Niemenlehto P-H
Department of Computer Sciences, University of Tampere, University of Tampere, Finland.
Comput Methods Programs Biomed. 2009 Nov;96(2):158-71. doi: 10.1016/j.cmpb.2009.04.011. Epub 2009 May 30.
The analysis of eye movements has proven to be valuable in both clinical work and research as well as in other fields besides medicine. The detection of saccadic eye movements and the extraction of related saccade parameters, such as maximum angular velocity, amplitude, and duration, are usually performed during the analysis of electro-oculographic (EOG) signals. This article considers a saccade detection method that is based on the constant false alarm rate technique, in which the detection sensitivity is continuously adjusted on the basis of the observed signal in order to keep the number of false alarms constant. The method is computationally efficient, it can operate autonomously without user intervention, and it is capable of detecting saccades in a sequential fashion. Therefore, the method finds potential use in applications that require automated analysis of electro-oculographic signals. Because of the constant false alarm rate property, the method can also perform in situations where ideal measurement conditions cannot be guaranteed and noise presents a considerable problem.
眼动分析在临床工作、研究以及医学以外的其他领域都已证明具有重要价值。在眼电图（EOG）信号分析过程中，通常会进行扫视眼动的检测以及相关扫视参数（如最大角速度、幅度和持续时间）的提取。本文考虑一种基于恒定误报率技术的扫视检测方法，该方法根据观测信号不断调整检测灵敏度，以保持误报数量恒定。该方法计算效率高，无需用户干预即可自主运行，并且能够按顺序检测扫视。因此，该方法在需要对眼电图信号进行自动分析的应用中具有潜在用途。由于具有恒定误报率特性，该方法在无法保证理想测量条件且噪声问题严重的情况下也能发挥作用。
