摘要
为准确提取步态特征、识别奶牛跛行,利用三维加速度传感器采集30头奶牛后趾加速度信号,针对奶牛步态人工分割的不足,提出基于改进的动态时间规整算法对奶牛步态进行分割,提取特征值并利用逻辑回归法建立跛行识别模型。采用本文方法得到的步态分割精确度、灵敏度、准确率平均值分别为89.53%、95.51%、87.49%,比常规动态时间规整算法分别提高了5.31、4.48、8.43个百分点,总体准确率达到90.57%,相较自相关函数法和峰值检测法分别提高了1.75、3.13个百分点。以支撑时间、步幅长度、平均强度、信号幅度面积、前进方向加速度均值和运动变化量为自变量的跛行识别模型识别率分别为83.44%、81.72%、86.15%、86.81%、89.45%和85.71%。本研究结果可为奶牛步态分割、跛行识别提供技术支持。
Lameness,as the second major disease affecting cows,has exerted great influence on the economic benefits and welfare rearing of the pasture.The accurate extraction of gait features is the key to recognizing lameness,while the precise segmentation of gait is the prerequisite.In view of the shortcomings in the current artificial segmentation of cow gait,an automatic method of cow gait segmentation was proposed based on the improved dynamic time warping algorithm.In the pasture,21 sound cows and 9 lame cows were selected.The acceleration signals of their hind legs were collected by three-dimensional accelerometers through a measuring channel with a length of 23 m.The gold standard data were obtained by shooting walking videos with a high-speed camera.The algorithm segmented a single stride from a continuous gait sequence,extracted the gait feature values,and established a model of recognizing cow lameness using the method of logical regression.The experimental results showed that the segmentation of gait precision,sensitivity and accuracy were 89.53%,95.51%and 87.49%,respectively.Compared with the values obtained by the conventional dynamic time warping algorithm,the average precision,sensitivity and accuracy of gait segmentation obtained by this algorithm were improved by 5.31,4.48 and 8.43 percentage points,respectively.Besides,there were 1.75 and 3.13 percentage points of increase compared with the autocorrelation function method and peak detection method,and the total accuracy reached 90.57%.The total recognition rate of the lameness recognition model arrived at 83.44%,81.72%,86.15%,86.81%,89.45%and 85.71%,respectively,taking the stance time,stride length,average intensity,signal amplitude area,average acceleration in the forward direction and movement variation as independent variables.Hopefully,the results can provide technical support for gait segmentation and lameness recognition.
作者
苏力德
张永
王健
尹玉
宗哲英
巩彩丽
SU Lide;ZHANG Yong;WANG Jian;YIN Yu;ZONG Zheying;GONG Caili(College of Mechanical and Electrical Engineering,Inner Mongolia Agricultural University,Huhhot 010018,China;College of Electronic Information Engineering,Inner Mongolia University,Huhhot 010021,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2020年第7期52-59,共8页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(61563042)
内蒙古自治区“草原英才”工程现代农牧业工程新技术研发及应用创新人才项目(内组通字[2018]19号)
“双一流”学科创新团队建设人才培育项目(NDSC2018-08)
内蒙古农业大学高层次人才引进科研启动项目(NDGCC2016-03)。
关键词
奶牛
跛行
步态分割
三维加速度传感器
动态时间规整
逻辑回归
dairy cattle
lameness
segmentation of gait
three-dimensional accelerometer
dynamic time warping
logistic regression
