Simultaneous, Non-Contact and Motion-Based Monitoring of Respiratory Rate in Sheep Under Experimental Condition Using Visible and Near-Infrared Videos

Abstract

The validation of methods for understanding the effects of many diseases and treatments requires the use of animal models in translational research. In this context, sheep have been employed extensively in scientific studies. However, the imposition of experimental conditions upon these animals may result in the experience of discomfort, pain, and stress. The ethical debates surrounding the use of animals in research have resulted in the adoption of Directive 2010/63/EU. The present study proposes a non-contact method for monitoring the respiration rate of sheep based on video processing. The Detecron2 model was trained to segment the sheep’s body, abdominal, and facial regions in the video frames. A motion-tracking algorithm was developed to assess abdominal movement associated with the sheep’s respiratory cycle. The method was applied to videos of Rhön sheep under experimental and housing conditions, utilising two types of cameras to assess the effectiveness of the proposed approach. The mean average error (MAE) obtained was 0.79 breaths/minute for the visible and 1.83 breaths/minute for the near-infrared (NIR) method. This study demonstrates the feasibility of video technology for simultaneous and non-invasive respiration monitoring, being a crucial parameter for assessing the health deterioration of multiple laboratory animals.

Keywords

• animal welfare
• respiration rate
• sheep model
• video signal processing
• welfare assessment
• refinement