Pain assessment in horses using automatic facial expression recognition through deep learning-based modeling.

ABSTRACT: The aim of this study was to develop and evaluate a machine vision algorithm to assess the pain level in horses, using an automatic computational classifier based on the Horse Grimace Scale (HGS) and trained by machine learning method. The use of the Horse Grimace Scale is dependent on a human observer, who most of the time does not have availability to evaluate the animal for long periods and must also be well trained in order to apply the evaluation system correctly. In addition, even with adequate training, the presence of an unknown person near an animal in pain can result in behavioral changes, making the evaluation more complex. As a possible solution, the automatic video-imaging system will be able to monitor pain responses in horses more accurately and in real-time, and thus allow

SUBMITTER: Lencioni GC 

PROVIDER: S-EPMC8525760 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature