Wireless Sensor Collar for Automatic Recognition of Canine Agility Activities

Canine agility is a rapidly growing sport where dogs and their handlers navigate obstacle courses. Recent studies show that over 40% of all agility dogs suffer an injury while training or competing. By collecting and analyzing sensor measurements from a wearable computer while dogs participate in the sport, we hope to better inform dog handlers and trainers and improve the performance and overall health of their dogs. As a first step towards this long-term project goal, we present the initial validation of a bespoke collar-worn activity tracker and machine learning classifier for recognizing agility activities. The ability to classify agility activities from collar-worn sensors will provide the groundwork for further analysis of relative activity exertion levels, activity variance with repetitions, and gait regularity. To validate our system, we conducted a pilot study of six dogs performing a short agility course including three different agility obstacles. Our wireless sensor collar was able to provide data in real-time via WiFi while dogs navigated the obstacles. Our MINIROCKET-based machine learning classifier achieved 85% accuracy across the pilot study data.