Quantified Canine: Inferring Dog Personality From Wearables
Lakmal Meegahapola, Marios Constantinides, Zoran Radivojevic, Hongwei Li, Daniele Quercia, Michael S. Eggleston
摘要
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.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper5
- Generalization and Personalization of Mobile Sensing-Based Mood Inference Models: An Analysis of College Students in Eight CountriesLakmal Meegahapola, William Droz, Peter Kun, Amalia de Götzen 等UbiComp 2023 · 被引用 55 次
- One More Bite?: Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-ReportsLakmal Meegahapola, Salvador Ruiz-Correa, Viridiana del Carmen Robledo-Valero, Emilio Ernesto Hernandez-Huerfano 等UbiComp 2021 · 被引用 37 次
- First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile SensingWeichen Wang, Subigya Nepal, Jeremy F. Huckins, Lessley Hernandez 等UbiComp 2022 · 被引用 33 次
- Predicting Brain Functional Connectivity Using Mobile SensingMikio Obuchi, Jeremy F. Huckins, Weichen Wang, Alex daSilva 等UbiComp 2020 · 被引用 30 次
- Detecting Job Promotion in Information Workers Using Mobile SensingSubigya Nepal, Shayan Mirjafari, Gonzalo J. Martínez, Pino G. Audia 等UbiComp 2020 · 被引用 26 次
相关 Paper
- Watch your Watch: Inferring Personality Traits from Wearable Activity TrackersNoé Zufferey, Mathias Humbert, Romain Tavenard, Kévin HugueninUSENIX Security 2023
- A Multisensor Person-Centered Approach to Understand the Role of Daily Activities in Job Performance with Organizational PersonasVedant Das Swain, Koustuv Saha, Hemang Rajvanshy, Anusha Sirigiri 等UbiComp 2020 · 被引用 49 次
- MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with SpeechYoung-Ho Kim, Diana Chou, Bongshin Lee, Margaret K. Danilovich 等CHI 2022 · 被引用 40 次
- ChallengeDetect: Investigating the Potential of Detecting In-Game Challenge Experience from Physiological MeasuresXiaolan Peng, Xurong Xie, Jin Huang, Chutian Jiang 等CHI 2023 · 被引用 16 次
- HandSAW: Wearable Hand-based Event Recognition via On-Body Surface Acoustic WavesKaylee Yaxuan Li, Yasha Iravantchi, Yichen Zhu, Hyunmin Park 等UbiComp 2025 · 被引用 5 次
