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.

Quantified Canine: Inferring Dog Personality From Wearables / Meegahapola, Lakmal; Constantinides, Marios; Radivojevic, Zoran; Li, Hongwei; Quercia, Daniele; Eggleston, Michael S. - (2023), pp. 1-19. (Intervento presentato al convegno CHI '23: CHI Conference on Human Factors in Computing Systems tenutosi a Hamburg (DEU) nel April 23 - 28, 2023) [10.1145/3544548.3581088].

Quantified Canine: Inferring Dog Personality From Wearables

Quercia, Daniele;
2023

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 psychological signals of pets using wearable technologies.
2023
978-1-4503-9421-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2996086