IRats:Intelligent system for rat behavior analysis

• Published in: 2022 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC) pp. 219 - 224
• Main Authors: Zaky, Andrew, Saber, Mona M, Essam, Reham M., Atia, Ayman
• Format: Conference Proceeding
• Language: English
• Published: IEEE 08.05.2022
• Subjects: Behavioral sciences; Drugs; Heuristic algorithms; Mice; Morris Water Maze; Rat behaviours; Rats; Tracking; Trajectory detection; Ubiquitous computing
• DOI: 10.1109/MIUCC55081.2022.9781727

Rats' behavior analysis is fundamentally important in the medical field and pharmaceutical industry. Drugs and chemical compounds are given to mice and rats to measure their therapeutic effects. If the drug's effect is promising, it will be investigated in humans. Data extraction from experiments and classifying the trajectory of rats and mice will help scientific researchers speed up the development of new drugs for the community. We used image processing and computer vision to analyze one of the eminent rat behavior analysis experiments, which is Morris Water Maze (MWM). In the current work, we implemented two experiments, the first 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 first experiment was that a combination of CSRT (Channel and Spatial Reliability Tracking) and optical flow 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%