90 cm高度障碍马前肢运动模型的建立与分析

doi:10.6048/j.issn.1001-4330.2022.11.033

新疆农业科学 ›› 2022, Vol. 59 ›› Issue (11): 2852-2860.DOI: 10.6048/j.issn.1001-4330.2022.11.033

• 马运动生理与健康养殖 • 上一篇

90 cm高度障碍马前肢运动模型的建立与分析

王彤亮¹(), 孟军¹^,², 曾亚琦¹^,², 王建文¹^,², 姚新奎¹^,²()

1.新疆农业大学动物科学学院,乌鲁木齐 830052
2.新疆马繁育与运动生理重点实验室/新疆农业大学马产业研究院,乌鲁木齐 830052

出版日期:2022-11-20 发布日期:2022-12-28
通信作者: 姚新奎
作者简介:王彤亮( 1996- ),男,新疆乌鲁木齐人,硕士研究生,研究方向为动物生产学,( E - mail ) 985868408@qq.com
基金资助:
新疆维吾尔自治区重大科技专项“马繁育共性关键技术研究”(2017A01002-1);中国博士后基金委“不同训练阶段伊犁马血气轨迹在速步中的变化规律研究及对速度的影响”(138620);新疆维吾尔自治区研究生科研创新项目“不同热身程度对伊犁马1 000 m赛后疲劳恢复的影响”(XJ2020G157)

Establishment and Analysis of the 90 cm Forelimb Motion Model of Obstacle Horse

WANG Tongliang¹(), MENG Jun¹^,², ZENG Yaqi¹^,², WANG Jianwen¹^,², YAO Xinkui¹^,²()

1. College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
2. Xinjiang Key Laboratory of Horse Breeding and Sports Physiology, Urumqi 830052, China
3. Institute of Horse Industry, Xinjiang Agricultural University, Urumqi 830052, China

Online:2022-11-20 Published:2022-12-28
Correspondence author: YAO Xinkui
Supported by:
Autonomous Region Key Technology R&D Program" Research on the key technology of horse breeding"(2017A01002-1);China Postdoctoral Science Foundation" Variation Law of Blood Gas Index and Motion Trail in Trotting of Yili Horse in Different Training Period for The Effect of Speed"(138620);Autonomous Region Postgraduate Research and Innovation Project "The Influence of Different Warm-up Degrees on the Fatigue Recovery of Yili Horse after 1000m Race"(XJ2020G157)

摘要/Abstract

摘要：

【目的】测定障碍赛马90 cm高度越障轨迹数据,建立各关节越障运动规律,筛选高斯或多项式最优拟合模型,为障碍赛马性能测定体系建设提供理论支持。【方法】使用高速摄像机收集视频材料,运用MATLAB软件中Curve Fitting tool工具包,采用二、三、四、五阶多项式函数模型和二、三、四、五阶高斯函数模型拟合越障轨迹并对比拟合结果。【结果】肩胛越障时运动规律中高斯函数模型的拟合度极显著优于多项式函数模型(P<0.01);前蹄的越障时运动规律中三阶高斯函数模型极显著优于三阶多项式函数模型(P<0.01);前球节的越障时运动规律中四、五阶高斯函数模型的拟合度极显著优于二、三阶高斯函数模型(P<0.01);肩关节,腕关节的越障时运动规律中多项式函数模型的拟合度显著优于高斯函数模型(P<0.05);肘关节的越障时运动规律与四、五阶多项式函数模型的拟合度极显著优于二、三阶多项式函数模型(P<0.01)。【结论】肩胛、前蹄、前球节的越障运动轨迹更接近“倒钟”型,左右对称。肩关节、腕关节、肘关节的越障运动轨迹左右不对称,曲线平滑。

关键词: 障碍赛马; 运动规律; 运动模型

Abstract:

