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Article

Objective Video-Based Assessment of ADHD-Like Canine Behavior Using Machine Learning

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Information Systems Department, University of Haifa, Haifa 3498838, Israel
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Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE7 7XA, UK
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Department of Automation and Control Processes, Saint Petersburg Electrotechnical University “LETI”, 197376 Saint Petersburg, Russia
*
Author to whom correspondence should be addressed.
Academic Editor: Lynette A. Hart
Animals 2021, 11(10), 2806; https://doi.org/10.3390/ani11102806
Received: 30 July 2021 / Revised: 3 September 2021 / Accepted: 13 September 2021 / Published: 26 September 2021
(This article belongs to the Special Issue Animal-Centered Computing)
This paper applies machine learning techniques to propose an objective video-based method for assessing the degree of canine ADHD-like behavior in veterinary consultation room. The method is evaluated using clinical data of dog patients in a veterinary clinic, as well as in a focus group of experts.
Canine ADHD-like behavior is a behavioral problem that often compromises dogs’ well-being, as well as the quality of life of their owners; early diagnosis and clinical intervention are often critical for successful treatment, which usually involves medication and/or behavioral modification. Diagnosis mainly relies on owner reports and some assessment scales, which are subject to subjectivity. This study is the first to propose an objective method for automated assessment of ADHD-like behavior based on video taken in a consultation room. We trained a machine learning classifier to differentiate between dogs clinically treated in the context of ADHD-like behavior and health control group with 81% accuracy; we then used its output to score the degree of exhibited ADHD-like behavior. In a preliminary evaluation in clinical context, in 8 out of 11 patients receiving medical treatment to treat excessive ADHD-like behavior, H-score was reduced. We further discuss the potential applications of the provided artifacts in clinical settings, based on feedback on H-score received from a focus group of four behavior experts. View Full-Text
Keywords: behavioral assessment; veterinary science; machine learning; ADHD-like behavior behavioral assessment; veterinary science; machine learning; ADHD-like behavior
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MDPI and ACS Style

Fux, A.; Zamansky, A.; Bleuer-Elsner, S.; van der Linden, D.; Sinitca, A.; Romanov, S.; Kaplun, D. Objective Video-Based Assessment of ADHD-Like Canine Behavior Using Machine Learning. Animals 2021, 11, 2806. https://doi.org/10.3390/ani11102806

AMA Style

Fux A, Zamansky A, Bleuer-Elsner S, van der Linden D, Sinitca A, Romanov S, Kaplun D. Objective Video-Based Assessment of ADHD-Like Canine Behavior Using Machine Learning. Animals. 2021; 11(10):2806. https://doi.org/10.3390/ani11102806

Chicago/Turabian Style

Fux, Asaf, Anna Zamansky, Stephane Bleuer-Elsner, Dirk van der Linden, Aleksandr Sinitca, Sergey Romanov, and Dmitrii Kaplun. 2021. "Objective Video-Based Assessment of ADHD-Like Canine Behavior Using Machine Learning" Animals 11, no. 10: 2806. https://doi.org/10.3390/ani11102806

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