How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households

Smit M; Corner-Thomas R; Draganova I; Andrews C; Thomas D

How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households

dc.citation.issue	8
dc.citation.volume	24
dc.contributor.author	Smit M
dc.contributor.author	Corner-Thomas R
dc.contributor.author	Draganova I
dc.contributor.author	Andrews C
dc.contributor.author	Thomas D
dc.contributor.editor	Friedrich CM
dc.coverage.spatial	Switzerland
dc.date.accessioned	2024-08-19T02:58:25Z
dc.date.available	2024-08-19T02:58:25Z
dc.date.issued	2024-04-19
dc.description.abstract	Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.
dc.description.confidential	false
dc.edition.edition	April-2 2024
dc.format.pagination	2623-
dc.identifier.author-url	https://www.ncbi.nlm.nih.gov/pubmed/38676239
dc.identifier.citation	Smit M, Corner-Thomas RA, Draganova I, Andrews CJ, Thomas DG. (2024). How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households.. Sensors (Basel). 24. 8. (pp. 2623-).
dc.identifier.doi	10.3390/s24082623
dc.identifier.eissn	1424-8220
dc.identifier.elements-type	journal-article
dc.identifier.issn	1424-8220
dc.identifier.number	2623
dc.identifier.pii	s24082623
dc.identifier.uri	https://mro.massey.ac.nz/handle/10179/71338
dc.language	eng
dc.publisher	MDPI (Basel, Switzerland)
dc.publisher.uri	https://www.mdpi.com/1424-8220/24/8/2623
dc.relation.isPartOf	Sensors (Basel)
dc.rights	(c) 2024 The Author/s
dc.rights	CC BY 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	accelerometry
dc.subject	behaviour
dc.subject	domestic cat
dc.subject	feline
dc.subject	home environment
dc.subject	machine learning
dc.subject	Animals
dc.subject	Cats
dc.subject	Machine Learning
dc.subject	Accelerometry
dc.subject	Pets
dc.subject	Behavior, Animal
dc.subject	Male
dc.subject	Female
dc.subject	Seasons
dc.subject	Humans
dc.subject	Family Characteristics
dc.title	How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households
dc.type	Journal article
pubs.elements-id	488376
pubs.organisational-group	Other