【Objective】 The obstacle crossing trajectory data at the height of 90cm of steeplecstatics was measured to establish the law of obstacle crossing motion of each joint, and the gaussian or polynomial optimal fitting model was screened to provide theoretical support for the construction of obstacle racing performance measurement system.【Method】 High speed camera was used to collect video materials, and Curve Fitting tool kit in MATLAB was used to fit the obstacle trajectory and match the results with the second, third, fourth and fifth order polynomial function model and the second, third, fourth and fifth order Gaussian function model.【Results】 The fitting degree between the motion law and gaussian function model is significantly better than that of polynomial function model (P<0.01).The motion law and the third-order Gaussian function model of the front hoofs are significantly better than the third-order polynomial function model (P<0.01).The fitting degree of the motion law of the front spherical joint with the fourth - and fifth-order Gaussian function model is significantly better than that of the second - and third-order Gaussian function model (P<0.01).The fitting degree of motion law and polynomial function model of shoulder joint and wrist joint was significantly better than that of Gaussian function model (P<0.05).The fitting degree of the elbow joint motion law and the fourth and fifth order polynomial function model is significantly better than that of the second and third order polynomial function model (P<0.01). 【Conclusion】 It is suitable to fit gaussian function model for the law of obstacle crossing movement of scapula, fore hoof and fore Fetlock joint.The obstacle breaking motion law of shoulder, wrist and elbow is suitable to fit the polynomial function model.The related reference indexes of obstacle racing performance measurement.

Key words: show jumping; law of motion; motion model

王彤亮, 孟军, 曾亚琦, 王建文, 姚新奎. 90 cm高度障碍马前肢运动模型的建立与分析[J]. 新疆农业科学, 2022, 59(11): 2852-2860.

WANG Tongliang, MENG Jun, ZENG Yaqi, WANG Jianwen, YAO Xinkui. Establishment and Analysis of the 90 cm Forelimb Motion Model of Obstacle Horse[J]. Xinjiang Agricultural Sciences, 2022, 59(11): 2852-2860.

图/表 6

参考文献 22

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函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	149.200(128.400~405.150)^Aa	0.943(0.918~0.969)^Bc	1.429(1.400~2.381)^Aa
三阶多项式 Third-order polynomial	102.500(67.770~154.950)^Ab	0.975(0.965~0.983)^ABb	1.256(0.958~1.493)^Ab
四阶多项式 Fourth-order polynomial	38.510(30.380~48.200)^ABc	0.991(0.988~0.993)^ABCb	0.776(0.681~0.830)^ABbc
五阶多项式 Fifth-order polynomial	28.710(19.245~41.145)^BCb	0.992(0.988~0.996)^Aa	0.675(0.534~0.784)^Bbc
二阶高斯 Second order gauss	30.740(16.620~45.995)^BCb	0.992(0.987~0.997)^Aa	0.699(0.493~0.825)^Bbc
三阶高斯 Third-order gauss	17.000(10.665~31.945)^BCb	0.997(0.989~0.998)^Aa	0.512(0.403~0.733)^Bc
四阶高斯 Fourth-order gauss	12.670(7.668~24.065)^BCb	0.998(0.991~0.998)^Aa	0.452(0.350~0.639)^Bc
五阶高斯 Fourth-order gauss	9.106(9.006~36.085)^BCb	0.996(0.993~0.998)^Aa	0.411(0.394~0.746)^Bc

函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	149.200(128.400~405.150)^Aa	0.943(0.918~0.969)^Bc	1.429(1.400~2.381)^Aa
三阶多项式 Third-order polynomial	102.500(67.770~154.950)^Ab	0.975(0.965~0.983)^ABb	1.256(0.958~1.493)^Ab
四阶多项式 Fourth-order polynomial	38.510(30.380~48.200)^ABc	0.991(0.988~0.993)^ABCb	0.776(0.681~0.830)^ABbc
五阶多项式 Fifth-order polynomial	28.710(19.245~41.145)^BCb	0.992(0.988~0.996)^Aa	0.675(0.534~0.784)^Bbc
二阶高斯 Second order gauss	30.740(16.620~45.995)^BCb	0.992(0.987~0.997)^Aa	0.699(0.493~0.825)^Bbc
三阶高斯 Third-order gauss	17.000(10.665~31.945)^BCb	0.997(0.989~0.998)^Aa	0.512(0.403~0.733)^Bc
四阶高斯 Fourth-order gauss	12.670(7.668~24.065)^BCb	0.998(0.991~0.998)^Aa	0.452(0.350~0.639)^Bc
五阶高斯 Fourth-order gauss	9.106(9.006~36.085)^BCb	0.996(0.993~0.998)^Aa	0.411(0.394~0.746)^Bc

