A Wearable Sensor System for Lameness Detection in Dairy Cattle

Abstract

Cow lameness is a common manifestation in dairy cattle that causes severe health and life quality issues to cows, including pain and a reduction in their life expectancy. In our previous work, we introduced an algorithmic approach to automatically detect anomalies in the walking pattern of cows using a wearable motion sensor. In this article, we provide further insights into a system for automatic lameness detection, including the decisions we made when designing the system, the requirements that drove these decisions and provide further insight into the algorithmic approach. Results from a controlled experiment we conducted indicate that our approach can detect deviations in cows’ gait with an accuracy of 91.1%. The information provided by our system can be useful to spot lameness-related diseases automatically and alarm veterinarians.

Keywords

• gait analysis
• anomaly detection
• unsupervised machine learning