开发基于面向对象逻辑编程的方法和算法,用于对实验室啮齿动物进行视频监控

A. Morozov, O. Sushkova, S. Vaniya
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引用次数: 3

摘要

本文探讨了通过面向对象的逻辑编程对实验室啮齿动物进行视频监控的问题。这些视频是在研究大脑皮层抽搐性电活动的神经生理学实验中制作的。实验鼠行为视频与动物脑电图(EEG)同时录制。有必要将脑电图数据与动物的行为进行比较,因为动物的剧烈运动可能导致与癫痫放电非常相似的脑电图信号。因此,视频监控的首要任务是识别动物的剧烈运动,并利用这些信息正确解释实验结果。视频监控的第二项任务是分析动物在认知测试中的行为。视频记录的基本特征是实验在动物生活的笼子里进行,即笼子的背景是锯末。动物的颜色与锯末的颜色大致相同,因此动物的检测工作并不简单。本文讨论了视频分析底层算法的开发以及动物行为分析的逻辑方法。这些方法和算法是用面向对象的 Actor Prolog 逻辑语言实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Methods and Algorithms Based on Object-Oriented Logic Programming for Video Monitoring of Laboratory Rodents
The problem of video monitoring of laboratory rodents by the means of object-oriented logic programming is considered. The videos are produced in neurophysiological experiments on the study of convulsive electrical activity of the brain cortex. Videos of behaviour of laboratory rats were recorded simultaneously with electroencephalograms (EEG) in the animals. A comparison of EEG data with the behaviour of the animals is necessary because sharp motions of the animals can result in EEG signals that are very similar to the epileptic discharges. Thus, the first task of the video monitoring is recognition of the sharp motions of the animals and using this information for proper interpretation of the results of the experiments. The second task of the video monitoring is analysis of behaviour of animals in cognitive testing. Essential feature of the video records is in that the experiments are conducted in the same cage where the animal lives, that is, the background of the cage is sawdust. The colour of the animals is about the same as the colour of the sawdust; thus the detection of the animals is not a simple task. In the paper, development of low-level algorithms for video analysis as well as logical methods for the analysis of the animal behaviour is discussed. The methods and algorithms are implemented in the Actor Prolog object-oriented logic language.
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