IRats:Intelligent system for rat behavior analysis

Abstract

Rats' behavior analysis is fundamentally crucial in the medical eld and the pharmaceutical industry. Drugs and chemical compounds are given to mice and rats to measure their therapeutic e ects. If the drug's e ect is promising, it will be investigated in humans. Data extraction from experiments and classifying the trajectory of rats and mice will help scienti c researchers speed up the development of new drugs for the community. We used image processing and computer vision to analyze two of the eminent rat behavior analysis experiments, which are the Morris Water Maze (MWM), and Open Field experiments. In the current work, we implemented two experiments, the rst was testing more than one object detection and tracking algorithm on rats and mice behavior analysis. Second, we used three tracking algorithms, which were $P Point-Cloud Recognizer, Dynamic Time Warping (DTW), and FastDTW, to track the rat's path and classify its movements. The result of the rst experiment was that a combination of CSRT (Channel and Spatial Reliability Tracking) and optical

ow sparse would be more accurate in extracting the data. In addition, the second experiment showed the highest tracking algorithm was FastDTW, with an accuracy of 81%