Open AccessArticle
Computational Analysis of Movement Patterns of Dogs with ADHD-Like Behavior
by
1, 1,*, 1, 2
, 2, 2
, 3 and 4
1
Information Systems Department, University of Haifa, Haifa 3498838, Israel
2
Department of Automation and Control Processes, Saint Petersburg Electrotechnical University “LETI”, Saint Petersburg 197376, Russia
3
Clinique de la Tivolliere, 38340 Voreppe, France
4
Department of Computer Science, University of Bristol, Bristol BS8 1TH, UK
*
Author to whom correspondence should be addressed.
Received: 18 October 2019 / Revised: 10 December 2019 / Accepted: 11 December 2019 / Published: 13 December 2019
Simple Summary
ADHD-like (attention deficit hyperactivity disorder) behavior in dogs may be expressed as impulsivity, inattentiveness, or aggression, compromising both dog and owner quality of life. Its treatment in a clinical setting requires behavioral modification and sometimes a medical treatment is added. There is a lack of objective tools for assessment and diagnosis of the problem, and behavioral experts mostly rely on owner reports. To address this gap, in this paper we use a self-developed computational tool which automatically analyzes movement of a dog from video footage collected during behavioral consultation. Based on a computational analysis of behavioral consultations of 12 dogs medically treated due to ADHD-like behavior and of a control group of 12 dogs with no reported behavioral problems, we identify three dimensions of characteristic movement patterns of dogs with ADHD-like behaviors, which are detectable during consultation. These include (i) high speed of movement, (ii) large coverage of room space, and (iii) frequent re-orientation in room space. These patterns can form the basis for computational methods for objective assessment of dogs with ADHD-like behavior that could help for diagnosis and clinical treatment of the disorder.