Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals.
Predicting Lameness in Sheep Activity Using Tri-Axial Acceleration Signals.
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DOI：
10.3390/ani8010012
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发表时间：
2018-01-11
期刊：
影响因子：
--
通讯作者：
Trotter M
中科院分区：
文献类型：
--
作者：
Barwick J;Lamb D;Dobos R;Schneider D;Welch M;Trotter M
监测在大范围条件下饲养的牲畜具有挑战性，在个体层面上观察动物行为时尤其困难。跛行是一种疾病症状，传统上依靠肉眼检查来检测那些行走模式不正常的动物。最近，加速度计传感器也被用于其他畜牧业，以检测跛行的动物。这些设备能够记录活动强度的变化，使我们能够区分放牧、散步和休息的动物。使用这些动物身上的传感器，可以准确地从连接在耳朵上的传感器检测到吃草、站立、行走和跛行。随着进一步的发展，这种分类算法可以与自动牲畜监测系统相联系，以提供关于个人健康状况的实时信息，这在目前广泛的牲畜生产系统下几乎是不可能的。跛行是一种临床症状，与世界各地的许多绵羊疾病有关，对体重增加、繁殖力和羔羊初生体重有不利影响，并增加继发性疾病的风险。目前识别跛行动物的方法依赖于劳动密集型的肉眼检查。目前这项研究的目的是确定项圈、腿和耳朵连接的三轴加速度计区分绵羊健全和跛行步态运动的能力。将数据划分为10个S互斥行为时期，并进行二次判别分析。初步分析表明，从所有部署模式来看，声音放牧和立地放牧对跛行放牧事件的误分类都很高。最终的分类模型包括跛行和所有声音活动类别，对于耳朵、项圈和腿的展开，对跛行的预测准确率分别为82%、35%和87%。腿部加速度计数据集中声音行走和跛行的错误分类突出了耳朵连接模式对于基于时间序列加速度计数据的跛行步态特征分类的优越性。
Monitoring livestock farmed under extensive conditions is challenging and this is particularly difficult when observing animal behaviour at an individual level. Lameness is a disease symptom that has traditionally relied on visual inspection to detect those animals with an abnormal walking pattern. More recently, accelerometer sensors have been used in other livestock industries to detect lame animals. These devices are able to record changes in activity intensity, allowing us to differentiate between a grazing, walking, and resting animal. Using these on-animal sensors, grazing, standing, walking, and lame walking were accurately detected from an ear attached sensor. With further development, this classification algorithm could be linked with an automatic livestock monitoring system to provide real time information on individual health status, something that is practically not possible under current extensive livestock production systems. Lameness is a clinical symptom associated with a number of sheep diseases around the world, having adverse effects on weight gain, fertility, and lamb birth weight, and increasing the risk of secondary diseases. Current methods to identify lame animals rely on labour intensive visual inspection. The aim of this current study was to determine the ability of a collar, leg, and ear attached tri-axial accelerometer to discriminate between sound and lame gait movement in sheep. Data were separated into 10 s mutually exclusive behaviour epochs and subjected to Quadratic Discriminant Analysis (QDA). Initial analysis showed the high misclassification of lame grazing events with sound grazing and standing from all deployment modes. The final classification model, which included lame walking and all sound activity classes, yielded a prediction accuracy for lame locomotion of 82%, 35%, and 87% for the ear, collar, and leg deployments, respectively. Misclassification of sound walking with lame walking within the leg accelerometer dataset highlights the superiority of an ear mode of attachment for the classification of lame gait characteristics based on time series accelerometer data.
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影响因子：
2.3
作者：
Blackie, Nicola;Amory, Jonathan;Scaife, Jes
通讯作者：
Scaife, Jes
影响因子：
1.1
作者：
Colditz, I. G.;Paull, D. R.;Lee, C.
通讯作者：
Lee, C.
影响因子：
1.4
作者：
Greenwood, Paul L.;Valencia, Philip;Purvis, Ian W.
通讯作者：
Purvis, Ian W.
DOI：
10.1055/s-0038-1632766
发表时间：
2003-01-01
影响因子：
1.3
作者：
Besancon, MF;Conzemius, MG;Ritter, MJ
通讯作者：
Ritter, MJ
影响因子：
1.8
作者：
Hodgkinson, O.
通讯作者：
Hodgkinson, O.