Classification of rat behavior with an image-processing method and a neural network

Video recordings of 11 rats were digitized at five frames per second, and p arameters describing the shape and the position of the rat were calculated. The behavior displayed by the rats was observed by an experienced observer . Separate neural networks were trained and validated, using the data for e ach individual rat. The neural networks correctly classified an average of 76.53% of the frames in the validation set and 98.18% of the frames in the training set. A single neural network was trained with 6 rats and validated with 5 rats. The neural network correctly classified 63.74% of the frames in the validation set and 82.85% of the frames in the training set.