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DOI: 10.1055/s-0044-1786205
Wearable Activity Monitor Detection of Rhythmicity in Canine Agility Weaving Performance
Authors
Introduction: The weave pole obstacle has been implicated in agility-related injuries and it has been speculated that changes in agility obstacle performance could indicate an injury. It is currently unknown how much variability in obstacle performance exists within a single dog. Wearable sensors have been developed to detect performance of specific agility obstacles. Our aim was to evaluate variability of weave pole performance within dogs and determine whether a wearable sensor could detect and quantify variability.
Materials and Methods: Twenty-two Master’s level agility dogs of various breeds performed four repetitions of the weave pole obstacle while wearing a custom designed activity monitor collar. A measure of rhythmicity was then computed from activity monitor data, which corresponded to the similarity of the dog’s weaving pattern throughout obstacle performance. Linear mixed models were used to estimate the amount of variance due to between dog variability (rather than within dog variability).
Results: The measure of rhythmicity varied between and within dogs, with 34% of total variance attributable to between dog variation (ICC=0.34). In contrast, dogs tended to be more consistent in obstacle completion time, with 84% of the variability in time to obstacle completion attributable to between dog variation (ICC=0.84).
Discussion/Conclusion: These data suggest a higher than expected level of within dog variability in weave obstacle performance. Despite this result, the wearable sensor was able to predict the level of variability within and between repetitions. Limitations of this study include a relatively small sample size and a small number of repetitions per dog.
Acknowledgments:
This study was funded by the American Kennel Club Canine Health Foundation.
Publication History
Article published online:
09 April 2024
© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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