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瞳孔疲劳波数据记录与处理中的数学程序

Mathematical procedures in data recording and processing of pupillary fatigue waves.

作者信息

Lüdtke H, Wilhelm B, Adler M, Schaeffel F, Wilhelm H

机构信息

Universität-Augenklinik Tübingen, Abt. für Pathophysiologie des Sehens und Neuroophtalmologie, Germany.

出版信息

Vision Res. 1998 Oct;38(19):2889-96. doi: 10.1016/s0042-6989(98)00081-9.

Abstract

Spontaneous pupillary behaviour in darkness provides information about a subject's level of vigilance. To establish infrared video pupillography (IVP) as a reliable and objective test in the detection and quantification of daytime sleepiness, the definition of numerical parameters is an important precondition characterising spontaneous pupil behaviour adequately for further statistical procedures. The correct measurement of the pupil size, even if the lid or eyelashes are occluding the pupil, is of particular concern when testing vigilance. In this case many edge points of the pupil are detected and a fitting procedure is described that fits these edge points to a circle and excludes outliers. The first step of data preparation consists of a mathematical artefact management consisting of blink detection and elimination, followed by interpolation. Second, a fast Fourier transformation is carried out for frequencies from 0.0 to 0.8 Hz for each time segment of 82 s. Results are given in absolute and relative power of each frequency band per time segment and mean values over the entire record of 11 min. Third, the changes of the mean pupillary diameter per data window against time are shown graphically. An additional parameter referring to the pupil's tendency to instability, the pupillary unrest index (PUI), is defined by cumulative changes in pupil size based on mean values of consecutive data sequences. These mathematical procedures provide a high level of quality in both data collection and evaluation of IVP as an objective test of vigilance. In a pilot study, the pupillary behaviour of two groups were measured. One group rated themselves as alert (ten men), the other group as sleepy (12 men). The power and PUI were compared using the Mann-Whitney U-test. Both parameters show significant differences between the two groups.

摘要

黑暗环境下的自发瞳孔行为可提供有关受试者警觉水平的信息。为了将红外视频瞳孔描记术(IVP)确立为检测和量化日间嗜睡的可靠且客观的测试方法,定义数值参数是一个重要的前提条件,即要充分表征自发瞳孔行为,以便进行进一步的统计程序。在测试警觉性时,即使眼睑或睫毛遮挡了瞳孔,正确测量瞳孔大小也尤为重要。在这种情况下,会检测到瞳孔的许多边缘点,并描述一种拟合程序,该程序将这些边缘点拟合到一个圆上并排除异常值。数据准备的第一步包括数学伪像管理,即眨眼检测与消除,然后进行插值。第二步,对每个82秒的时间段,在0.0至0.8赫兹的频率范围内进行快速傅里叶变换。结果以每个时间段每个频段的绝对功率和相对功率以及11分钟整个记录的平均值给出。第三步,以图形方式显示每个数据窗口的平均瞳孔直径随时间的变化。另一个与瞳孔不稳定趋势相关的参数,即瞳孔不安指数(PUI),由基于连续数据序列平均值的瞳孔大小累积变化定义。这些数学程序在IVP作为警觉性客观测试的数据收集和评估方面都提供了很高的质量。在一项初步研究中,测量了两组的瞳孔行为。一组自我评定为警觉(10名男性),另一组为困倦(12名男性)。使用曼-惠特尼U检验比较了功率和PUI。这两个参数在两组之间均显示出显著差异。

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