Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness
IntroductionLameness is a major welfare challenge facing the dairy industry worldwide. Monitoring herd lameness prevalence, and early detection and therapeutic intervention are important aspects of lameness control in dairy herds. The objective of this study was to evaluate the performance of a comm...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-06-01
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| Series: | Frontiers in Veterinary Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2023.1111057/full |
| _version_ | 1797805771344314368 |
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| author | Alkiviadis Anagnostopoulos Bethany E. Griffiths Nektarios Siachos Joseph Neary Robert F. Smith Georgios Oikonomou |
| author_facet | Alkiviadis Anagnostopoulos Bethany E. Griffiths Nektarios Siachos Joseph Neary Robert F. Smith Georgios Oikonomou |
| author_sort | Alkiviadis Anagnostopoulos |
| collection | DOAJ |
| description | IntroductionLameness is a major welfare challenge facing the dairy industry worldwide. Monitoring herd lameness prevalence, and early detection and therapeutic intervention are important aspects of lameness control in dairy herds. The objective of this study was to evaluate the performance of a commercially available video surveillance system for automatic detection of dairy cattle lameness (CattleEye Ltd).MethodsThis was achieved by first measuring mobility score agreement between CattleEye and two veterinarians (Assessor 1 and Assessor 2), and second, by investigating the ability of the CattleEye system to detect cows with potentially painful foot lesions. We analysed 6,040 mobility scores collected from three dairy farms. Inter-rate agreement was estimated by calculating percentage agreement (PA), Cohen’s kappa (κ) and Gwet’s agreement coefficient (AC). Data regarding the presence of foot lesions were also available for a subset of this dataset. The ability of the system to predict the presence of potentially painful foot lesions was tested against that of Assessor 1 by calculating measures of accuracy, using lesion records during the foot trimming sessions as reference.ResultsIn general, inter-rater agreement between CattleEye and either human assessor was strong and similar to that between the human assessors, with PA and AC being consistently above 80% and 0.80, respectively. Kappa agreement between CattleEye and the human scorers was in line with previous studies (investigating agreement between human assessors) and within the fair to moderate agreement range. The system was more sensitive than Assessor 1 in identifying cows with potentially painful lesions, with 0.52 sensitivity and 0.81 specificity compared to the Assessor’s 0.29 and 0.89 respectively.DiscussionThis pilot study showed that the CattleEye system achieved scores comparable to that of two experienced veterinarians and was more sensitive than a trained veterinarian in detecting painful foot lesions. |
| first_indexed | 2024-03-13T05:57:05Z |
| format | Article |
| id | doaj.art-94d96b2c16f54685bf8d2881d2ae9047 |
| institution | Directory Open Access Journal |
| issn | 2297-1769 |
| language | English |
| last_indexed | 2024-03-13T05:57:05Z |
| publishDate | 2023-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Veterinary Science |
| spelling | doaj.art-94d96b2c16f54685bf8d2881d2ae90472023-06-13T04:21:50ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692023-06-011010.3389/fvets.2023.11110571111057Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lamenessAlkiviadis AnagnostopoulosBethany E. GriffithsNektarios SiachosJoseph NearyRobert F. SmithGeorgios OikonomouIntroductionLameness is a major welfare challenge facing the dairy industry worldwide. Monitoring herd lameness prevalence, and early detection and therapeutic intervention are important aspects of lameness control in dairy herds. The objective of this study was to evaluate the performance of a commercially available video surveillance system for automatic detection of dairy cattle lameness (CattleEye Ltd).MethodsThis was achieved by first measuring mobility score agreement between CattleEye and two veterinarians (Assessor 1 and Assessor 2), and second, by investigating the ability of the CattleEye system to detect cows with potentially painful foot lesions. We analysed 6,040 mobility scores collected from three dairy farms. Inter-rate agreement was estimated by calculating percentage agreement (PA), Cohen’s kappa (κ) and Gwet’s agreement coefficient (AC). Data regarding the presence of foot lesions were also available for a subset of this dataset. The ability of the system to predict the presence of potentially painful foot lesions was tested against that of Assessor 1 by calculating measures of accuracy, using lesion records during the foot trimming sessions as reference.ResultsIn general, inter-rater agreement between CattleEye and either human assessor was strong and similar to that between the human assessors, with PA and AC being consistently above 80% and 0.80, respectively. Kappa agreement between CattleEye and the human scorers was in line with previous studies (investigating agreement between human assessors) and within the fair to moderate agreement range. The system was more sensitive than Assessor 1 in identifying cows with potentially painful lesions, with 0.52 sensitivity and 0.81 specificity compared to the Assessor’s 0.29 and 0.89 respectively.DiscussionThis pilot study showed that the CattleEye system achieved scores comparable to that of two experienced veterinarians and was more sensitive than a trained veterinarian in detecting painful foot lesions.https://www.frontiersin.org/articles/10.3389/fvets.2023.1111057/fullcattle lamenessautomated systemfoot lesionsmobility scoringartificial intelligence |
| spellingShingle | Alkiviadis Anagnostopoulos Bethany E. Griffiths Nektarios Siachos Joseph Neary Robert F. Smith Georgios Oikonomou Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness Frontiers in Veterinary Science cattle lameness automated system foot lesions mobility scoring artificial intelligence |
| title | Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| title_full | Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| title_fullStr | Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| title_full_unstemmed | Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| title_short | Initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| title_sort | initial validation of an intelligent video surveillance system for automatic detection of dairy cattle lameness |
| topic | cattle lameness automated system foot lesions mobility scoring artificial intelligence |
| url | https://www.frontiersin.org/articles/10.3389/fvets.2023.1111057/full |
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