Development of an Automated Pain Facial Expression Detection System for Sheep (Ovis Aries)
Development of an Automated Pain Facial Expression Detection System for Sheep (Ovis Aries)
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DOI：
10.3390/ani9040196
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发表时间：
2019-04-01
期刊：
影响因子：
3
通讯作者：
Mahmoud, Marwa
中科院分区：
文献类型：
--
作者：
McLennan, Krista;Mahmoud, Marwa
简单总结 检测绵羊的疼痛迹象是一个具有挑战性的问题，因为它们是猎物物种，通常会试图隐藏任何不适或受伤的迹象。这意味着治疗生病或受伤的羊以及防止腐蹄病等传染病的进一步传播可能会很缓慢。最近开发和出版的绵羊疼痛面部表情量表（SPFES）为可靠地检测该物种的疼痛提供了一种工具。然而，由于农业集约化程度的提高以及个体农民饲养的羊群规模的扩大，用于监测绵羊是否存在可能表明疾病或受伤的行为变化的时间越来越少。拥有一个可以检测每只羊面部表情变化的自动化系统意味着农民可以直接接收有关需要评估的特定个体的信息。这将使治疗能够及时、直接地提供，减少痛苦。我们一直在进一步开发 SPFES，以使其成为一个自动化系统。在本文中，我们提出了将 SPFES 概念与自动面部表情分析技术相结合的新颖框架。 摘要 使用技术来优化每只动物的生产和管理正在成为良好农业的关键。需要对动物疾病进行实时系统检测和控制，以限制对动物福利和食品供应的影响。腐蹄病和乳腺炎等疾病会给羊带来严重的疼痛，因此早期发现对于确保有效治疗和防止羊群传播至关重要。用于评估人类和非人类疼痛的面部表情评分现已得到很好的利用，绵羊疼痛面部表情量表（SPFES）是一种可以可靠地检测该物种疼痛的工具。 SPFES 目前需要手动评分，容易受到观察者偏差的影响，而且也很耗时。计算机自动检测并指导生产者哪里需要评估和治疗的能力将增加控制疾病传播的机会。它还将有助于在国家和国际层面上预防个人、农场和景观中的耐药性。在本文中，我们提出了一个集成新颖系统的框架，该系统基于最初应用于人类面部表情识别的技术，可以在农场层面实施。据作者所知，这是该技术首次应用于绵羊来评估疼痛。
Simple Summary Detecting signs of pain in sheep is a challenging problem, as they are a prey species and would usually try to hide any signs that they are unwell or injured. This means that treating ill or injured sheep and preventing any further spread of contagious diseases such as footrot can be slow. The recent development and publication of a Sheep Pain Facial Expression Scale (SPFES) has provided a tool to reliably detect pain in this species. However, due to the increase in intensification in farming and larger flock sizes being cared for by individual farmers, there is less time to spend monitoring sheep for changes in behaviour that may indicate illness or injury. Having an automated system that could detect changes in the facial expression of individual sheep would mean that farmers could receive information directly about particular individuals that need assessment. This would allow treatment to be provided in a timely and direct manner, reducing suffering. We have been developing the SPFES further in order for it to become an automated system. In this paper, we present our novel framework that integrates SPFES concepts with automatic facial expression analysis technologies.Abstract The use of technology to optimize the production and management of each individual animal is becoming key to good farming. There is a need for the real-time systematic detection and control of disease in animals in order to limit the impact on animal welfare and food supply. Diseases such as footrot and mastitis cause significant pain in sheep, and so early detection is vital to ensuring effective treatment and preventing the spread across the flock. Facial expression scoring to assess pain in humans and non-humans is now well utilized, and the Sheep Pain Facial Expression Scale (SPFES) is a tool that can reliably detect pain in this species. The SPFES currently requires manual scoring, leaving it open to observer bias, and it is also time-consuming. The ability of a computer to automatically detect and direct a producer as to where assessment and treatment are needed would increase the chances of controlling the spread of disease. It would also aid in the prevention of resistance across the individual, farm, and landscape at both national and international levels. In this paper, we present our framework for an integrated novel system based on techniques originally applied for human facial expression recognition that could be implemented at the farm level. To the authors' knowledge, this is the first time that this technology has been applied to sheep to assess pain.