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Kinematic analysis of forelimb and hind limb joints in clinically healthy sheep

Overview of attention for article published in BMC Veterinary Research, December 2014
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Title
Kinematic analysis of forelimb and hind limb joints in clinically healthy sheep
Published in
BMC Veterinary Research, December 2014
DOI 10.1186/s12917-014-0294-4
Pubmed ID
Authors

Luis G Faria, Sheila C Rahal, Felipe S Agostinho, Bruno W Minto, Lídia M Matsubara, Washington T Kano, Maira S Castilho, Luciane R Mesquita

Abstract

Variations associated with sex, age, velocity, breed and body geometry should be considered in the determination of kinematic parameters for a gait considered normal.Therefore, this study aimed to evaluate kinematic patterns of forelimbs and hind limbs in clinically normal sheep from two different age groups walking at a constant velocity. The hypothesis was that the age may influence sagittal plane kinematic patterns. Fourteen clinically healthy female sheep were divided into Group 1 - seven animals aged from 8 to 12 months, and Group 2 - seven animals aged above 5 years. Before starting data collection, the sheep were trained to be conducted for walking in a pre-determined space at constant velocity. A minimum of 5 valid trials were obtained from the right and left sides of each sheep. Data were analyzed by use of a motion-analysis program. Flexion and extension joint angles (maximum, minimum, displacement), and angular velocity (maximum, minimum) were determined for the shoulder, elbow, carpal, hip, stifle, and tarsal joints.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Luxembourg 1 2%
Austria 1 2%
Unknown 41 93%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 12 27%
Student > Master 6 14%
Student > Ph. D. Student 6 14%
Researcher 5 11%
Student > Doctoral Student 2 5%
Other 4 9%
Unknown 9 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 16%
Medicine and Dentistry 6 14%
Engineering 5 11%
Neuroscience 3 7%
Nursing and Health Professions 2 5%
Other 8 18%
Unknown 13 30%