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Pregnancy detection and monitoring in cattle via combined foetus electrocardiogram and phonocardiogram signal processing

机译:结合胎儿心电图和心电图信号处理技术对牛进行怀孕检测和监测

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摘要

BackgroundPregnancy testing in cattle is commonly invasive requiring manual rectal palpation of the reproductive tract that presents risks to the operator and pregnancy. Alternative non-invasive tests have been developed but have not gained popularity due to poor specificity, sensitivity and the inconvenience of sample handling. Our aim is to present the pilot study and proof of concept of a new non invasive technique to sense the presence and age (limited to the closest trimester of pregnancy) of the foetus by recording the electrical and audio signals produced by the foetus heartbeat using an array of specialized sensors embedded in a stand alone handheld prototype device. The device was applied to the right flank (approximately at the intercept of a horizontal line drawn through the right mid femur region of the cow and a vertical line drawn anywhere between lumbar vertebrae 3 to 5) of more than 2000 cattle from 13 different farms, including pregnant and not pregnant, a diversity of breeds, and both dairy and beef herds. Pregnancy status response is given “on the spot” from an optimized machine learning algorithm running on the device within seconds after data collection.
机译:背景技术牛的妊娠试验通常是侵入性的,需要人工触诊生殖道,这对操作者和怀孕均构成风险。已经开发出了替代性的非侵入性测试方法,但由于特异性差,敏感性差以及样品处理不便,因此尚未普及。我们的目标是通过记录胎儿心跳产生的电和音频信号,来介绍一种新的非侵入性技术的初步研究和概念验证,以感测胎儿的存在和年龄(仅限于妊娠的最近三个月)。嵌入在独立手持式原型设备中的专用传感器阵列。该设备应用于来自13个不同农场的2000多头牛的右胁腹(大约在穿过母牛右股骨中部区域的水平线与在腰椎3至5之间的任何地方绘制的垂直线的交点处)处,包括怀孕和未怀孕,品种繁多,以及奶牛和牛群。数据收集后几秒钟内,设备上运行的优化的机器学习算法可“现场”提供怀孕状态响应。

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