函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	307.100(170.250~452.350)^ABCDab	0.941(0.900~0.962)^ABCbcd	2.174(1.573~2.5100)^ABCab
三阶多项式 Third-order polynomial	129.600(69.325~171.350)^BCDbc	0.972(0.967~0.985)^ABCabc	1.423(0.972~1.558)^ABCbc
四阶多项式 Fourth-order polynomial	35.880(29.990~47.050)^CDbc	0.993(0.990~0.994)^ABab	0.727(0.681~0.816)^BCbc
五阶多项式 Fifth-order polynomial	33.250(19.325~44.415)^Dc	0.994(0.990~0.996)^Aa	0.702(0.545~0.807)^Cc
二阶高斯 Second order gauss	520.100(453.200~803.400)^Aa	0.863(0.8479~0.906)^Cd	2.883(2.652~3.361)^Aa
三阶高斯 Third-order gauss	474.000(428.500~753.850)^ABa	0.876(0.854~0.915)^Ad	2.747(2.641~3.3505)^ABa
四阶高斯 Fourth-order gauss	461.000(410.950~755.850)^ABCa	0.879(0.85645~0.917)^BCcd	2.761(2.651~3.435)^Aa
五阶高斯 Fourth-order gauss	399.900(17.502~463.300)^ABCDabc	0.922(0.873~0.997)^ABCabcd	2.724(0.527~2.869)^ABCabc

函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	307.100(170.250~452.350)^ABCDab	0.941(0.900~0.962)^ABCbcd	2.174(1.573~2.5100)^ABCab
三阶多项式 Third-order polynomial	129.600(69.325~171.350)^BCDbc	0.972(0.967~0.985)^ABCabc	1.423(0.972~1.558)^ABCbc
四阶多项式 Fourth-order polynomial	35.880(29.990~47.050)^CDbc	0.993(0.990~0.994)^ABab	0.727(0.681~0.816)^BCbc
五阶多项式 Fifth-order polynomial	33.250(19.325~44.415)^Dc	0.994(0.990~0.996)^Aa	0.702(0.545~0.807)^Cc
二阶高斯 Second order gauss	520.100(453.200~803.400)^Aa	0.863(0.8479~0.906)^Cd	2.883(2.652~3.361)^Aa
三阶高斯 Third-order gauss	474.000(428.500~753.850)^ABa	0.876(0.854~0.915)^Ad	2.747(2.641~3.3505)^ABa
四阶高斯 Fourth-order gauss	461.000(410.950~755.850)^ABCa	0.879(0.85645~0.917)^BCcd	2.761(2.651~3.435)^Aa
五阶高斯 Fourth-order gauss	399.900(17.502~463.300)^ABCDabc	0.922(0.873~0.997)^ABCabcd	2.724(0.527~2.869)^ABCabc

函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	246.400(95.940~635.000)^Aa	0.953(0.887~0.972)^Bc	1.837(1.210~2.969)^Aa
三阶多项式 Third-order polynomial	74.460(47.760~122.340)^ABb	0.982(0.977~0.989)^ABb	1.017(0.863~1.320)^ABb
四阶多项式 Fourth-order polynomial	44.310(17.600~79.985)^ABb	0.994(0.986~0.994)^Aab	0.790(0.527~1.081)^ABb
五阶多项式 Fifth-order polynomial	36.330(13.276~53.825)^Bb	0.994(0.991~0.996)^Aa	0.731(0.457~0.881)^Bb
二阶高斯 Second order gauss	8236(4244.500~8696.500)	-0.411(-0.549~-0.246)	11.080(8.267~11.230)
三阶高斯 Third-order gauss	8232(1955.675~8689.500)	-0.410(-0.5483~0.342)	11.33(4.334~11.480)
四阶高斯 Fourth-order gauss	8231(4240~8688.500)	-0.410(-0.548~-0.244)	11.600(8.694~11.750)
五阶高斯 Fourth-order gauss	4585(1958.740~8283.500)	-0.410(-0.548~0.410)	9.301(4.596~11.900)

