Quantified Canine: Inferring Dog Personality From Wearables


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 psychological signals of pets using wearable technologies.

Lakmal Meegahapola
Idiap Research Institute, Martigny, Switzerland
Marios Constantinides
Nokia Bell Labs, Cambridge, United Kingdom
Zoran Radivojevic
Nokia Bell Labs, Cambridge, United Kingdom
Hongwei Li
Nokia Bell Labs, Cambridge, United Kingdom
Daniele Quercia
Nokia Bell Labs, Cambridge, United Kingdom
Michael S. Eggleston
Nokia Bell Labs, Murray Hill, New Jersey, United States



会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Wearables and Materials

Room Y03+Y04
6 件の発表
2023-04-26 18:00:00
2023-04-26 19:30:00