Analysis of Problem Behavior in Pet Dogs Using Artificial Intelligence Technology: A Pilot Study
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Keywords

pet dog
anxiety
aggression
excitability
movement speed
switching frequency
artificial intelligence
affective computing

Abstract

Introduction. Research on problem behavior in pet dogs is underrepresented in Russian zoopsychology, primarily due to the lack of measurable metrics for objective assessment of their behavior. Drawing on international studies, this work aims to identify objective markers of problem behavior in pet dogs.

Methods. The pilot sample included 35 dogs—15 males and 20 females. The assessment consisted of the owner questionnaire CBARQ and behavioral tests: meet and greet, interaction with owner, and interaction with a stranger. Behavioral patterns were extracted from video recordings using the YOLO neural network. Movement speed was calculated using the Euclidean distance formula, and switching frequency was determined from behavioral pattern transitions.

Results. Based on the median value of the "Fear and Anxiety" scale from CBARQ, dogs were divided into anxious and calm groups. Anxious dogs showed higher baseline values during the stranger interaction test and greater distance from the owner during all tests. From the anxious group, excitable dogs were additionally identified. Average speed was higher in excitable dogs and anxious dogs compared to calm dogs—most pronounced in anxious dogs. Switching frequency calculations showed differences in behavioral patterns depending on the dog's psychological profile.

Discussion. The combination of various methods made it possible to analyze possible markers of behavioral disorders, taking into account the dog's chart, visual observation (distance between frames), data on motor activity dynamics, and behavior patterns. As spart of the pilot study, test ethograms were obtained, allowing for the objective classification of a dog's behavior type. The possibility of adding movement speed and switching frequency to the dog ethogram, as well as the results of anxiety, aggression, and excitability analysis based on owner surveys, was demonstrated. It was found that contact with humans is a manifesting factor that allows the use of selected metrics to identify problematic dog behavior.

https://doi.org/10.21702/rpj.2025.4.11
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PDF (Russian)

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