90 cm高度障碍马前肢运动模型的建立与分析

Establishment and Analysis of the 90 cm Forelimb Motion Model of Obstacle Horse

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参考文献 22

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Metrics

函数类别	和方差 SSE	拟合度 R²	均方差 RMSE
二阶多项式 Second-order polynomial	1458.000(1199.300~1679.000)^Aa	0.895(0.857~0.906)^Bb	4.869(4.468~5.278)^Aa
三阶多项式 Third-order polynomial	41.600(33.825~113.535)^Bb	0.996(0.992~0.997)^Aa	0.886(0.752~1.339)^Bb
四阶多项式 Fourth-order polynomial	30.530(22.355~70.380)^Bb	0.998(0.994~0.998)^Aa	0.737(0.622~1.046)^Bb
五阶多项式 Fifth-order polynomial	22.860(13.945~57.230)^Bb	0.998(0.996~0.999)^Aa	0.670(0.493~0.951)^Bb
二阶高斯 Second order gauss	27670(24810~32680)	-1.213(-1.424~-1.112)	22.520(21.360~23.045)
三阶高斯 Third-order gauss	27390(11157.850~32680)	-1.112(-1.425~-0.059)	23.170(11.384~23.630)
四阶高斯 Fourth-order gauss	22230(309.433~27530)	-1.213(-1.425~0.081)	22.230(1.842~23.480)
五阶高斯 Fourth-order gauss	28950(28993~29425)	-1.219(-1.350~0.098)	22.055(21.7481~24.635)

函数类别	和方差SSE	拟合度R²	均方差RMSE
二阶多项式 Second-order polynomial	137.500(76.540~250.900)^Aa	0.989(0.980~0.992)^Df	1.553(1.223~2.138)^Aa
三阶多项式 Third-order polynomial	108.000(70.285~204.800)^ABab	0.990(0.985~0.992)^CDef	1.469(1.184~1.872)^ABab
四阶多项式 Fourth-order polynomial	55.150(21.520~106.785)^ABCabc	0.995(0.991~0.998)^BCDde	1.058(0.639~1.378)^ABCabc
五阶多项式 Fifth-order polynomial	14.950(12.119~42.315)^BCDcd	0.999(0.997~0.999)^ABbc	0.547(0.494~0.838)^BCDcde
二阶高斯 Second order gauss	24.670(18.740~74.310)^ABCbc	0.998(0.994~0.998)^BCDcd	0.676(0.619~1.120)^ABCbc
三阶高斯 Third-order gauss	15.550(11.189~51.575)^ABCDcd	0.999(0.996~0.999)^ABCbcd	0.552(0.503~0.949)^ABCDcd
四阶高斯 Fourth-order gauss	8.929(4.505~14.890)^CDde	0.999(0.999~0.999)^ABab	0.427(0.328~0.564)^Cde
五阶高斯 Fourth-order gauss	6.199(3.848~7.888)^De	0.999(0.999~0.999)^Aa	0.387(0.300~0.437)^De

函数类别	和方差SSE	拟合度R²	均方差RMSE
二阶多项式 Second-order polynomial	309.900(130.005~480.150)^Aa	0.980(0.961~0.988)^Dd	2.475(1.580~2.955)^Aa
三阶多项式 Third-order polynomial	128.100(70.015~157.900)^Bab	0.991(0.987~0.993)^CDcd	1.550(1.190~1.742)^Aab
四阶多项式 Fourth-order polynomial	58.600(50.850~101.490)^ABb	0.994(0.993~0.995)^ABCDc	1.129(1.028~1.357)^ABCb
五阶多项式 Fifth-order polynomial	51.770(49.060~68.720) ^ABCbc	0.995(0.995~0.996)^ABCbc	1.040(1.021~1.150)^ABCb
二阶高斯 Second order gauss	66.480(50.685~115.900)^ABb	0.994(0.993~0.995)^BCDc	1.215(1.036~1.471)^ABab
三阶高斯 Third-order gauss	36.050(20.865~46.650) ^BCcd	0.997(0.996~0.998)^ABab	0.895(0.681~0.989)^BCc
四阶高斯 Fourth-order gauss	25.210(16.110~30.635)^Cd	0.998(0.997~0.999)^Aa	0.766(0.602~0.864)^Cc
五阶高斯 Fourth-order gauss	12.310(10.799~60.455)^BCcd	0.999(0.995~0.999)^ABab	0.577(0.532~1.115)^BCc