Quantified Canine: Inferring Dog Personality From Wearables

Abstract

Being able to assess dog personality can be used to, for example, match shelter dogs with future owners, and personalize dog activities. Such an assessment typically relies on experts or psychological scales administered to dog owners, both of which are costly. To tackle that challenge, we built a device called "Patchkeeper" that can be strapped on the pet's chest and measures activity through an accelerometer and a gyroscope. In an in-the-wild deployment involving 12 healthy dogs, we collected 1300 hours of sensor activity data and dog personality test results from two validated questionnaires. By matching these two datasets, we trained ten machine-learning classifiers that predicted dog personality from activity data, achieving AUCs in [0.63-0.90], suggesting the value of tracking the psychological signals of pets using wearable technologies.CCS Concepts: • Human-centered computing → Ubiquitous and mobile devices; Computer supported cooperative work; Empirical studies in ubiquitous and mobile computing; User studies.

Development of a Dog Health Score Using an Artificial Intelligence Disease Prediction Algorithm Based on Multifaceted Data

“…The validity of the results was ascertained through comparison with diagnoses made by veterinarians. The Health Score emerged as an effective tool for articulating the health status of companion dogs [27]. For dog owners lacking veterinary expertise, visually assessing a dog's health can be challenging; therefore, the developed method holds significance in evaluating a dog's condition based on daily activities.…”