Evaluation of lameness detection using radar sensing in ruminants

Busin, V. , Viora, L. , King, G. , Tomlinson, M., Le Kernec, J. , Jonsson, N. and Fioranelli, F. (2019) Evaluation of lameness detection using radar sensing in ruminants. Veterinary Record, 185(18), 572. (doi: 10.1136/vr.105407) (PMID:31554712)

193981.pdf - Accepted Version



Background: Lameness is a major health, welfare and production-limiting condition for the livestock industries. The current ‘gold-standard’ method of assessing lameness by visual locomotion scoring is subjective and time consuming, whereas recent technological advancements have enabled the development of alternative and more objective methods for its detection. Methods: This study evaluated a novel lameness detection method using micro-Doppler radar signatures to categorise animals as lame or non-lame. Animals were visually scored by veterinarian and radar data were collected for the same animals. Results: A machine learning algorithm was developed to interpret the radar signatures and provide automatic classification of the animals. Using veterinary scoring as a standard method, the classification by radar signature provided 85 per cent sensitivity and 81 per cent specificity for cattle and 96 per cent sensitivity and 94 per cent specificity for sheep. Conclusion: This radar sensing method shows promise for the development of a highly functional, rapid and reliable recognition tool of lame animals, which could be integrated into automatic, on-farm systems for sheep and cattle.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Jonsson, Professor Nicholas and Tomlinson, Mr Martin and Fioranelli, Dr Francesco and King, Mr George and Busin, Valentina and Viora, Dr Lorenzo and Le Kernec, Dr Julien
Authors: Busin, V., Viora, L., King, G., Tomlinson, M., Le Kernec, J., Jonsson, N., and Fioranelli, F.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Veterinary Record
Publisher:BMJ Publishing Group
ISSN (Online):2042-7670
Published Online:25 September 2019
Copyright Holders:Copyright © 2019 British Veterinary Association
First Published:First published in Veterinary Record 185(18): 572
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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