Clustering of facial action units in horses with pain

Pain assessment in horses is a relatively new topic in veterinary medicine and there is no universally accepted pain scale for assessing pain in horses. Assessing and managing pain is essential for the welfare of the animal. Several different pain scale systems have been made for both humans and...

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Autor principal: Silventoinen, Alina
Formato: Second cycle, A2E
Lenguaje:sueco
Inglés
Publicado: 2019
Materias:
Acceso en línea:https://stud.epsilon.slu.se/14892/
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author Silventoinen, Alina
author_browse Silventoinen, Alina
author_facet Silventoinen, Alina
author_sort Silventoinen, Alina
collection Epsilon Archive for Student Projects
description Pain assessment in horses is a relatively new topic in veterinary medicine and there is no universally accepted pain scale for assessing pain in horses. Assessing and managing pain is essential for the welfare of the animal. Several different pain scale systems have been made for both humans and animals. An example of this is Composite Pain Scale (CPS), where several parameters, such as behaviour and physiological parameters, are being assessed at the same time. Studies of pain assessment through facial expressions are several in human medicine but only a few studies have been made on horses. The Horse Grimace Scale and Equine Pain Scale are examples of studies on facial expressions and pain in horses. Equine Facial Action Coding System (EquiFACS) is a method of identifying and coding facial expressions on horses on the basis of underlying facial musculature and muscle movement. The system is based on Action Units and Action Descriptors which each represent a separate movement. Facial actions have been used together with artificial intelligence in order to evaluate pain in humans. This is probably possible to do with horses as well, but more training data is needed. This study included 28 films of horses with and without pain, both in experimental and clinical setting. The films were coded using Equine Facial Action Coding System in order to analyse how the different facial action units cluster in horses with and without pain. Relevant facial actions for the equine pain face were selected in order to visualise changes in duration, frequency and occurrence between painful and non-painful horses, as well as upper and lower facial actions. According to the two-sample t test, only one facial action unit (AD38, nostril dilator) had statistical significance. However, the linear discriminant analysis showed a 92% correct classification in duration in pain/no pain. Stress may have influenced pain behaviour due to stress-induced analgesia or hyperalgesia. A larger sample size is needed in order to investigate this further, but there is potential for EquiFACS to be used as a tool for objective pain scoring.
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spelling RepoSLU148922021-03-01T00:15:07Z https://stud.epsilon.slu.se/14892/ Clustering of facial action units in horses with pain Silventoinen, Alina Veterinary science and hygiene - General aspects Pain assessment in horses is a relatively new topic in veterinary medicine and there is no universally accepted pain scale for assessing pain in horses. Assessing and managing pain is essential for the welfare of the animal. Several different pain scale systems have been made for both humans and animals. An example of this is Composite Pain Scale (CPS), where several parameters, such as behaviour and physiological parameters, are being assessed at the same time. Studies of pain assessment through facial expressions are several in human medicine but only a few studies have been made on horses. The Horse Grimace Scale and Equine Pain Scale are examples of studies on facial expressions and pain in horses. Equine Facial Action Coding System (EquiFACS) is a method of identifying and coding facial expressions on horses on the basis of underlying facial musculature and muscle movement. The system is based on Action Units and Action Descriptors which each represent a separate movement. Facial actions have been used together with artificial intelligence in order to evaluate pain in humans. This is probably possible to do with horses as well, but more training data is needed. This study included 28 films of horses with and without pain, both in experimental and clinical setting. The films were coded using Equine Facial Action Coding System in order to analyse how the different facial action units cluster in horses with and without pain. Relevant facial actions for the equine pain face were selected in order to visualise changes in duration, frequency and occurrence between painful and non-painful horses, as well as upper and lower facial actions. According to the two-sample t test, only one facial action unit (AD38, nostril dilator) had statistical significance. However, the linear discriminant analysis showed a 92% correct classification in duration in pain/no pain. Stress may have influenced pain behaviour due to stress-induced analgesia or hyperalgesia. A larger sample size is needed in order to investigate this further, but there is potential for EquiFACS to be used as a tool for objective pain scoring. 2019-08-19 Second cycle, A2E NonPeerReviewed application/pdf sv https://stud.epsilon.slu.se/14892/7/silventoinen_a_190123.pdf Silventoinen, Alina, 2019. Clustering of facial action units in horses with pain. Second cycle, A2E. Uppsala: (VH) > Dept. of Clinical Sciences (until 231231) <https://stud.epsilon.slu.se/view/divisions/OID-715.html> urn:nbn:se:slu:epsilon-s-10997 eng
spellingShingle Veterinary science and hygiene - General aspects
Silventoinen, Alina
Clustering of facial action units in horses with pain
title Clustering of facial action units in horses with pain
title_full Clustering of facial action units in horses with pain
title_fullStr Clustering of facial action units in horses with pain
title_full_unstemmed Clustering of facial action units in horses with pain
title_short Clustering of facial action units in horses with pain
title_sort clustering of facial action units in horses with pain
topic Veterinary science and hygiene - General aspects
url https://stud.epsilon.slu.se/14892/
https://stud.epsilon.slu.se/14892/