Using imagery and computer vision as remote monitoring methods for early detection of respiratory disease in pigs

呼吸频率 心率 呼吸速率 生命体征 呼吸 医学 血压 外科 内科学 解剖
作者
Maria Jorquera-Chavez,Sigfredo Fuentes,Frank R. Dunshea,R. D. Warner,Tomas Poblete,Ranjith Rajasekharan Unnithan,R. S. Morrison,Ellen C. Jongman
出处
期刊:Computers and Electronics in Agriculture [Elsevier BV]
卷期号:187: 106283-106283 被引量:17
标识
DOI:10.1016/j.compag.2021.106283
摘要

Respiratory diseases in pigs impact the wellbeing of animals and increase the cost of production. One of the most appropriate approaches to minimizing these negative effects is the early detection of ill animals. The use of cameras coupled with computer-based techniques could assist the early detection of physiological changes in pigs when they are beginning to become ill and prior to exhibiting clinical signs. This study consisted of two experiments that aimed to (a) evaluate the use of computer-based techniques over RGB (red, green, and blue) and thermal infrared imagery to measure heart rate and respiration rate of pigs, and (b) to investigate whether eye-temperature, heart rate and respiration rate assessed remotely could be used to identify early signs of respiratory diseases in free-moving, and group-housed growing pigs in a commercial piggery. In the first experiment, the remotely-obtained heart rate and respiration rate were compared with the measures obtained with standard methods, showing positive correlations (r = 0.61 – 0.66; p < 0.05). In the second experiment, pigs were recorded by overhead cameras and the remotely-obtained physiological measures were analysed to identify whether physiological changes could be detected in sick pigs before clinical signs were observed. The changes in eye-temperature and heart rate remotely obtained showed clear differences between sick and healthy pigs two days before clinical signs were detected. While significant changes in respiration rate occurred the day before clinical signs of illness were identified. The results of the present study indicate the possible use of computer vision technique for constant animal monitoring and rapid detection of physiological changes related to illness in commercial pigs. Further research is recommended to continue the development, automatization, and commercial practicality of this novel technology.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
含蓄大雁发布了新的文献求助10
1秒前
1秒前
香蕉雨泽完成签到,获得积分10
2秒前
caochang完成签到,获得积分10
2秒前
xxx发布了新的文献求助10
3秒前
心心发布了新的文献求助10
3秒前
一次性过完成签到,获得积分10
3秒前
4秒前
4秒前
XIAONAN发布了新的文献求助10
4秒前
zsl完成签到 ,获得积分10
5秒前
96完成签到 ,获得积分10
5秒前
YIYI完成签到,获得积分10
5秒前
6秒前
杨钧贺发布了新的文献求助10
7秒前
林惊语完成签到 ,获得积分10
7秒前
肖志勇完成签到,获得积分10
7秒前
灵巧尔云发布了新的文献求助10
7秒前
燕武发布了新的文献求助10
8秒前
saya发布了新的文献求助10
8秒前
xxx完成签到,获得积分10
8秒前
浮游应助纯真的德地采纳,获得10
8秒前
8秒前
8秒前
龙龙ff11_完成签到,获得积分10
8秒前
共享精神应助文静煜城采纳,获得10
9秒前
9秒前
TeeteePor完成签到,获得积分10
9秒前
fei_hong完成签到,获得积分10
9秒前
浮游应助donk采纳,获得10
10秒前
唐一应助donk采纳,获得10
10秒前
汉堡包应助敏感沛春采纳,获得10
10秒前
刘梦通发布了新的文献求助10
10秒前
爆米花应助长心采纳,获得100
10秒前
量子星尘发布了新的文献求助10
10秒前
lshao发布了新的文献求助10
12秒前
dove00完成签到,获得积分10
12秒前
奋斗的采蓝完成签到,获得积分20
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Zeolites: From Fundamentals to Emerging Applications 1500
International Encyclopedia of Business Management 1000
Encyclopedia of Materials: Plastics and Polymers 1000
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
Hidden Generalizations Phonological Opacity in Optimality Theory 1000
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4937256
求助须知:如何正确求助?哪些是违规求助? 4204376
关于积分的说明 13065366
捐赠科研通 3982001
什么是DOI,文献DOI怎么找? 2180433
邀请新用户注册赠送积分活动 1196350
关于科研通互助平台的介绍 1108366