{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T14:52:59Z","timestamp":1778251979598,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005747","name":"The A.P. Moeller Foundation for Medical Research","doi-asserted-by":"publisher","award":["L-2023-00228"],"award-info":[{"award-number":["L-2023-00228"]}],"id":[{"id":"10.13039\/501100005747","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005747","name":"The A.P. Moeller Foundation for Medical Research","doi-asserted-by":"publisher","award":["L-2024-00989"],"award-info":[{"award-number":["L-2024-00989"]}],"id":[{"id":"10.13039\/501100005747","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Monitoring experimental animals is essential for ethical, scientific, and financial reasons. Conventional observation methods are limited by subjectivity and time constraints. Camera-based monitoring combined with machine learning offers a promising solution for automating the monitoring process. This study aimed to validate and assess the performance of a machine learning model for analyzing drinking behavior in minipigs. A novel, vision-based monitoring system was developed and tested to detect drinking behavior in minipigs. The system, based on low-cost Raspberry Pi units, enabled on-site video analysis. A dataset of 5297 images was used to train a YOLOv11n object detection model to identify key features such as pig heads and water faucets. Drinking events were defined by the spatial proximity of these features within video frames. The multi-class object detection model achieved an accuracy of above 97%. Manual validation using human-annotated ground truth on 72 h of video yielded an overall accuracy of 99.7%, with a precision of 99.7%, recall of 99.2%, and F1-score of 99.5%. Drinking patterns for three pigs were analyzed using 216 h of video. The results revealed a bimodal drinking pattern and substantial inter-pig variability. A limitation to the study was chosen methods missing distinguishment between multiple pigs and the absence of quantification of water intake. This study demonstrates the feasibility of a low-cost, computer vision-based system for monitoring drinking behavior in individually housed experimental pigs, supporting earlier detection of illness.<\/jats:p>","DOI":"10.3390\/s26020402","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T10:10:50Z","timestamp":1767867050000},"page":"402","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Developing and Assessing the Performance of a Machine Learning Model for Analyzing Drinking Behaviors in Minipigs for Experimental Research"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3127-8535","authenticated-orcid":false,"given":"Frederik","family":"Deutch","sequence":"first","affiliation":[{"name":"Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark"},{"name":"Department of Urology, Aarhus University Hospital, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9508-8939","authenticated-orcid":false,"given":"Lars Schmidt","family":"Hansen","sequence":"additional","affiliation":[{"name":"Department of Electro- and Computer Technology, Section of Biomedical Engineering, Aarhus University, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0602-0598","authenticated-orcid":false,"given":"Firas Omar","family":"Saleh","sequence":"additional","affiliation":[{"name":"Department of Electro- and Computer Technology, Section of Biomedical Engineering, Aarhus University, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9829-5860","authenticated-orcid":false,"given":"Marc Gjern","family":"Weiss","sequence":"additional","affiliation":[{"name":"Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2786-0388","authenticated-orcid":false,"given":"Constanca","family":"Figueiredo","sequence":"additional","affiliation":[{"name":"Institute of Transfusion Medicine and Transplant Engineering, Hannover Medical School, 30625 Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8014-8387","authenticated-orcid":false,"given":"Cyril","family":"Moers","sequence":"additional","affiliation":[{"name":"Department of Surgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9109-5521","authenticated-orcid":false,"given":"Anna Krarup","family":"Keller","sequence":"additional","affiliation":[{"name":"Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark"},{"name":"Department of Urology, Aarhus University Hospital, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9985-4588","authenticated-orcid":false,"given":"Stefan Rahr","family":"Wagner","sequence":"additional","affiliation":[{"name":"Department of Electro- and Computer Technology, Section of Biomedical Engineering, Aarhus University, 8000 Aarhus, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Mir\u00f3, S., Tecles, F., Ram\u00f3n, M., Escribano, D., Hern\u00e1ndez, F., Madrid, J., Orengo, J., Mart\u00ednez-Subiela, S., Manteca, X., and Cer\u00f3n, J.J. 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