Automatic Scratching Pattern Detection for Laboratory Mice Using High-Speed Video Images

Quantifying the rapid action of a mouse scratching its head with its hind leg can provide an objective behavioral indicator for atopic dermatitis, and the development of new drugs for this disease can be significantly expedited by automating such quantification. In this paper, we propose methods for extracting the scratching patterns of a mouse by focusing on its rapid and periodic behavioral patterns. We extracted the scratching patterns from the high-speed video images of actual laboratory mice, and our experimental results show that scratching can be automatically quantified without misinterpretations. Note to Practitioners - The proposed pattern detection method is completely free from the detection of false behaviors caused by markers painted on their skins. Therefore, practitioners in laboratory experiments can also easily apply it to other periodic behavior analyses, such as gait pattern analysis and tremble detection for automated quantitative evaluations of behaviors related to brain, heart, or other diseases, even if the experimented animals are sensitive to painting.