Lune

CHI2023Top-tier venue

Quantified Canine: Inferring Dog Personality From Wearables

Lakmal Meegahapola, Marios Constantinides, Zoran Radivojevic, Hongwei Li, Daniele Quercia, Michael S. Eggleston

2023Year
7Citations
1Top-tier citations

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.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 4d5cd6a7-c04d-4417-b587-17e123af5d78

Cited by top-tier papers1

Ask how each one uses it

Builds on5

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines