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Development of Methods and Algorithms Based on Object-Oriented Logic Programming for Video Monitoring of Laboratory Rodents

机译:基于对面向对象逻辑编程的方法和算法的开发实验室啮齿动物的视频监控

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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.
机译:考虑了通过面向对象逻辑编程的实验室啮齿动物视频监测问题。该视频是在神经生理学实验中产生的关于脑皮层的痉挛电活动研究。实验室大鼠行为的视频同时记录动物中的脑电图(EEG)。 EEG数据与动物行为的比较是必要的,因为动物的尖锐运动可以导致与癫痫发出非常相似的EEG信号。因此,视频监测的第一任务是识别动物的急剧运动,并使用该信息进行正确解释实验结果。视频监测的第二任务是在认知测试中的动物行为分析。视频记录的基本特征在于,实验是在动物生活的同一笼子中进行的,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,对动物的检测不是一个简单的任务。本文讨论了视频分析的低级算法的发展以及用于分析动物行为的逻辑方法。方法和算法以actor prolog面向对象的逻辑语言实现。

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