AI-Enabled Animal Behavior Analysis with High Usability: A Case Study on Open-Field Experiments

Featured Application In this study, we designed a highly available animal behavior analysis platform that can help researchers significantly improve their work efficiency. In addition, the platform has good flexibility, scalability, and human-machine interaction. Researchers can easily configure and use the platform for behavioral observation experiments with minimal learning costs.Abstract In recent years, with the rapid development of medicine, pathology, toxicology, and neuroscience technology, animal behavior research has become essential in modern life science research. However, the current mainstream commercial animal behavior recognition tools only provide a single behavior recognition method, limiting the expansion of algorithms and how researchers interact with experimental data. To address this issue, we propose an AI-enabled, highly usable platform for analyzing experimental animal behavior, which aims to provide better flexibility, scalability, and interactivity to make the platform more usable. Researchers can flexibly select or extend different behavior recognition algorithms for automated recognition of animal behaviors or experience more convenient human-computer interaction through natural language descriptions only. A case study at a medical laboratory where the platform was used to evaluate behavioral differences between sick and healthy animals demonstrated the high usability of the platform.