an iterative optimization procedure; it provides a basis for extending this approach to more complex stimulus–response situations. In the SOS case, the genetic algorithm estimates the amplitude and phase values of the component frequencies as well as removing biases. ©2001 Biomedical Engineering Society.PAC01: 8719St, 8780Tq