4.7 Article

A 2D stick model for simulation of sow walking on concrete floors and detection of sow lameness

期刊

BIOSYSTEMS ENGINEERING
卷 226, 期 -, 页码 99-115

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2022.12.011

关键词

Stick model; Sow gait; Concrete floor; Lameness detection

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A 2D stick model was developed to simulate sow walking on concrete floors. Video images of sows walking on concrete floors were analyzed and translated into a 2D coordinate dataset. The motion of each landmark was calculated, and a step of walking was modeled as three consecutive phases of motion. The joint coordinates at each time step were used to calculate characteristic gait parameters for lameness detection with an accuracy greater than 92%.
A 2D stick model was developed to simulate sow walking on concrete floors. The model consisted of thirteen connective body joints to form a simple stick figure that approximates a sow's body skeleton. The video images of sows with reflective markers on their bodies walking along a corridor of concrete floor were analysed and translated into a 2D coordi-nate dataset. The motion of each landmark, including displacement, velocity and accel-eration were calculated. A step of walking was modelled as three consecutive phases of motion: acceleration of foot leaving the ground; constant speed of foot swinging; and deceleration of foot touching the ground. One gait cycle was separated into several time steps and the movements of each joint at a time step in the horizontal (x) and vertical (y) directions were described by a combination of first and 2nd order polynomial functions. The coordinates of all joints were calculated in the x-and y-directions and these joints were then linked by synchronizing the motions of each joint at a given time step. The joint coordinates at each time step were then used to calculate a selected set of characteristic gait parameters, including the stride length and stance time for fore-and hindlimbs, diagonality, back angle and walking speed. Based on the comparisons of the predicted gait parameters between the lame and non-lame sows, the criteria were established for using the predicted gait parameters to detect sow lameness. The results showed an accuracy greater than 92% for lameness detection. Crown Copyright (c) 2022 Published by Elsevier Ltd on behalf of IAgrE. All rights reserved.

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